ppxscal/embedding_network huggingface dataset:
A mailbox ownership based mechanism for curbing spam
Authors: Nadeem Jamali, Hongxing Geng
Venue: Computer Communications (2008)

Not only does Spam put strain on computational and network resources, it also drains the attention resource of users. Existing approaches to combat spam make decisions on per sender or per message basis. Where the former demands explicit intervention by users, the latter suffers from false negatives and positives. We take an owned-resource view of email spam. An email recipient's attention space as well as computational and network resources devoted to handling email are viewed as precious owned resources. Anyone interested in using these resources - by sending a message which must be delivered and stored on a server and subsequently viewed in a list of received messages, and possibly read - must purchase the resource in the form of sending rights. These rights may be to resources owned by individuals and groups, and may also be owned by individuals or group. Our approach is based on the CyberOrgs model for encapsulating distributed owned resources for multi-agent computations. The model uses a small set of primitive operations to enable multi-agent computations to engage in a rich set of interactions in a market of owned resources. We have developed key mechanisms to enable message senders and recipients to negotiate contracts for mailbox access, as well as to construct policies leading to implicit and automatic negotiations for typical cases. A prototype implementation is described, and examples of policies are presented. Experimental results show that system performance is policy-dependent: as long as policies are carefully designed, negotiation overhead is minimal.
Modeling Appraisal in Theory of Mind Reasoning
Authors: Mei Si, Stacy C. Marsella, David V. Pynadath
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

Cognitive appraisal theories, which link human emotional experience to their interpretations of events happening in the environment, are leading approaches to model emotions. In this paper, we investigate the computational modeling of appraisal in a multi-agent decision-theoretic framework using POMDP based agents. We illustrate how five key appraisal dimensions (motivational relevance, motivation congruence, accountability, control and novelty) can be derived from the processes and information required for the agent's decision-making and belief maintenance. Through this illustration, we not only provide a solution for computationally modeling emotion in POMDP based agents, but also demonstrate the tight relationship between emotion and cognition. Our model of appraisal is applied to three different scenarios to illustrate its usage. We also discuss how the modeling of theory of mind (recursive beliefs about self and others) is critical for simulating social emotions.
A High Precision Information Retrieval Method for WiQA
Authors: Constantin Orăsan, Georgiana Puşcaşu
Venue: Evaluation of Multilingual and Multi-modal Information Retrieval: 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006, Alicante, Spain, September 20-22, 2006, Revised Selected Papers (2007)

This paper presents Wolverhampton University's participation in the WiQA competition. The method chosen for this task combines a high precision, but low recall information retrieval approach with a greedy sentence ranking algorithm. The high precision retrieval is ensured by querying the search engine with the exact topic, in this way obtaining only sentences which contain the topic. In one of the runs, the set of retrieved sentences is expanded using coreferential relations between sentences. The greedy algorithm used for ranking selects one sentence at a time, always the one which adds most information to the set of sentences without repeating the existing information too much. The evaluation revealed that it achieves a performance similar to other systems participating in the competition and that the run which uses coreference obtains the highest MRR score among all the participants.
Oscillations and spiking pairs: Behavior of a neuronal model with stdp learning
Authors: Xi Shen, Xiaobin Lin, Philippe De Wilde
Venue: Neural Computation (2008)

In a biologically plausible but computationally simplified integrate-and-fire neuronal population, it is observed that transient synchronized spikes can occur repeatedly. However, groups with different properties exhibit different periods and different patterns of synchrony. We include learning mechanisms in these models. The effects of spike-timing-dependent plasticity have been known to play a distinct role in information processing in the central nervous system for several years. In this letter, neuronal models with dynamical synapses are constructed, and we analyze the effect of STDP on collective network behavior, such as oscillatory activity, weight distribution, and spike timing precision. We comment on how information is encoded by the neuronal signaling, when synchrony groups may appear, and what could contribute to the uncertainty in decision making.
Analysis of application heartbeats: learning structural and temporal features in time series data for identification of performance problems
Authors: Emma S. Buneci, Daniel A. Reed
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

Grids promote new modes of scientific collaboration and discovery by connecting distributed instruments, data and computing facilities. Because many resources are shared, application performance can vary widely and unexpectedly. We describe a novel performance analysis framework that reasons temporally and qualitatively about performance data from multiple monitoring levels and sources. The framework periodically analyzes application performance states by generating and interpreting signatures containing structural and temporal features from time-series data. Signatures are compared to expected behaviors and in case of mismatches, the framework hints at causes of degraded performance, based on unexpected behavior characteristics previously learned by application exposure to known performance stress factors. Experiments with two scientific applications reveal signatures that have distinct characteristics during well-performing versus poor-performing executions. The ability to automatically and compactly generate signatures capturing fundamental differences between good and poor application performance states is essential to improving the quality of service for Grid applications.
Proposal of a New Conception of an Elastic Neural Network and Its Application to the Solution of a Two-Dimensional Travelling Salesman Problem
Authors: Tomasz Szatkiewicz
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

