ppxscal/embedding_network huggingface dataset:
Kalman filter-based channel estimation and ICI suppression for high-mobility OFDM systems
Authors: Prerana Gupta, D. K. Mehra
Venue: International Journal of Communication Systems (2008)

The use of orthogonal frequency division multiplexing (OFDM) in frequency-selective fading environments has been well explored. However, OFDM is more prone to time-selective fading compared with single-carrier systems. Rapid time variations destroy the subcarrier orthogonality and introduce inter-carrier interference (ICI). Besides this, obtaining reliable channel estimates for receiver equalization is a non-trivial task in rapidly fading systems. Our work addresses the problem of channel estimation and ICI suppression by viewing the system as a state-space model. The Kalman filter is employed to estimate the channel; this is followed by a time-domain ICI mitigation filter that maximizes the signal-to-interference plus noise ratio (SINR) at the receiver. This method is seen to provide good estimation performance apart from significant SINR gain with low training overhead. Suitable bounds on the performance of the system are described; bit error rate (BER) performance over a time-invariant Rayleigh fading channel serves as the lower bound, whereas BER performance over a doubly selective system with ICI as the dominant impairment provides the upper bound. Copyright &copy; 2008 John Wiley & Sons, Ltd.
The set-valued mapping based on ample fields
Authors: Xue-Hai Yuan, Hong-Xing Li, Cheng Zhang
Venue: Computers Mathematics with Applications (2008)

Ample fields play an important role in possibility theory. Based on the ample fields in possibility theory, two new concepts such as possibilistic set and possibility mapping are presented. A theoretical approach to define operations and implication operations of fuzzy sets based on the theory of falling shadows of possibilistic sets is established, and the category PosM of ample spaces and possibility mappings and the category @X(@W,A) of possibilistic sets are built up respectively. It is proved that the category @X(@W,A) is a topos.
Formal models and algorithms for decentralized decision making under uncertainty
Authors: Sven Seuken, Shlomo Zilberstein
Venue: Autonomous Agents and Multi-Agent Systems (2008)

Over the last 5 years, the AI community has shown considerable interest in decentralized control of multiple decision makers or "agents" under uncertainty. This problem arises in many application domains, such as multi-robot coordination, manufacturing, information gathering, and load balancing. Such problems must be treated as decentralized decision problems because each agent may have different partial information about the other agents and about the state of the world. It has been shown that these problems are significantly harder than their centralized counterparts, requiring new formal models and algorithms to be developed. Rapid progress in recent years has produced a number of different frameworks, complexity results, and planning algorithms. The objectives of this paper are to provide a comprehensive overview of these results, to compare and contrast the existing frameworks, and to provide a deeper understanding of their relationships with one another, their strengths, and their weaknesses. While we focus on cooperative systems, we do point out important connections with game-theoretic approaches. We analyze five different formal frameworks, three different optimal algorithms, as well as a series of approximation techniques. The paper provides interesting insights into the structure of decentralized problems, the expressiveness of the various models, and the relative advantages and limitations of the different solution techniques. A better understanding of these issues will facilitate further progress in the field and help resolve several open problems that we identify.
Note: Jordan canonical form of Pascal-type matrices via sequences of binomial type
Authors: Sheng-liang Yang
Venue: Discrete Applied Mathematics (2008)

In this paper, we study the Jordan canonical form of the generalized Pascal functional matrix associated with a sequence of binomial type, and demonstrate that the transition matrix between the generalized Pascal functional matrix and its Jordan canonical form is the iteration matrix associated with the binomial sequence. In addition, some combinatorial identities are derived from the corresponding matrix factorization.
Sentence-Level Evaluation Using Co-occurences of N-Grams
Authors: Theologos Athanaselis, Stelios Bakamidis, Konstantinos Mamouras, Ioannis Dologlou
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

This work presents an evaluation method of Greek sentences with respect to word order errors. The evaluation method is based on words' reordering and choosing the version that maximizes the number of trigram hits according to a language model. The new parameter of the proposed technique concerns the incorporation of unigram probability. This probability corresponds to the frequency of each unigram to be posed in the first and in the last position of the training set sentences. The comparative advantage of this method is that it works with a large set of words, and avoids the laborious and costly process of collecting word order errors for creating error patterns.
Evaluating Learning Automata as a Model for Cooperation in Complex Multi-agent Domains
Authors: Mohammad Reza Khojasteh, Mohammad Reza Meybodi
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

