ppxscal/embedding_network huggingface dataset:
Case-Based Anomaly Detection
Authors: Alessandro Micarelli, Giuseppe Sansonetti
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

Computer and network security is an extremely active and productive research area. Scientists from all over the world address the pertaining issues, using different types of models and methods. In this article we illustrate a case-based approach where the normal user-computer interaction is read like snapshots regarding a reduced number of instances of the same application, attack-free and sufficiently different from each other. The generic case representation is obtained by interpreting in numeric form the arguments and parameters of system calls deemed potentially dangerous. The similarity measure between a new input case and the ones stored in the case library is achieved through the calculation of the Earth Mover's Distance between the corresponding feature distributions, obtained by means of cluster analysis.
An Integrated and Flexible Scheduler for Sensor Grids
Authors: Hock Beng Lim, Danny Lee
Venue: Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing (2007)

The integration of wireless sensor networks and grid computing is an emerging and promising area of research. Sensor grids extend the grid computing paradigm to the sharing of sensor resources in wireless sensor networks. By combining the complementary strengths of sensor networks and grid computing, sensor grids can support applications that require real-time information from the physical environment and vast amount of computational and storage resources.One of the major challenges in the design of sensor grids is how to efficiently schedule sensor jobs across the collection of sensor resources in a sensor grid. In this paper, we design an integrated and flexible scheduler for a sensor grid testbed. The scheduler makes use of several scheduling and load balancing algorithms to suit the characteristics of sensor jobs. We performed extensive evaluations to characterize the behaviour and performance of these scheduling and load balancing algorithms. Our performance results indicate that the sensor grid scheduler can provide a good tradeoff betweeen performance objectives such as sensor resource utilization, sensor job throughput, and sensor grid lifetime.
From Databases to Natural Language: The Unusual Direction
Authors: Yannis Ioannidis
Venue: Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems (2008)

There has been much work in the past that combines the fields of Databases and Natural Language Processing. Almost all efforts, however, have gone in one direction: given unstructured, natural-language elements (requests, text excerpts, etc.), one creates structured, database elements (queries, records, etc.). The other direction has been mostly ignored, although it is very rich in application opportunities as well as in research problems. This short paper outlines several aspects of this other direction, identifying some relevant technical challenges as well as corresponding real applications.
Positive Solutions of General Delayed Competitive or Cooperative Lotka-Volterra Systems
Authors: Wenlian Lu, Tianping Chen
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

In this paper, we investigate dynamical behavior of a general class of competitive or cooperative Lotka-Volterra systems with delays. Positive solutions and global stability of nonnegative equilibrium are discussed. Sufficient condition independent of delays guaranteeing existence of globally stable equilibrium is given. A Simulation verifying theoretical results is given, too.
Search-based many-to-one component substitution
Authors: Nicolas Desnos, Marianne Huchard, Guy Tremblay, Christelle Urtado, Sylvain Vauttier
Venue: Journal of Software Maintenance and Evolution: Research and Practice (2008)

In this paper, we present a search-based automatic many-to-one component substitution mechanism. When a component is removed from an assembly to overcome component obsolescence, failure or unavailability, most existing systems perform component-to-component (one-to-one) substitution. Thus, they only handle situations where a specific candidate component is available. As this is not the most frequent case, it would be more flexible to allow a single component to be replaced by a whole component assembly (many-to-one component substitution). We propose such an automatic substitution mechanism, which does not require the possible changes to be anticipated and which preserves the quality of the assembly. This mechanism requires components to be enhanced with ports, which provide synthetic information on components' assembling capabilities. Such port-enhanced components then constitute input data for a search-based mechanism that looks for possible assemblies using various heuristics to tame complexity. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Fixed-Mobile Hybrid Mashups: Applying the REST Principles to Mobile-Specific Resources
Authors: Sami Mäkeläinen, Timo Alakoski
Venue: Proceedings of the 2008 international workshops on Web Information Systems Engineering (2008)

Mashups have already for years been quite popular and common in the Internet. However, data sources used for creating mashups rarely include anything from the vast potential of the mobile domain and mashups either used from mobile devices or utilizing mobile-specific assets are largely absent. Many enablers, such as smartphones equipped with GPS receivers, already exist for such mashups; operators also possess a large array of useful information on their network server. The lack of mashups in this potentially fruitful area stems partly from the difficulties in accessing such data. This paper describers the application of Representational State Transfer (REST) principles to opening up new and legacy mobile-specific assets in order to enable the creation of compelling "fixed-mobile hybrid" mashups --- mashups that utilize information both from existing "fixed" Internet sources as well as mobile-specific sources exposed via an open, simple API. We also present alternative architectures for the deployment of such a system and provide key lessons learned when implementing a subset of the designed API and proof-of-concept mashups.
Fuzzy Ontology, Fuzzy Description Logics and Fuzzy-OWL
Authors: Silvia Calegari, Davide Ciucci
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

