ppxscal/embedding_network huggingface dataset:
A High Connectivity Pre-Distribution Key Management Scheme in Grid-Based Wireless Sensor Networks
Authors: Nguyen Xuan Quy, Vishnu Kumar, Yunjung Park, Eunmi Choi, Dugki Min
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

Key management is a decisive part for security in Wireless Sensor Networks. Pre-distribution of secret keys for all pairs of nodes is not viable due to the large amount of memory used when the number of sensor node is huge. Recently, a random key pre-distribution scheme is proposed as an efficient solution for sharing keys among sensor nodes to reduce the length of shared key and avoid unnecessary key assignments. By studying the range of the communication signal in sensor nodes, we can improve the pre-distribution key mechanism, thus get a higher connectivity possibility between sensor nodes in the whole network. In this paper, we present a grid-based scheme with novel approach for key-distribution mechanism based on the communication range of sensor nodes that guarantees a high probability of sharing keys between sensor nodes. Our evaluation and simulation show that our approach outperforms the existing schemes in both high connectivity probability and low memory usage.
Linear-algebraic λ-calculus: higher-order, encodings, and confluence.
Authors: Pablo Arrighi, Gilles Dowek
Venue: Proceedings of the 19th international conference on Rewriting Techniques and Applications (2008)

We introduce a minimal language combining higher-order computation and linear algebra. This language extends the &lambda;-calculus with the possibility to make arbitrary linear combinations of terms &lambda;.t + &beta;.u. We describe how to "execute" this language in terms of a few rewrite rules, and justify them through the two fundamental requirements that the language be a language of linear operators, and that it be higher-order. We mention the perspectives of this work in the field of quantum computation, whose circuits we show can be easily encoded in the calculus. Finally we prove the confluence of the calculus, this is our main result.
A grounded theory of software process improvement model adoption
Authors: Van Dempsey
Venue:  (2007)

This study, using a grounded theory methodology, analyzed data collected from software developers and IT professionals on software process improvement (SPI) adoption. The study is presented within a backdrop of organizational change steps described by John P. Kotter in his 1996 book, Leading Change. Software quality problems and failures have caused many financial losses, injuries, and even deaths. In the mid 1980s, as a means of mitigating these problems, the Department of Defense (DoD) and Carnegie Mellon University (CMU) began work on the Capability Maturity Model (CMM&reg;) In 2001, the model was superseded by a more robust model, the Capability Maturity Model Integration (CMMI&reg;) These models were designed to provide descriptive, key process improvement areas for organizations to achieve greater maturity in their software and systems development. Organizations could then be appraised at specific maturity levels. According to CMU, SPI improves quality and reliability of software products. The DoD and several organizations now require companies to be appraised at a certain maturity level prior to being awarded a contract. From the onset, there have been difficulties in the adoption of these SPI models. Some of these difficulties can be attributed to organizational change issues. Through grounded theory analysis, a substantive theory was developed, The Theory of Software Process Improvement Model Adoption. This theory contributes to the body of knowledge by providing data and analysis from numerous IT professionals and software developers. This study also provides suggested key organizational change concerns for better SPI adoption practices.
Defining Adaptation in a Generic Multi Layer Model: CAM: The GRAPPLE Conceptual Adaptation Model
Authors: Maurice Hendrix, Paul Bra, Mykola Pechenizkiy, David Smits, Alexandra Cristea
Venue: Proceedings of the 3rd European conference on Technology Enhanced Learning: Times of Convergence: Technologies Across Learning Contexts (2008)

Authoring of Adaptive Hypermedia is a difficult and time consuming task. Reference models like LAOS and AHAM separate adaptation and content in different layers. Systems like AHA!, offer graphical tools based on these models to allow authors to define adaptation without knowing any adaptation language. The adaptation that can be defined using such tools is still limited. Authoring systems like MOT are more flexible, but usability of adaptation specification is low. This paper proposes a more generic model, CAM, which allows the adaptation to be defined in an arbitrary number of layers, where adaptation is expressed in terms of relationships between concepts. This model allows the creation of more powerful yet easier to use graphical authoring tools.
Design of Self-Directed E-Learning Material Recommendation System with On-Line Evaluation
Authors: Feng-Jung Liu
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

