ppxscal/embedding_network huggingface dataset:
Collateral Damage: The Impact of Optimised TCP Variants on Real-Time Traffic Latency in Consumer Broadband Environments
Authors: Lawrence Stewart, Grenville Armitage, Alana Huebner
Venue: Proceedings of the 8th International IFIP-TC 6 Networking Conference (2009)

In recent years a number of TCP variants have emerged to optimise some aspect of data transport where high delay-bandwidth product paths are common. We evaluate a different scenario - latency-sensitive UDP-based traffic sharing a consumer-grade `broadband' link with one or more TCP flows. In particular we compare Linux implementations of NewReno, H-TCP and CUBIC. We find that dynamic latency fluctuations induced by each TCP variant is a more significant differentiator than `goodput' (useful throughput), and that CUBIC induces far more latency than either H-TCP or NewReno when multiple TCP flows are active concurrently. This potential for `collateral damage' should influence future efforts to re-design TCP for widespread deployment.
Intelligent Decision Making with the Semantic Web
Authors: Kevin Curran, Gary Gumbleton
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

There has been a move to acetate web context with explicit meaning so that machines will be able to make better use of it and thus better able to assist web users, leading to a Semantic Web. To date, the possibilities for delivering personalized digital media experiences have been limited however more and more companies are entering the marketplace to offer personal digital media delivery. These companies provide products and services that offer an instant solution for digital media deployments. This paper presents a prototype which demonstrates the power of the semantic web where users can connect to an existing database of media files (e.g. political interviews, new snippets, football manager pre-match interviews etc) and retrieve a selection of media clips. In the case of a football manager giving an interview before a game, it would be possible to also associate his interview with that of another premiership manager. Therefore whenever a user requests an interview clip, the other clip could also be offered to this user.
TIE: A Community-Oriented Traffic Classification Platform
Authors: Alberto Dainotti, Walter Donato, Antonio Pescapé
Venue: Proceedings of the First International Workshop on Traffic Monitoring and Analysis (2009)

The research on network traffic classification has recently become very active. The research community, moved by increasing difficulties in the automated identification of network traffic, started to investigate classification approaches alternative to port-based and payload-based techniques. Despite the large quantity of works published in the past few years on this topic, very few implementations targeting alternative approaches have been made available to the community. Moreover, most approaches proposed in literature suffer of problems related to the ability of evaluating and comparing them. In this paper we present a novel community-oriented software for traffic classification called TIE, which aims at becoming a common tool for the fair evaluation and comparison of different techniques and at fostering the sharing of common implementations and data. Moreover, TIE supports the combination of more classification plugins in order to build multi-classifier systems, and its architecture is designed to allow online traffic classification.
Imbalanced Training Set Reduction and Feature Selection Through Genetic Optimization
Authors: R. Barandela, J. K. Hernández, J. S. Sánchez, F. J. Ferri
Venue: Proceeding of the 2005 conference on Artificial Intelligence Research and Development (2005)

Despite its simplicity and good classification performance, the Nearest Neighbor (NN) rule is not applied in many practical tasks because of the high amount of computational resources that it requires. Besides, when working with imbalanced training samples, its classification accuracy can be seriously degraded. In the present paper we propose two genetic algorithms to cope with these two issues. The purpose is to obtain complexity reduction while at the same time, to get a better balance in the training sample. Experimental results showing the benefits of our proposals are also reported.
On Symbolic Semantics for Name-decorated Contexts
Authors: Andrea Bracciali, Roberto Bruni, Alberto Lluch Lafuente
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

Under several regards, various of the recently proposed computational paradigms are open-ended, i.e. they may comprise components whose behaviour is not or cannot be fully specified. For instance, applications can be distributed across different administration domains that do not fully disclose their internal business processes to each other, or the dynamics of the system may allow reconfigurations and dynamic bindings whose specification is not available at design time. While a large set of mature design and analysis techniques for closed systems have been developed, their lifting to the open case is not always straightforward. Some existing approaches in the process calculi community are based on the need of proving properties for components that may hold in any, or significantly many, execution environments. Dually, frameworks describing the dynamics of systems with unspecified components have also been presented. In this paper we lay some preliminary ideas on how to extend a symbolic semantics model for open systems in order to deal with name-based calculi. Moreover, we also discuss how the use of a simple type system based on name-decoration for unknown components can improve the expressiveness of the framework. The approach is illustrated on a simple, paradigmatic calculus of web crawlers, which can be understood as a term representation of a simple class of graphs.
Mining Local Buffer Data
Authors: Andrzej Siemiński
Venue: Proceeding of the 2008 conference on New Trends in Multimedia and Network Information Systems (2008)