In this publication, a new conception of a neural network proposed by the author was described. It belongs to the class of self-organizing networks. The theory, structure and learning principles of the network proposed were all described. Further chapters include the application of a system of two proposed neural networks for the solution of a two-dimensional Euclides' travelling salesman problem. The feature of the neural network system proposed is an ability to avoid unfavourable local minima. The article presents graphical results of the evaluation of the neural network system from the initialization point to the determination of the selected TSP instance. 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
Evolvable hardware applied to multi-objective optimization of controllers structure for robot manipulators
Authors: Mario Jungbeck, Marconi Kolm Madrid, Tatiane Jesus De Campos
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

The increasing complexity of the modern control systems has emphasized the idea of applying new approaches in order to solve design problems for different control engineering problems. This paper reports a performance comparison between traditional (linear PID controller) and evolvable methods (evolvable hardware controllers) applied to the problem of three-degrees-of-freedom manipulator control. An evolution procedure is used to tune the PID controllers and design the EHW controllers raised as a multiobjective optimization problem (MOP), applying the multiobjective genetic algorithm NSGA-II (MOGA NSGA-II). In this paper the objective functions are deployed considering the Integral of Square Error (ISE) criteria as performance index to be minimized. This paper shows that the evolutionary approach can discover the concept and learn the behavior of the control system. Numerical simulation results are presented to validate the controllers design and to demonstrate that the proposed evolvable controller has excellent results.
The Early Computers of Konrad Zuse, 1935 to 1945
Authors: Paul E. Ceruzzi
Venue: IEEE Annals of the History of Computing (1981)

This paper examines in detail the early work of Zuse, beginning with his first thoughts on mechanizing calculation in the 1930s and continuing through the completion of his general-purpose relay computer, the Z4, in 1945. The primary objective of this paper is to describe the machines Zuse constructed, but in addition it examines the social, technical, and political milieu in which he carried out his work.
A General Framework for Adaptive Filtering in Wireless Sensor Networks Based on Fuzzy Logic
Authors: Hae Young Lee, Tae Ho Cho
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Wireless sensor networks are vulnerable to false data injection attacks. In these, adversaries inject false reports into the network using compromised nodes, with the goal of deceiving the base station and depleting the energy resources of forwarding nodes. Several filtering schemes, and the adaptive versions of them, have been proposed to detect and drop such false reports during the forwarding process. In this paper, we propose a fuzzy-based framework to achieve adaptive filtering of false reports. A fuzzy rule-based system controls the security level of the filtering scheme through the determination of the required number of endorsements in every report. Compared to existing adaptive solutions, the proposed method uses more practical factors for the determination and can be applied to the network, regardless of scale. The proposed method can provide energy saving and sufficient resilience against false data injection attacks.
Chora: Expert-Based P2P Web Search
Authors: Halldor Isak Gylfason, Omar Khan, Grant Schoenebeck
Venue: Agents and Peer-to-Peer Computing: 5th International Workshop, AP2PC 2006, Hakodate, Japan, May 9, 2006, Revised and Invited Papers (2006)

We present Chora, a P2P web search engine which complements, not replaces, traditional web search by using peers' web viewing history to recommend useful web sites to queriers. Chora is designed around a two-step paradigm. First, Chora determines which peers to query and then it executes a query across these peers. Each peer uses a desktop search engine to query their local web history and retrieve results ordered by relevance. To determine which peers to query, a small sketch of the information available from each peer is stored in a DHT. Peers with sketches indicating that they may have relevant information are queried. The query is dispersed through an ad hoc network connecting only those machines in the query and is optimized for getting good results as quickly as possible.
Grounding Concrete Motion Concepts with a Linguistic Framework
Authors: Gutemberg Guerra-Filho, Yiannis Aloimonos
Venue: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications (2008)