The conceptual formalism supported by an ontology is not sufficient for handling vague information that is commonly found in many application domains. We describe how to introduce fuzziness in an ontology. To this aim we define a framework consisting of a fuzzy ontology based on Fuzzy Description Logic and Fuzzy---Owl.
Unsupervised real time obstacle avoidance technique based on ARTMAP and BK-product of fuzzy relation for autonomous underwater vehicle
Authors: Arif Reza Anwary
Venue: Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation (2008)

The article presents ARTMAP and Fuzzy BK-Product approach underwater obstacle avoidance for the Autonomous underwater Vehicles (AUV). The AUV moves an unstructured area of underwater and obstacles that is might meet in its way and whom AUV might avoid. The AUVs are equipped with complex sensorial systems like camera, aquatic sonar system, and transducers. A Neural integrated Fuzzy BK-Product controller, which integrates Fuzzy logic representation of the human thinking procedure with the learning capabilities of neural-networks (ARTMAP), is developed for obstacle avoidance in the case of unstructured areas. In this paper, ARTMAP-Fuzzy BK-Product controller architecture comprises of two distinct elements, are 1) Fuzzy Logic Membership Function and 2) Feed-Forward ART component. Feed-Forward ART component is used to understanding the unstructured underwater environment and Fuzzy BK-Product interpolates the Fuzzy rule set and after the defuzzyfication, the output is used to take the decision for safety direction to go for avoiding the obstacle collision with the AUV. An on-line reinforcement learning method is introduced which adapts the performance of the fuzzy units continuously to any changes in the environment and make decision for the optimal path from source to destination.
Unlinkable Secret Handshakes and Key-Private Group Key Management Schemes
Authors: Stanisław Jarecki, Xiaomin Liu
Venue: Proceedings of the 5th international conference on Applied Cryptography and Network Security (2007)

We present the first practical unlinkable secret handshake scheme. An unlinkable secret handshake is a two-way authentication protocol in a PKI setting which protects privacy and anonymity of all information about the participants to everyone except of their intended authentication partners. Namely, if entity A certified by organization CA A wants to authenticate itself only to other entities certified by CA A , and, symmetrically, entity B certified by CA B wants to authenticate itself only to entities also certified by CA B , then a secret handshake protocol authenticates these parties and establishes a fresh shared key between them if and only if CA A = CA B and the two parties entered valid certificates for this CA into the protocol. If, however CA A ¿ CA B , or CA A = CA B but either A or B is not certified by this CA, the secret handshake protocol reveals no information to the participants except of the bare fact that their inputs do not match. In other words, an Unlinkable Secret Handshake scheme is a perfectly private authentication method in the PKI setting: One can establish authenticated communication with parties that possess the credentials required by one's policy, and at the same time one's affiliation and identity remain perfectly secret to everyone except of the parties to whom one wants to authenticate.Efficient secret handshake schemes, i.e. authentication protocols which protect the privacy of participants' affiliations, were proposed before, but participants in these schemes remained linkable. Namely, an attacker could recognize all the instances of the protocol executed by the same entity. Secondly, the previous schemes surrendered user's privacy if the certificates of this user were revoked, and our scheme alleviates this problem as well. Unlinkable schemes were proposed as well, but they either relied on single-use certificates, or did not support revocation, or required instantaneous propagation of revocation information.Crucial ingredients in our construction of unlinkable secret handshakes are chosen-ciphertext secure key-private encryption and multi-encryption schemes, and the first efficient construction of a key-private group key management scheme, which is a stateful analogue of (key-private) public key broadcast encryption.
Mobile Retriever: access to digital documents from their physical source
Authors: Xu Liu, David Doermann
Venue: International Journal on Document Analysis and Recognition (2008)