Web mining employs the techniques of data mining to extract information from the Web for a variety of purposes. The usual sources of data are the log files of WWW or proxy servers. The paper examines the possibility of using the local browser buffer for that purpose. The data that could be extracted from both types of logs are compared. It turns out, that despite its limitations the browser buffer is a rich source of unique data about user navigational habits and the properties of the fragment of the WWW that he/she visits. The cache contains the both the full body of a WWW object as well as the header control data sent by the server. Additionally the cache includes some basic information about the usage pattern of each object. Therefore it is possible to study the susceptibility to buffering the objects which is measured by the CF (cacheability factor) and to study the word diversity of Internet texts seen by the user. The CF factor provides an objective measure of the web site caching potential and thus makes it possible to infer about latency of the web site. The word diversity study tests the compliance of the Internet texts with the well known Zipf and Heaps Laws' that are valid for all natural languages. That part study could be used for the optimization indexing engines or the recommendation of pages potentially interesting for the user.
Large-Scale Statistical Machine Translation with Weighted Finite State Transducers
Authors: Graeme Blackwood, Adrià de Gispert, Jamie Brunning, William Byrne
Venue: Proceeding of the 2009 conference on Finite-State Methods and Natural Language Processing: Post-proceedings of the 7th International Workshop FSMNLP 2008 (2009)

The Cambridge University Engineering Department phrase-based statistical machine translation system follows a generative model of translation and is implemented by the composition of component models of translation and movement realised as Weighted Finite State Transducers. Our flexible architecture requires no special purpose decoder and readily handles the large-scale natural language processing demands of state-of-the-art machine translation systems. In this paper we describe the CUED system's participation in the NIST 2008 Arabic-English machine translation evaluation task.
Use of Ensemble Based on GA for Imbalance Problem
Authors: Laura Cleofas, Rosa Maria Valdovinos, Vicente García, Roberto Alejo
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

In real-world applications, it has been observed that class imbalance (significant differences in class prior probabilities) may produce an important deterioration of the classifier performance, in particular with patterns belonging to the less represented classes. One method to tackle this problem consists to resample the original training set, either by over-sampling the minority class and/or under-sampling the majority class. In this paper, we propose two ensemble models (using a modular neural network and the nearest neighbor rule) trained on datasets under-sampled with genetic algorithms. Experiments with real datasets demonstrate the effectiveness of the methodology here proposed.
Scalable architecture for context-aware activity-detecting mobile recommendation systems
Authors: Michael Roberts, Nicolas Ducheneaut, Bo Begole, Kurt Partridge, Bob Price, Victoria Bellotti, Alan Walendowski, Paul Rasmussen
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

One of the main challenges in building multi-user mobile information systems for real-world deployment lies in the development of scalable systems. Recent work on scaling infrastructure for conventional web services using distributed approaches can be applied to the mobile space, but limitations inherent to mobile devices (computational power, battery life) and their communication infrastructure (availability and quality of network connectivity) challenge system designers to carefully design and optimize their software architectures. Additionally, notions of mobility and position in space, unique to mobile systems, provide interesting directions for the segmentation and scalability of mobile information systems. In this paper we describe the implementation of a mobile recommender system for leisure activities, codenamed Magitti, which was built for commercial deployment under stringent scalability requirements. We present concrete solutions addressing these scalability challenges, with the goal of informing the design of future mobile multi-user systems.
WeWrite: 'on-the-fly' interactive writing on electronic textiles with mobile phones
Authors: Thomas Winkler, Martina Ide, Christian Wolters, Michael Herczeg
Venue: Proceedings of the 8th International Conference on Interaction Design and Children (2009)