Learning automata act in a stochastic environment and are able to update their action probabilities considering the inputs from their environment, so optimizing their functionality as a result. In this paper, the goal is to investigate and evaluate the application of learning automata to cooperation in multi-agent systems, using soccer simulation server as a test bed. We have also evaluated our learning method in hard situations such as malfunctioning of some of the agents in the team and in situations that agents' sense/act abilities have a lot of noise involved. Our experiment results show that learning automata adapt well with these situations.
On Phase Transitions in Learning Sparse Networks
Authors: Goele Hollanders, Geert Jan Bex, Marc Gyssens, Ronald L. Westra, Karl Tuyls
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

In this paper we study the identification of sparse interaction networks as a machine learning problem. Sparsity mean that we are provided with a small data set and a high number of unknown components of the system, most of which are zero. Under these circumstances, a model needs to be learned that fits the underlying system, capable of generalization. This corresponds to the student-teacher setting in machine learning. In the first part of this paper we introduce a learning algorithm, based on L 1-minimization, to identify interaction networks from poor data and analyze its dynamics with respect to phase transitions. The efficiency of the algorithm is measured by the generalization error, which represents the probability that the student is a good fit to the teacher. In the second part of this paper we show that from a system with a specific system size value the generalization error of other system sizes can be estimated. A comparison with a set of simulation experiments show a very good fit.
Basic consideration for SIL calculation in safety systems
Authors: J. Börcsök, P. Holub
Venue: Proceedings of the 7th WSEAS International Conference on Applied Computer and Applied Computational Science (2008)

Safety instrumented systems might be evaluated regarding their safety-relevant availability in the occurrence of an error. By means of the procedures indicated in the IEC/EN 61508 standard such a value, called Probability of Failure on Demand (PFD), can be determined. The standard IEC/EN 61508 serves as generic standard for the development of sensitive electrical, electronic and programmable electronic systems. This standard supplies qualitative and quantitative criteria to evaluate safety related systems, in order to apply it in safety critical applications. The purpose of this paper is to describe the criterion PFD, to derive the necessary equations and to calculate the PFD-values for the 1oo2-architecture. The PFD value indicates the quality of a system.
Capturing User Interests by Both Exploitation and Exploration
Authors: Ka Cheung Sia, Shenghuo Zhu, Yun Chi, Koji Hino, Belle L. Tseng
Venue: Proceedings of the 11th international conference on User Modeling (2007)

Personalization is one of the important research issues in the areas of information retrieval and Web search. Providing personalized services that are tailored toward the specific preferences and interests of a given user can enhance her experience and satisfaction. However, to effectively capture user interests is a challenging research problem. Some challenges include how to quickly capture user interests in an unobtrusive way, how to provide diversified recommendations, and how to track the drifts of user interests in a timely fashion. In this paper, we propose a model for learning user interests and an algorithm that actively captures user interests through an interactive recommendation process. The key advantage of our algorithm is that it takes into account both exploitation (recommending items that belong to users' core interest) and exploration (discovering potential interests of users). Extensive experiments using synthetic data and a user study show that our algorithm can quickly capture diversified user interests in an unobtrusive way, even when the user interests may drift along time.
Category-Based Rough Induction
Authors: Marcin Wolski
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

The present paper is concerned with Rough Set Theory (RST) and Similarity Coverage Model (SCM) of category-based induction. It redefines basic concepts of RST in the light of SCM, and explains how RST may be seen as an elegant formal model of inductive reasoning. Furthermore, following SCM, we enrich RST by the concept of an ontology defined as a subset of the family of all definable sets. The paper also presents a model of inductive reasoning which is driven by recent works on RST and nearness-type structures. We show how approximation spaces can be characterised in terms of non-Archimedean nearness spaces.
Rank Lower Bounds for the Sherali-Adams Operator
Authors: Mark Rhodes
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

We consider the Sherali-Adams (SA) operator as a proof system for integer linear programming and prove linear lower bounds on the SA rank required to prove both the pigeon hole and least number principles. We also define the size of a SA proof and show that that while the pigeon hole principle requires linear rank, it only requires at most polynomial size.
MetaLinks: Authoring and Affordances for Conceptual and Narrative Flow in Adaptive Hyperbooks
Authors: Tom Murray
Venue: International Journal of Artificial Intelligence in Education (2003)