We have empirically discovered that the space of human actions has a linguistic framework. This is a sensorimotor space consisting of the evolution of the joint angles of the human body in movement. The space of human activity has its own phonemes, morphemes, and sentences formed by syntax. This has implications for the grounding of concrete motion concepts. We present a Human Activity Language (HAL) for symbolic non-arbitrary representation of visual and motor information. In phonology, we define basic atomic segments that are used to compose human activity. We introduce the concept of a kinetological system and propose basic properties for such a system: compactness, view-invariance, reproducibility, and reconstructivity. In morphology, we extend sequential language learning to incorporate associative learning with our parallel learning approach. Parallel learning solves the problem of overgeneralization and is effective in identifying the kinetemes and active joints in a particular action. In syntax, we suggest four lexical categories for our Human Activity Language (noun, verb, adjective, adverb). These categories are combined into sentences through specific syntax for human movement.
Experience report: a pure shirt fits
Authors: Ravi Nanavati
Venue: ACM SIGPLAN Notices (2008)

Bluespec is a hardware-design tools startup whose core technology is developed using Haskell. Haskell is an unusual choice for a startup because it adds technical risk to the inherent business risk. In the years since Bluespec's founding, we have discovered that Haskell's purity is an unexpected match for the development needs of a startup. Based on Bluespec's experience, we conclude that pure programming languages can be the source of a competitive advantage for startup software companies.
Evaluation of Java Card Performance
Authors: Samia Bouzefrane, Julien Cordry, Hervé Meunier, Pierre Paradinas
Venue: Proceedings of the 8th IFIP WG 8.8/11.2 international conference on Smart Card Research and Advanced Applications (2008)

With the growing acceptance of the Java Card standard, understanding the performance behaviour of these platforms is becoming crucial. To meet this need, we present in this paper, a benchmark framework that enables performance evaluation at the bytecode and API levels. We also show, how we assign, from the measurements, a global mark to characterise the efficiency of a given Java Card platform, and to determine its performance according to distinct smart card profiles.
The MC68881 Floating-point Coprocessor
Authors: Clayton Huntsman, Duane Cawthron
Venue: IEEE Micro (1983)

This device, a hardware implementation of the proposed IEEE floating-point standard, can operate as a coprocessor on a 32-bit bus or as a peripheral on an 8- or 16-bit bus.
Intuitionistic Fuzzy Spatial Relationships in Mobile GIS Environment
Authors: Mohammad Reza Malek, Farid Karimipour, Saeed Nadi
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

The paper aimed to establish a framework for handling the relationships between different agents in mobile environments. In such environments, objects are vague due to incompleteness and local nature of sensed data. The lack of relevant data stimulated us to use intuitionistic fuzzy (IF) logic for modeling spatial relationships between them. In this paper uncertainty modeling of spatial relationships are analyzed from the view point of intuitionistic fuzzy (IF) logic and in order to provide a paradigm that treats with uncertain topological relationships in mobile GIS environments, a logical framework is presented in which the concept of spatial influenceability is combined with the IF logic.
Static and Dynamic Modelling for the Recognition of Non-verbal Vocalisations in Conversational Speech
Authors: Björn Schuller, Florian Eyben, Gerhard Rigoll
Venue: Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems (2008)

Non-verbal vocalisations such as laughter, breathing, hesitation, and consent play an important role in the recognition and understanding of human conversational speech and spontaneous affect. In this contribution we discuss two different strategies for robust discrimination of such events: dynamic modelling by a broad selection of diverse acoustic Low-Level-Descriptors vs. static modelling by projection of these via statistical functionals onto a 0.6k feature space with subsequent de-correlation. As classifiers we employ Hidden Markov Models, Conditional Random Fields, and Support Vector Machines, respectively. For discussion of extensive parameter optimisation test-runs with respect to features and model topology, 2.9k non-verbals are extracted from the spontaneous Audio-Visual Interest Corpus. 80.7% accuracy can be reported with, and 92.6% without a garbage model for the discrimination of the named classes.
A Pattern-Based Framework for Uncertainty Representation in Ontologies
Authors: Miroslav Vacura, Vojtěch Svátek, Pavel Smrž
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

We present a novel approach to representing uncertain information in ontologies based on design patterns. We provide a brief description of our approach, present its use in connection with fuzzy information and probabilistic information, and describe the possibility to model multiple types of uncertainty in a single ontology. We also shortly present an appropriate fuzzy reasoning tool and define a complex ontology architecture for well-founded handling of uncertain information.
On the Invariant Properties of Hyperbolic Bivariate Third-Order Linear Partial Differential Operators
Authors: Ekaterina Shemyakova, Franz Winkler
Venue: Computer Mathematics: 8th Asian Symposium, ASCM 2007, Singapore, December 15-17, 2007. Revised and Invited Papers (2008)