Along with explosive growth of the IT and Internet, they have led much development on education, such as e-learning, distance learning and on-line learning etc., which provide learners with another better alternative for learning at anytime and anywhere. Practically, the essence of the Information technology application on education is that Learning is the essential and the technology is the auxiliary. That is, on education, the information technology just acts as a method or a tool in the process of learning. As the IT gets more mature, the e-learning becomes more popular. If the e-learning can effectively exploit the techniques of Data-mining, it will make user-learning more efficient. Thus, in this project, we not only continue the e-learning activity-based material recommendation system construction, but also design the self-evaluation system supporting with semantic search for an adaptive learning platform. In this paper, we mainly propose the ontology-based self-evaluation system with material recommendation system for providing a better learning platform. In the item bank construction, we will invite some domain experts to assist the collection and creation of examination questions and classification. We believe such self-directed learning system will be good for the improvement on the efficiency of the e-learning and will be beneficial to get more achievements on learning for learners.
A Definition Approach for an "Emotional Turing Test"
Authors: Dirk M. Reichardt
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

There are lots of modelling approaches for emotional agents. Can they be compared in any way? The intention of this work is to provide a basis for comparison in a small but consistent environment which focuses on the impact of emotions in the decision making of agents. We chose the public goods game with punishment option as a scenario. Why? In this scenario it has been proven that humans show emotional, non-rational reactions. An emotional agent should therefore be able to show the same emotions and the underlying models should be capable of explaining them! The simulation and test environment is designed to allow any emotional agent model. Eventually, human players should not be distinguishable from artificial emotional agents.
Recognizing Chinese Proper Nouns with Transformation-Based Learning and Ontology
Authors: Peifeng Li, Qiaoming Zhu, Lei Wang
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

This paper proposes an approach based on the Ontology and transformation-based error-driven learning (TBL) to recognize Chinese proper nouns. Firstly, our approach redefines the label set and tags Chinese words according to the usage of proper nouns and their context, and then it extracts Characteristic Information (CI) of the proper noun from the text and merges them based on the Ontology. Secondly, it tags the training corpus following the new definition of Multi-dimension Attribute Points (MAP), and then extracts rules using the TBL approach. Finally, it recognizes proper nouns by utilizing the rule set and Ontology. The experimental results in our open test show that the precision is 92.5% and the recall is 86.3%.
Snap and Spread: A Self-deployment Algorithm for Mobile Sensor Networks
Authors: N. Bartolini, T. Calamoneri, E. G. Fusco, A. Massini, S. Silvestri
Venue: Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems (2008)

The use of mobile sensors is motivated by the necessity to monitor critical areas where sensor deployment cannot be performed manually. In these working scenarios, sensors must adapt their initial position to reach a final deployment which meets some given performance objectives such as coverage extension and uniformity, total moving distance, number of message exchanges and convergence rate.We propose an original algorithm for autonomous deployment of mobile sensors called Snap Spread. Decisions regarding the behavior of each sensor are based on locally available information and do not require any prior knowledge of the operating conditions nor any manual tuning of key parameters. We conduct extensive simulations to evaluate the performance of our algorithm. This experimental study shows that, unlike previous solutions, our algorithm reaches a final stable deployment, uniformly covering even irregular target areas. Simulations also give insights on the choice of some algorithm variants that may be used under some different operative settings.
On Combining Dissimilarity-Based Classifiers to Solve the Small Sample Size Problem for Appearance-Based Face Recognition
Authors: Sang-Woon Kim, Robert P. Duin
Venue: Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence (2007)

For high-dimensional classification tasks, such as face recognition, the number of samples is smaller than the dimensionality of the samples. In such cases, a problem encountered in Linear Discriminant Analysis-based (LDA) methods for dimension reduction is what is known as the Small Sample Size (SSS) problem. A number of LDA-extension approaches that attempt to solve the SSS problem have been proposed in the literature. Recently, a different way of employing a dissimilarity representation method was proposed [18], where an object was represented based on the dissimilarity measures among representatives extracted from training samples instead of the feature vector itself. Apart from utilizing the dissimilarity representation, in this paper, a new way of employing a fusion technique in representing features as well as in designing classifiers is proposed in order to increase the classification accuracy. The proposed scheme is completely different from the conventional ones in terms of the computation of the transformation matrix as well as the selection of the number of dimensions. The present experimental results demonstrate that the proposed combining mechanism works well and achieves further improved efficiency compared with the LDA-extension approaches for well-known face databases involving AT T and Yale databases. The results especially demonstrate that the highest accuracy rates are achieved when the combined representation is classified with the trained combiners.
A Tunable Constrained Test Problems Generator for Multi-objective Optimization
Authors: Peng Cheng
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