In this paper, we describe the background of the design and the new possibilities of interaction for teenagers with WeWrite, a JAVA-based interaction tool for mobile phones. WeWrite opens up new possibilities for interacting with self-designed and programmed wearables, using the Lily-Pad, the iconic programming interface Amici, as well as IDE Arduino. WeWrite has been designed and developed by three university students in close cooperation with teachers and thirty-one 10th grade students. WeWrite enables its young users to experience and reflect on e-textiles as creating new modes of communication, interaction and identity construction while writing letter strings. Using LED matrixes, animated forms of digital writing can be displayed on clothes (e.g. jeans and sweatshirts). Furthermore, LEDs can be attached to gloves that create the impression of air letters when moved quickly in darkened rooms.
Measuring self-focus bias in community-maintained knowledge repositories
Authors: Brent Hecht, Darren Gergle
Venue: Proceedings of the fourth international conference on Communities and technologies (2009)

Self-focus is a novel way of understanding a type of bias in community-maintained Web 2.0 graph structures. It goes beyond previous measures of topical coverage bias by encapsulating both node- and edge-hosted biases in a single holistic measure of an entire community-maintained graph. We outline two methods to quantify self-focus, one of which is very computationally inexpensive, and present empirical evidence for the existence of self-focus using a "hyperlingual" approach that examines 15 different language editions of Wikipedia. We suggest applications of our methods and discuss the risks of ignoring self-focus bias in technological applications.
An Innovative Model of Tempo and Its Application in Action Scene Detection for Movie Analysis
Authors: Anan Liu, Jintao Li, Yongdong Zhang, Sheng Tang, Yan Song, Zhaoxuan Yang
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

In this paper, we present an innovative model of tempo and its application in action scene detection for movie analysis. For the first time, we clearly propose that tempo indicates the rhythm of both movie scenarios and human perception. By thoroughly analyzing both aspects, we classify the factors of tempo into two sorts. The first is based on the film grammar and we use the low level features of Shot Length and Camera Motion to describe filmmaking by directors. The second is based on the human perception and we originally propose the information measure for perception depending on the cognitive informatics, a newly emerging and significative subject. With the information in both visual and auditory modalities, the low level features of Motion Intensity, Motion Complexity, Audio Energy and Audio Pace are integrated for the formulation of information to describe the viewers' emotional changes to continuously developing storyline. With both aspects, tempo is defined and tempo flow plot is derived as the clue of storyline. On the basis of video structuralization and movie tempo analysis, we build a system for hierarchical browse and edit with action scene annotation. The large-scale experiments demonstrate the effectiveness and generality of tempo for action movie analysis.
Information Extraction and Semantic Annotation of Wikipedia
Authors: Maria Ruiz-Casado, Enrique Alfonseca, Manabu Okumura, Pablo Castells
Venue: Proceeding of the 2008 conference on Ontology Learning and Population: Bridging the Gap between Text and Knowledge (2008)

An architecture is proposed that, focusing on the Wikipedia as a textual repository, aims at enriching it with semantic information in an automatic way. This approach combines linguistic processing, Word Sense Disambiguation and Relation Extraction techniques for adding the semantic annotations to the existing texts.
Signal processing's importance in manufacturing of a special device
Authors: Mihaiela Iliescu, Brindus Comanescu, Emil Nutu
Venue: WSEAS Transactions on Signal Processing (2009)

Lot of the parts manufactured for various required purposes involve machining processes, such as turning, drilling or, cold pressing processes, such as stamping, drawing, extruding, etc. When these processes are involved, special attention should be given to their specific force values and, as consequence, to devices used in measuring force's values. The most important element of a force measuring device is represented by elastic element and, further, by the transducers "fitted" to it. Appropriate transducers signal processing is essential when device's characteristics have to de specified and, more, to be tested and applied into real manufacturing conditions.
Segmentation of legal documents
Authors: Eneldo Loza Mencía
Venue: Proceedings of the 12th International Conference on Artificial Intelligence and Law (2009)

An overwhelming number of legal documents is available in digital form. However, most of the texts are usually only provided in a semi-structured form, i.e. the documents are structured only implicitly using text formatting and alignment. In this form the documents are perfectly understandable by a human, but not by a machine. This is an obstacle towards advanced intelligent legal information retrieval and knowledge systems. The reason for this lack of structured knowledge is that the conversion of texts in conventional form into a structured, machine-readable form, a process called segmentation, is frequently done manually and is therefore very expensive. We introduce a trainable system based on state-of-the-art Information Extraction techniques for the automatic segmentation of legal documents. Our system makes special use of the implicitly given structure in the source digital file as well as of the explicit knowledge about the target structure. Our evaluation on the French IPR Law demonstrates that the system is able to learn an effective segmenter given only a few manually processed training documents. In some cases, even only one seen example is sufficient in order to correctly process the remaining documents.
A Proposal of Fuzzy Inference Model Composed of Small-Number-of-Input Rule Modules
Authors: Noritaka Shigei, Hiromi Miyajima, Shinya Nagamine
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