In this paper, we describe an image based document retrieval system which runs on camera enabled mobile devices. &#x201c;Mobile Retriever&#x201d; aims to seamlessly link physical and digital documents by allowing users to snap a picture of the text of a document and retrieve its electronic version from a database. Experiments show that for a database of 100,093 pages, the correct document can be retrieved in less than 4 s at a success rate over 95%. Our system extracts token pairs from the text, to efficiently index and retrieve candidate pages using only a small portion of the image. We use token triplets that define the orientation of three corresponding tokens to effectively prune the false positives and identify the correct page to retrieve. We stress the importance of geometrical relationship between feature points and show its effectiveness in our camera based image retrieval system.
Long-chain molecule analog as key in secure active encoding for access control and encryption
Authors: Carol Dianne Martin
Venue:  (2008)

Whereas the science of cryptography can trace its origins back thousands of years, the increasing reliance of militaries, businesses and individuals on electronically stored and transmitted information has resulted in the need for increasingly robust data protection techniques. Applications involving cryptography are no longer limited to protecting national security interests. Instead, cryptography today is empowering the Internet, telephones, televisions, personal digital assistants, and a variety of other common electronic items. If cryptography is to gain widespread acceptance in the marketplace, it is necessary to develop more transparent methods of securing information, as well as more robust security algorithms. Current key generation and storage mechanisms are responsible for some of the common security weaknesses affecting information systems today. It has been shown that users typically choose passwords (or pass phrases) that are easily remembered, as well as easily recovered, to protect cipher keys. Backup files of cryptographic keys serve as an attractive target for hackers since they are usually unattended. Many people simply overlook the process of creating a backup file for their cryptographic keys and when these keys are damaged or lost, they must generate and distribute new keys which can be costly and provide opportunities for unintended disclosure. This dissertation describes techniques that could be used to solve some of the problems associated with security of cryptographic keys. First, a taxonomic scheme was developed which can be used to describe a biometric cipher key. Secondly, a novel cipher key using biometric features was devised that cannot be lost, stolen, or forgotten using biometric features. Thirdly, a method for the easy expansion of such a key using biometric traits was developed. Finally, a method was demonstrated for secure access control using the novel cipher key without enrolling or storing biometric information. Implementation of the techniques described in this research will both increase the security of data and peripherals without sacrificing the privacy of personal information as well as eliminate the storage and processing requirements associated with conventional cipher keys.
A Novel Hybrid Method of Gene Selection and Its Application on Tumor Classification
Authors: Zhuhong You, Shulin Wang, Jie Gui, Shanwen Zhang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

Microarray gene expression profile data is used to accurately predict different tumor types, which has great value in providing better treatment and toxicity minimization on the patients. However, it is difficult to classify different tumor types using microarray data because the number of samples is much smaller than the number of genes. It has been proved that a small feature gene subset can improve classification accuracy, so feature gene selection and extraction algorithm is very important in tumor classification. In this paper, a novel hybrid gene selection method is proposed to find a feature gene subset so that the feature genes related to certain cancer can be kept and the redundant genes can be leave out. In the proposed method, we combine the advantages of the PCA and the LDA and proposed a novel feature gene extraction scheme. We also compared several kinds of parametric and non-parametric feature gene selection methods. We use the SVM as the classifier in the experiment and compare the performance of three common SVM kernels. Their differences are analyzed. Using the n-fold cross validation, the proposed algorithm is carried out on three published benchmark tumor datasets and experimental results show that this algorithm leads to better classification performance than other methods.
Unbiased Likelihood Backpropagation Learning
Authors: Masashi Sekino, Katsumi Nitta
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

The error backpropagation is one of the popular methods for training an artificial neural network. When the error backpropagation is used for training an artificial neural network, overfitting occurs in the latter half of the training. This paper provides an explanation about why overfitting occurs with the model selection framework. The explanation leads to a new method for training an aritificial neural network, Unibiased Likelihood Backpropagation Learning. Several results are shown.
Evaluating and Comparing Biomedical Term Identification Systems
Authors: Yifei Chen, Feng Liu, Bernard Manderick
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

In this paper, we propose a term identification system using conditional random fields (CRFs) on two biomedical datasets. Through employing several sets of experiments, we make a comprehensive investigation for different types of features. The final experimental results reflect that with carefully designed features i.e., adding not only the individual and dynamic features but also the combinational features, our system can identify biomedical terms with fairly high accuracy on both datasets, compared with other top systems already published in the literature.
Heap Decomposition for Concurrent Shape Analysis
Authors: Roman Manevich, Tal Lev-Ami, Mooly Sagiv, Ganesan Ramalingam, Josh Berdine
Venue: Proceedings of the 15th international symposium on Static Analysis (2008)