Multi-objective optimization problems (MOPs) in real world are often constrained optimization problems. So test problems to evaluate multi-objective optimization evolutionary algorithms (MOEAs) should have some constraints in order to simulate real-world problems. In this paper, a well understood and tunable constrained test problems generator is suggested. By setting parameters in the constraint function, test problems with various complexity and Pareto-optimal front geometries can be created. Six constrained MOPs are developed and explained in figures so as to account for parameters in the constraint function. Furthermore, NSGA-Ⅱ with an constrained handling strategy are used to solve the test problems. Experiments results show test problem can greatly increase difficulties in searching Pareto-optimal solutions, and they are effective tools to evaluate MOEAs in constraints handling.
Peer-to-Peer Overlay Multicast for Scalable Audiovisual Services over Converging Wired and Wireless Networks
Authors: Ahmed Mehaoua, Li Fang, George Kormentzas, Dominique Seret
Venue: Proceedings of the 11th IFIP/IEEE international conference on Management of Multimedia and Mobile Networks and Services: Management of Converged Multimedia Networks and Services (2008)

The deployment of scalable audiovisual multicast services over heterogeneous core and access networks is a challenging problem. In this article we propose E-Cast, an efficient, source-specific, scalable, overlay multicast system based on the peer-to-peer system Kademlia. This novel overlay multicast system enables IPTV multicast to be deployed as a service level infrastructure to overcome IP network multicast discontinuity in converging wired and wireless network domains. E-cast consists of a set of edge devices called E-Cast Service Node (ESN) and one managing device called E-Cast Service Manager (ESM). ESNs are distributed in the network and provide efficient video distribution services. They not only transport the media-streaming but also can cache the media files according to some given criteria. Performance evaluation using simulation and features comparison with existing proposals are also proposed.
Enterprise Flash Storage
Venue: Queue (2008)

Flash is growing from mere curiosity to a new tier in the storage hierarchy.
Corner singularities for elliptic problems: Integral equations, graded meshes, quadrature, and compressed inverse preconditioning
Authors: Johan Helsing, Rikard Ojala
Venue: Journal of Computational Physics (2008)

We take a fairly comprehensive approach to the problem of solving elliptic partial differential equations numerically using integral equation methods on domains where the boundary has a large number of corners and branching points. Use of non-standard integral equations, graded meshes, interpolatory quadrature, and compressed inverse preconditioning are techniques that are explored, developed, mixed, and tested on some familiar problems in materials science. The recursive compressed inverse preconditioning, the major novelty of the paper, turns out to be particularly powerful and, when it applies, eliminates the need for mesh grading completely. In an electrostatic example for a multiphase granular material with about two thousand corners and triple junctions and a conductivity ratio between phases up to a million we compute a common functional of the solution with an estimated relative error of 10^-^1^2. In another example, five times as large but with a conductivity ratio of only a hundred, we achieve an estimated relative error of 10^-^1^4.
Energy Partitioning Analysis of the Chemical Bonds in mer-Mq3 (M = AlIII, GaIII, InIII, TlIII)
Authors: Ruihai Cui, Jingping Zhang
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Geometries of ground states of mer-tris(8-hydroxyquinoli- nato)metal (Mq3, M=Al3 + , Ga3 + , In3 + , Tl3 + ) are optimized by B3LYP/6-31G(d) methods. The bonding interactions between the metal fragment Mq2 and each single ligand q have been analyzed with the energy decomposition scheme. The calculated results suggest that the HOMO and LUMO distribution fashion can be simply traced back to the lowest electrostatic attractive and highest orbital interaction energy between fragments A-quinolate ligand and Mq2 and B-ligand and Mq2, respectively.
Developing a model of online learning-technology acceptance model (TAM)
Authors: Rong-Jyue Fang, Chung-Ping Lee, Shi-Jer Lou, Hua-Lin Tsai, Hung-Jen Yang
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

With the rapid development of information technology and network infrastructure construction, the online learning system has been changed from traditional face-to-face classroom to speedy information technology. On the past decades, few of researchers have constructed specifically for the principals' attitudes toward online learning. The purpose of this study was to develop a Technology Acceptance Model (TAM) for the principals in elementary schools and junior high schools. The TAM on this study was framed by six subscales: perceived ease of use, perceived useful planning, perceived useful learning, perceived useful contents, attitudes toward using online learning, and behavioral intentions to manage via online learning. This study would also explore the relationship between online learning and the principals' leadership. At the same time, the study introduced perceived useful planning, perceived useful learning, and perceived useful contents as new factors that reflected the principals' intrinsic belief in online learning acceptance.
Mining the Web Through Verbs: A Case Study
Authors: Peyman Sazedj, H. Sofia Pinto
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

ining non-taxonomic relations is an important part of the Semantic Web puzzle. Building on the work of the semantic annotation community, we address the problem of extracting relation instances among annotated entities. In particular, we analyze the problem of verb-based relation instantiation in some detail and present a heuristic domain independent approach, based on verb chunking and entity clustering, which doesn't require parsing. We also address the problem of mapping linguistic tuples to relations from the ontology. A case study conducted within the biography domain demonstrates the validity of our results in contrast to related work, whilst examining the complexity of the extraction task and the feasibility of verb-based extraction in general.
Inter-deriving Semantic Artifacts for Object-Oriented Programming
Authors: Olivier Danvy, Jacob Johannsen
Venue: Proceedings of the 15th international workshop on Logic, Language, Information and Computation (2008)