The automatic construction of fuzzy system with a large number of input variables involves many difficulties such as large time complexities and getting stuck in a shallow local minimum. In order to overcome them, an SIRMs (Single-Input Rule Modules) model has been proposed. However, such a simple model does not always achieve good performance in complex non-linear systems. This paper proposes a fuzzy reasoning model as a generalized SIRMs model, in which each module deals with a small number of input variables. The reasoning output of the model is determined as the weighted sum of all modules, where each weight is the importance degree of a module. Further, in order to construct a simpler model, we introduce a module deletion function according to the importance degree into the proposed system. With the deletion function, we propose a learning algorithm to construct a fuzzy reasoning system consisting of small-number-of-input rule modules (SNIRMs). The conducted numerical simulation shows that the proposed method is superior in terms of accuracy compared to the conventional SIRMs model.
Managing cooperation in e-business systems
Authors: Pradeep Ray, Lundy Lewis
Venue: Information Systems Frontiers (2009)

E-Business management involves monitoring and controlling all forms of business transactions conducted over the Internet, extranets, and related communications technologies and services. As such, it includes the management of networks, systems, and software applications. E-Business management is beginning to depend increasingly on knowledge of the cooperative aspects of partners in a business chain and the cooperative aspects of stake-holders in e-business operations. The study of cooperation offers many opportunities to apply social network analyses to derive software solutions for the management of e-business. This article provides a methodology and case study that recognises the dimension of cooperation among a multiplicity of organisations, coined "Awareness-based Cooperative Management." It is aimed towards the design or re-engineering of effective e-business management systems, where the key concept involves the degree of awareness held by e-business stake-holders. Awareness is defined in terms of stake-holder interactions and artefacts used in those interactions such as buyer specifications, requests for proposals, offers, service level agreements, and the like. Since awareness is an indispensable, albeit an inherently vague concept, we cast it and reason about it with the apparatus of fuzzy logic.
Domain-Driven Design Quickly
Authors: Abel Avram
Venue:  (2007)

Domain Driven Design is a vision and approach for dealing with highly complex domains that is based on making the domain itself the main focus of the project, and maintaining a software model that reflects a deep understanding of the domain. This book is a short, quickly-readable summary and introduction to the fundamentals of DDD; it does not introduce any new concepts; it attempts to concisely summarize the essence of what DDD is, drawing mostly Eric Evans' original book, as well other sources since published such as Jimmy Nilsson's Applying Domain Driven Design, and various DDD discussion forums. The main topics covered in the book include: Building Domain Knowledge, The Ubiquitous Language, Model Driven Design, Refactoring Toward Deeper Insight, and Preserving Model Integrity. Also included is an interview with Eric Evans on Domain Driven Design today. 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
A First Evaluation of the Instructional Value of Negotiable Problem Solving Goals on the Exploratory Learning Continuum
Authors: Carolyn Rosé, Vincent Aleven, Regan Carey, Allen Robinson
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

We evaluate the effectiveness of a tutorial-dialogue based approach to guided exploratory learning involving problem solving goals that are negotiated between tutor and student rather than dictated by the tutor or freely chosen by the student. This approach, referred to as Negotiable Problem Solving Goals (NPSG), is located on a previously untested space on what we call The Exploratory Learning Continuum. The results of our empirical classroom investigation provide design recommendations for a new type of tutorial dialogue system and strong evidence in favor of tutorial dialogue support in exploratory learning environments.
Agent programming with temporally extended goals
Authors: Koen V. Hindriks, Wiebe van der Hoek, M. Birna van Riemsdijk
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

In planning as well as in other areas, temporal logic has been used to specify so-called temporally extended goals. Temporally extended goals refer to desirable sequences of states instead of a set of desirable final states as the traditional notion of achievement goal does, and provide for more variety in the types of goals allowed. In this paper, we show how temporally extended goals can be integrated into the agent programming language Goal. The result is that Goal agents may now have both beliefs about the future as well as have temporally extended goals. We propose a new decision making mechanism that takes temporally extended goals into account, and investigate properties of this framework.