MetaLinks, an authoring tool and web server for adaptive hyperbooks, is described. MetaLinks hyperbooks provide textbook-like content in a flexible manner that supports opportunistic processes of active reading and learning. Through adaptive methods a single on-line artifact can address the diverse needs of a variety of user goals and backgrounds. The system is designed to support inquiry, exploratory, or curiosity-driven learning in richly interconnected material and to ameliorate a number of usability issues that arise in such open ended learning environments. Chief among the usability issues addressed are the potential for discontinuous conceptual and narrative flow as users navigate flexibly and idiosyncratically through hyperbook content. Our goals are addressed through a number of interface features and adaptive methods including narrative smoothing, custom depth control, and thematic links. In this paper we describe the MetaLinks system, discuss a number of hyperbook design issues, and give the results of two formative evaluations of a MetaLinks Hyperbook.
Incorporating Learning in Grid-Based Randomized SAT Solving
Authors: Antti E. Hyvärinen, Tommi Junttila, Ilkka Niemelä
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

Computational Grids provide a widely distributed computing environment suitable for randomized SAT solving. This paper develops techniques for incorporating learning, known to yield significant speed-ups in the sequential case, in such a distributed framework. The approach exploits existing state-of-the-art clause learning SAT solvers by embedding them with virtually no modifications. We show that for many industrial SAT instances, the expected run time can be decreased by carefully combining the learned clauses from the distributed solvers. We compare different parallel learning strategies by using a representative set of benchmarks, and exploit the results to devise an algorithm for learning-enhanced randomized SAT solving in Grid environments. Finally, we experiment with an implementation of the algorithm in a production level Grid and solve several problems which were not solved in the SAT 2007 solver competition.
Directions in Locative Media
Authors: Jeremy Hight
Venue: IEEE MultiMedia (2008)

Editor's NoteIn 2002, Jeremy Hight was involved in the project 34 North 118 West, one of the seminal works of what became known as locative media. He also wrote one of the seminal texts of the field, Narrative Archaeology. Here he discusses the process of conceptualizing and making the work and how it has fueled his latest projects with locative narratives.&#x2014;Maria Miranda
Quantitative Morphodynamic Analysis of Time-Lapse Imaging by Edge Evolution Tracking
Authors: Yuki Tsukada, Yuichi Sakumura, Shin Ishii
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

To perform morphodynamic profiling from time lapse images of neurite outgrowth, we developed an edge evolution tracking (EET) algorithm, by which cell boundary movements including an arbitrary complex boundary transition are quantified. This algorithm enables us to estimate temporal evolution of cellular edge, and thus to trace the transition of any objective edge movements. We show advantages of EET by comparing it with the other two methods on an artificial data set that imitates neural outgrowth. We also demonstrate the usefulness of our EET by applying it to a data set of time-lapse imaging of neural outgrowth. The results show verification of quantitative profiling for arbitrary complex cell boundary movements.
Evaluation of Critical Infrastructures: Challenges and Viable Approaches
Authors: Silvano Chiaradonna, Felicita Giandomenico, Paolo Lollini
Venue: Architecting Dependable Systems V (2008)

Critical Infrastructures (CI) are complex and highly interdependent systems, networks and assets that provide essential services in our daily life. Given the increasing dependence upon such critical infrastructures, research and investments in identifying their vulnerabilities and devising survivability enhancements are recognized paramount by many countries. Understanding and analyzing interdependencies and interoperabilities between different critical infrastructures and between the several heterogeneous subsystems each infrastructure is composed of, are among the most challenging aspects faced today by designers, developers and operators in these critical sectors. Assessing the impact of interdependencies on the ability of the system to provide resilient and secure services is of primarily importance; following this analysis, steps can be taken to mitigate vulnerabilities revealed in critical assets. This paper addresses the analysis of CI, with focus on interdependencies between the involved subsystems. In particular, the experience gained by the authors in an on-going European project is reported and discussed, both in terms of identified challenges and in viable approaches under investigation.
GFE --- Graphical Finite State Machine Editor for Parallel Execution
Authors: David Obdrzalek, Jan Benda
Venue: Proceedings of the 6th international conference on Entertainment Computing (2007)

In this paper we present GFE --- the Graphical FSM (Finite State Machine) Editor based on the Grafcet SFC (Sequential Function Chart) model. The GFE takes advantage of automated code generation and provides strong tools for complex control. At the same time it gives a high-level overview of the entire robotic control architecture. A complex control system may be designed, tested and deployed using visual approach. This is particularly useful for education where the students do not have to start always from scratch, or for young robot builders who are not as experienced in low-level programming. Once a control library is implemented for a particular robot, it may be reused and the robot may be programmed using solely graphical approach, because the most complicated part of controller design - the state machine - is automatically generated. This avoids typing errors and allows fast and simple redesign.
Cooperative Approaches to Bacterial Foraging Optimization
Authors: Hanning Chen, Yunlong Zhu, Kunyuan Hu, Xiaoxian He, Ben Niu
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