Bivariate, hyperbolic third-order linear partial differential operators under the gauge transformations L ¿g(x,y)¿ 1 ¿ L ¿ g(x,y) are considered. The existence of a factorization, the existence of a factorization that extends a given factorization of the symbol of the operator are expressed in terms of the invariants of some known generating set of invariants. The operation of taking the formal adjoint can be also defined for equivalent classes of LPDOs, and explicit formulae defining this operation in the space invariants were obtained.
Agent-Based Evolutionary and Immunological Optimization
Authors: Aleksander Byrski, Marek Kisiel-Dorohinicki
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

An immunological selection mechanism for evolutionary multi-agent systems is discussed in the paper. It allows for reducing the number of fitness assignments required to get the solution of comparable quality as the classical resource-based selection in EMAS. Experimental studies aim at comparing the performance of immune-inspired selection, with resource-based one, and also with classical parallel evolutionary algorithms, based on typical multi-modal optimization benchmarks.
Towards a Worldwide Verification Technology
Authors: Wolfgang Paul
Venue: Verified Software: Theories, Tools, Experiments: First IFIP TC 2/WG 2.3 Conference, VSTTE 2005, Zurich, Switzerland, October 10-13, 2005, Revised Selected Papers and Discussions (2005)

Verisoft [1] is a large coordinated project funded by the German Federal Government. The mission of the project is i) to develop the technology which permits the pervasive formal verification of entire computer systems consisting of hardware, system software, communication systems and applications ii) to demonstrate in collaboration with industry this technology with several prototypes. During the fall and winter of 02/03 this project was planned by a task force headed by the author.This task force had to face issues very closely related to what we have discussed in Zurich and we have lived now with the decisions made early in the year 2003 for more than two years. Based on this-mostly positive-experience we make eight scientific, technological and administrative suggestions for the worldwide coordination of efforts in software verification.
On the Deterministic Tracking of Moving Objects with a Binary Sensor Network
Authors: Yann Busnel, Leonardo Querzoni, Roberto Baldoni, Marin Bertier, Anne-Marie Kermarrec
Venue: Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems (2008)

This paper studies the problem of associating deterministically a track revealed by a binary sensor network with the trajectory of a unique moving anonymous object, namely the Multiple Object Tracking and Identification (MOTI) problem. In our model, the network is represented by a sparse connected graph where each vertex represents a binary sensor and there is an edge between two sensors if an object can pass from a sensed region to another without activating any other remaining sensor. The difficulty of MOTI lies in the fact that trajectories of two or more objects can be so close (track merging) that the corresponding tracks on the sensor network can no longer be distinguished, thus confusing the deterministic association between an object trajectory and a track.The paper presents several results. We first show that MOTI cannot be solved on a general graph of ideal binary sensors even by an omniscient external observer if all the objects can freely move on the graph. Then, we describe some restrictions that can be imposed a priori either on the graph, on the object movements or both, to make MOTI problem always solvable. We also discuss the consequences of our results and present some related open problems.
Resource Management of Disruption Tolerant Networks
Authors: Iyad Tumar, Jürgen Schönwälder
Venue: Proceedings of the 2nd international conference on Autonomous Infrastructure, Management and Security: Resilient Networks and Services (2008)

Disruption tolerant networks (DTNs) differ from traditional networks due to their special characteristics such as frequent partitions, intermittent connectivity, and message delivery delay. This paper presents a new idea for the resource management of sparse disruption tolerant networks where the density of nodes is insufficient to support direct end-to-end communications. The idea combines an asynchronous approach, where nodes work on their own wake up schedules without synchronized clocks, with an on-demand scheme, where a low power radio (LPR) is used to search about contacts and a high power radio (HPR) undertakes the actual data transmission.
Subgoal Identification for Reinforcement Learning and Planning in Multiagent Problem Solving
Authors: Chung-Cheng Chiu, Von-Wun Soo
Venue: Proceedings of the 5th German conference on Multiagent System Technologies (2007)

We provide a new probability flow analysis algorithm to automatically identify subgoals in a problem space. Our flow analysis, inspired by preflow-push algorithms, measures the topological structure of the problem space to identify states that connect different subset of state space as the subgoals within linear-time complexity. Then we apply a hybrid approach known as subgoal-based SMDP (semi-Markov Decision Process) that is composed of reinforcement learning and planning based on the identified subgoals to solve the problem in a multiagent environment. The effectiveness of this new method used in a multiagent system is demonstrated and evaluated using a capture-the-flag scenario. We showed also that the cooperative coordination emerged between two agents in the scenario through distributed policy learning.