We demonstrate shape analyses that can achieve a state space reduction exponential in the number of threads compared to the state-of-the-art analyses, while retaining sufficient precision to verify sophisticated properties such as linearizability. The key idea is to abstract the global heap by decomposing it into (not necessarily disjoint) subheaps, abstracting away some correlations between them. These new shape analyses are instances of an analysis framework based on heap decomposition. This framework allows rapid prototyping of complex static analyses by providing efficient abstract transformers given user-specified decomposition schemes. Initial experiments confirm the value of heap decomposition in scaling concurrent shape analyses.
Synchronization in Arrays of Chaotic Neural Networks
Authors: C. Posadas-Castillo, C. Cruz-Hernández, R. M. López-Gutiérrez
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

In this paper, synchronization in coupled arrays of Cellular Neural Networks (CNN) is presented. In particular, synchronization of chaotic neural networks is obtained from complex systems theory. We consider two complex networks composed by second-order 3×4 CNN array, and a CNN with delay, the information interactions are defined via coupling law through of the first state of each cell. We impose the dynamics of a master cell to multiple slave cells of a complex network. We obtain synchronization in the complex network when the CNN's cells are globally coupled.
Imprecision Measures for Type-2 Fuzzy Sets: Applications to Linguistic Summarization of Databases
Authors: Adam Niewiadomski
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

The paper proposes new definitions of (im)precision measures for type-2 fuzzy sets representing linguistic terms and linguistically quantified statements. The proposed imprecision measures extend similar concepts for traditional (type-1) fuzzy sets, cf. [1,2]. Applications of those new concepts to linguistic summarization of data are proposed in the context of the problem statement of finding the best summaries.
An Initial Evaluation of the NAG f90 Compiler
Authors: Michael Metcalf
Venue: Scientific Programming (1992)

A few weeks before the formal publication of the ISO Fortran 90 Standard, NAG announced the world's first f90 compiler. We have evaluated the compiler by using it to assess the impact of Fortran 90 on the CERN Program Library.
Mixed Feelings About Using Phoneme-Level Models in Emotion Recognition
Authors: Hannes Pirker
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

This study deals with the application of MFCC based models for both the recognition of emotional speech and the recognition of emotions in speech. More specifically it investigates the performance of phone-level models. First, results from performing forced alignment for the phonetic segmentation on GEMEP, a novel multimodal corpus of acted emotional utterances are presented, then the newly acquired segmentations are used for experiments with emotion recognition.
Treewidth Computation and Extremal Combinatorics
Authors: Fedor V. Fomin, Yngve Villanger
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

For a given graph G and integers b,f &ge; 0, let S be a subset of vertices of G of size b + 1 such that the subgraph of G induced by S is connected and S can be separated from other vertices of G by removing f vertices. We prove that every graph on n vertices contains at most $n\binom{b+f}{b}$ such vertex subsets. This result from extremal combinatorics appears to be very useful in the design of several enumeration and exact algorithms. In particular, we use it to provide algorithms that for a given n-vertex graph G compute the treewidth of G in time $\mathcal{O}(1.7549^n)$ by making use of exponential space and in time $\mathcal{O}(2.6151^n)$ and polynomial space; decide in time $\mathcal{O}(({\frac{2n+k+1}{3})^{k+1}\cdot kn^6})$ if the treewidth of G is at most k; list all minimal separators of G in time $\mathcal{O}(1.6181^n)$ and all potential maximal cliques of G in time $\mathcal{O}(1.7549^n)$. This significantly improves previous algorithms for these problems.
Towards an Open Negotiation Architecture for Heterogeneous Agents
Authors: Koen V. Hindriks, Catholijn Jonker, Dmytro Tykhonov
Venue: Proceedings of the 12th international workshop on Cooperative Information Agents XII (2008)

This paper presents the design of an open architecture for heterogeneous negotiating agents. Both the system level architecture as well as the architecture for negotiating agents are provided. The main contribution of this paper is that it derives a precisely specified interface from these architectures that facilitates an easy integration of heterogeneous agents into the overall negotiation framework. The interface is defined as a set of adapters that allows for various levels of integration of agents into the system architecture. The functionality provided by the system architecture depends on the number of adapters that are implemented and used to connect an agent to this architecture, ranging from functionality to conduct a bilateral negotiation to functionality for computing agent internal performance measures such as the quality of an opponent model. The architecture is used as the basis of a competitive testbed which allows us to study various negotiating agents. The design yields a flexible negotiation framework that facilitates negotiating different domains potentially using different protocols whereas no details of the internal negotiating agent structure are enforced. An application of the framework is illustrated by integrating two agents from the literature.