Bacterial Foraging Optimization (BFO) is a novel optimization algorithm based on the foraging behavior of E. coli bacteria. This paper presents a variation on the original BFO algorithm, called Cooperative Bacterial Foraging Optimization (CBFO), which significantly improve the convergence speed, accuracy and robustness of original BFO in solving complex optimization problems. This is achieved by applying two cooperative approaches to the BFO, namely the serial heterogeneous cooperation on the implicit space decomposition level and the serial heterogeneous cooperation on the hybrid space decomposition level. Four widely-used benchmark functions have been implemented to test the proposed algorithm, and the results show remarked improvement in performance over the original BFO.
ANTS: A Complete System for Automatic News Programme Annotation Based on Multimodal Analysis
Authors: A. Messina, R. Borgotallo, G. Dimino, D. Airola Gnota, L. Boch
Venue: Proceedings of the 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services (2008)

This paper describes an integrated sytem for the acquisition, automatic annotation and web publication of television broadcast news programmes named ANTS (Automatic Newscast Transcription System). The system consists of several analysis components integrated in a unified architecture. Users have the possibility to access a large daily-growing database of news stories from the main national channels, all identified, categorised and published in a fully automatic way. The system identifies story boundaries, extracts texts from spoken content, classifies stories by subject and links external relevant information coming from the web. Performances of the system have been evaluated in a real-life scenario, by providing an instance of the system to a panel of professional users inside RAI. The strength of the approach behind \ANTS consists in the ability to integrate several heterogeneous analysis components in a performant and ready-for-production environment, capable of elaborating many hours of material per day without significant service drops and with sufficiently good accuracy for industrial employment in large broadcasting facilities.
Weighted Cluster Ensemble Using a Kernel Consensus Function
Authors: Sandro Vega-Pons, Jyrko Correa-Morris, José Ruiz-Shulcloper
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

Cluster ensemble is a good alternative to face the problem of data clustering. Some studies based on mathematical models have shown that cluster ensemble methods lead to an effective improvement of the results of the standard clustering algorithms. In this paper, we focus on this problem, proposing a new approach to solve it, by adding a new step into the usual cluster ensemble methodology. Representing partitions by graphs and a new kernel function to measure the similarity between partitions are other proposals for this work. Experiments with synthetic and real databases show the suitability and effectiveness of our method.
Users with Disabilities: Maximum Control with Minimum Effort
Authors: Julio Abascal
Venue: Proceedings of the 5th international conference on Articulated Motion and Deformable Objects (2008)

People with disabilities can benefit greatly from services provided by computers and robots. Access to remote communications and information as well as to interpersonal communication and environmental control are assisted by current ubiquitous computers, wired and wireless networks and intelligent environments. Sensory, physical or/and cognitive restrictions to interacting with computers can be avoided by means of alternative interaction devices and procedures. Nevertheless, alternative methods are usually much slower than standard communications, frequently leading users with disabilities into unbalanced or unsafe situations. Therefore, the main challenge of human-machine interaction systems that have to be used by people with disabilities is to obtain the maximum communication and control with the minimum physical and cognitive effort from the user. This lecture overviews the main techniques used to optimize the control and communication flow, resulting in higher user satisfaction and security.
Visualization of dilute hydrogen jet flame in air flow
Authors: S. Chinone, N. Fujisawa
Venue: Journal of Visualization (2004)

The structure of hydrogen jet flame diluted by CO$_2$ in air flow is studied by various visualization techniques, such as schlieren, direct photograph, tracer injection and reactive Mie scattering method, which allow understanding of the influence of CO$_2$ on the characteristics of the hydrogen jet flame. The experimental result indicates that the flame structure consists of laminar fuel jet and surrounding reaction zone near the nozzle exit. When the CO$_2$ fraction is increased, the width of the fuel jet grows and the reaction zone is reduced in size. These observations are further confirmed by quantitative measurements of temperature and velocity fields in the flame, which are evaluated by thermocouple and particle image velocimetry (PIV), respectively. These results indicate that the flame temperature is decreased and the flow rate of the fuel jet is increased by the influence of diluents, which are due to the reduced calorific value and larger density of fuel, respectively.
Adaptive Middleware for Distributed Sensor Environments
Authors: Xingbo Yu, Koushik Niyogi, Sharad Mehrotra, Nalini Venkatasubramanian
Venue: IEEE Distributed Systems Online (2003)

Distributed sensor environments are emerging as a feasible solution to various datacollection applications. However, energy constraints on sensor nodes, which areusually battery powered, hinder the successful deployment of such networks. Aproposed adaptive middleware framework for energy-aware information collectionin sensor networks will ensure overall application quality while reducingcommunication overhead.