We present a new abstract machine for Abadi and Cardelli's untyped calculus of objects. What is special about this semantic artifact (i.e., man-made construct) is that is mechanically corresponds to both the reduction semantics (i.e., small-step operational semantics) and the natural semantics (i.e., big-step operational semantics) specified in Abadi and Cardelli's monograph. This abstract machine therefore embodies the soundness of Abadi and Cardelli's reduction semantics and natural semantics relative to each other.To move closer to actual implementations, which use environments rather than actual substitutions, we then represent object methods as closures and in the same inter-derivational spirit, we present three new semantic artifacts: a reduction semantics for a version of Abadi and Cardelli's untyped calculus of objects with explicit substitutions, an environment-based abstract machine, and a natural semantics (i.e., an interpreter) with environments. These three new semantic artifacts mechanically correspond to each other, and furthermore, they are coherent with the previous ones since as we show, the two abstract machines are bisimilar. Overall, though, the significance of these artifacts lies in them not having been designed from scratch and then proved correct: instead, they were mechanically inter-derived.
Overview of the ImageCLEF 2007 Object Retrieval Task
Authors: Thomas Deselaers, Allan Hanbury, Ville Viitaniemi, András Benczúr, Mátyás Brendel, Bálint Daróczy, Hugo Jair Escalante Balderas, Theo Gevers, Carlos Arturo Hernández Gracidas, Steven C. Hoi, Jorma Laaksonen, Mingjing Li, Heidy Marisol Marín Castro, Hermann Ney, Xiaoguang Rui, Nicu Sebe, Julian Stöttinger, Lei Wu
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

We describe the object retrieval task of ImageCLEF 2007, give an overview of the methods of the participating groups, and present and discuss the results.The task was based on the widely used PASCAL object recognition data to train object recognition methods and on the IAPR TC-12 benchmark dataset from which images of objects of the ten different classes bicycles, buses, cars, motorbikes, cats, cows, dogs, horses, sheep, and persons had to be retrieved.Seven international groups participated using a wide variety of methods. The results of the evaluation show that the task was very challenging and that different methods for relevance assessment can have a strong influence on the results of an evaluation.
Representing Functional Data Using Support Vector Machines
Authors: Javier González, Alberto Muñoz
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

Functional data are difficult to manage for many traditional pattern recognition techniques, given the very high (or intrinsically infinite) dimensionality. The reason is that functional data are functions and most algorithms are designed to work with (small) finite-dimensional vectors. In this paper we propose a functional analysis technique to obtain finite-dimensional representations of functional data. The key idea is to consider each functional curve as a point in a general function space and then project these points onto a Reproducing Kernel Hilbert Space with the aid of a Support Vector Machine. We show some theoretical properties of the method and illustrate the performance of the proposed representation in clustering using a real data set.
Interference aware channel allocation in a multichannel, multi-interface wireless network
Authors: Vijay Raman, Nitin H. Vaidya
Venue: Proceedings of the third ACM international workshop on Wireless network testbeds, experimental evaluation and characterization (2008)

In this article, we present an interference-aware channel allocation algorithm for a multichannel, multi-interface wireless network. The channel allocation algorithm minimizes the effect of adjacent and co-channel channel interference both within a node (due to multiple interfaces) and across nodes. Furthermore, our allocation makes use of all the available channels for improving spatial reuse in the network. We demonstrate our algorithm using a multichannel testbed, and bring out the performance benefit of our algorithm compared to another algorithm that utilizes only orthogonal channels.
Understanding Network Mobility in Pervasive Markets: Realistic Human Shopping Behavioral Model
Authors: Lu Yan
Venue: Proceedings of the 1st world summit on The Knowledge Society: Emerging Technologies and Information Systems for the Knowledge Society (2008)

With recent advances of wireless ad hoc networking, especially opportunistic forwarding and cognitive radio, there is an increasing concern that existing mobility models are insufficient to represent network mobility in real world settings. In this paper, we discuss our proposal for a more realistic mobility model which captures key features of human movements in pervasive markets. Our findings lead to a non-traditional mobility model which can be used to reconstruct the statistical patterns of realistic human shopping behaviors. We believe this model is ground-breaking, since no similar model exists in the literature, to the best of our knowledge.