ppxscal/embedding_network huggingface dataset:
Method on Network Information System Security Assessment Based on Rough Set
Authors: Wang Qiangmin, Lin Mengquan, Li Jianhua
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Based on the analyzing the concept of network information system security assessment, this paper proposed an information system security basic attribute model for information system security assessment based on optimal security tree criteria. Then a novel heuristic rough set attributes reduction algorithm was proposed to reduce the attributes and build weight set. The validity and practical value of it were illustrated by an example. The main idea of the security assessment is improve the assessment efficiency and reduce the cost.
Dynamic classification for video stream using support vector machine
Authors: Mariette Awad, Yuichi Motai
Venue: Applied Soft Computing (2008)

A dynamic classification using the support vector machine (SVM) technique is presented in this paper as a new 'incremental' framework for multiple-classifying video stream data. The contribution of this study is the derivation of a unique, fast and simple to implement technique that allows multi-classification of behavioral motions based on an adaptation of the least-square SVM (LS-SVM) formulation. This dynamic approach leads to an extension of SVM beyond its current static image-based learning capabilities. The proposed incremental multi-classification method is applied to video stream data, which consists of an articulated humanoid model monitored by a surveillance camera. The initial supervised off-line learning phase is followed by a visual behavior data acquisition and then an incremental learning phase. The resulting error rate and the confidence level for the proposed technique demonstrate its validity and merits in articulated motion learning. Furthermore, the enabled online learning allows an adaptive domain knowledge insertion and provides the advantage of reducing both the model training time and the information storage requirements of the overall system which are both essential for dynamic soft computing applications.
Unsupervised slow subspace-learning from stationary processes
Authors: Andreas Maurer
Venue: Theoretical Computer Science (2008)

We propose a method of unsupervised learning from stationary, vector-valued processes. A projection to a low-dimensional subspace is selected on the basis of an objective function which rewards data-variance and penalizes the variance of the velocity vector, thus exploiting the short-time dependencies of the process. We prove bounds on the estimation error of the objective in terms of the @b-mixing coefficients of the process. It is also shown that maximizing the objective minimizes an error bound for simple classification algorithms on a generic class of learning tasks. Experiments with image recognition demonstrate the algorithms ability to learn geometrically invariant feature maps.
Constructing Classification Rules Based on SVR and Its Derivative Characteristics
Authors: Dexian Zhang, Zhixiao Yang, Yanfeng Fan, Ziqiang Wang
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

Support vector regression (SVR) is a new technique for pattern classification , function approximation and so on. In this paper we propose an new constructing approach of classification rules based on support vector regression and its derivative characteristics for the classification task of data mining. a new measure for determining the importance level of the attributes based on the trained SVR is proposed. Based on this new measure, a new approach for clas-sification rule construction using trained SVR is proposed. The performance of the new approach is demonstrated by several computing cases. The experimen-tal results prove that the approach proposed can improve the validity of the ex-tracted classification rules remarkably compared with other constructing rule approaches, especially for the complicated classification problems.
Static resource allocation for heterogeneous computing environments with tasks having dependencies, priorities, deadlines, and multiple versions
Authors: Tracy D. Braun, Howard Jay Siegel, Anthony A. Maciejewski, Ye Hong
Venue: Journal of Parallel and Distributed Computing (2008)

Heterogeneous computing (HC) environments composed of interconnected machines with varied computational capabilities are well suited to meet the computational demands of large, diverse groups of tasks. One aspect of resource allocation in HC environments is matching tasks with machines and scheduling task execution on the assigned machines. We will refer to this matching and scheduling process as mapping. The problem of mapping these tasks onto the machines of a distributed HC environment has been shown, in general, to be NP-complete. Therefore, the development of heuristic techniques to find near-optimal solutions is required. In the HC environment investigated, tasks have deadlines, priorities, multiple versions, and may be composed of communicating subtasks. The best static (off-line) techniques from some previous studies are adapted and applied to this mapping problem: a genetic algorithm (GA), a GENITOR-style algorithm, and a two phase greedy technique based on the concept of Min-min heuristics. Simulation studies compare the performance of these heuristics in several overloaded scenarios, i.e., not all tasks can be executed by their deadlines. The performance measure used is the sum of weighted priorities of tasks that completed before their deadline, adjusted based on the version of the task used. It is shown that for the cases studied here, the GENITOR technique finds the best results, but the faster two phase greedy approach also performs very well.
MISS: Medicine Information Support System in the Smart Home Environment
Authors: José M. Reyes Álamo, Johnny Wong, Ryan Babbitt, Carl Chang
Venue: Proceedings of the 6th international conference on Smart Homes and Health Telematics (2008)

The Smart Home uses different technology to facilitate the lives of the resident and is especially useful for assisting the elderly and persons with special needs. One area where this population would benefit is managing their prescribed medications. This paper presents the Medicine Information Support System (MISS) which integrates the patient's information to assist with the prescriptions management. The system checks for conflicting medicines, health conditions and food items. The data generated is used to feed other subsystems in the Smart Home such as the reminder and medicine inventory. A formal model is introduced for conflicts checking. The three main entities: doctor, pharmacy and Smart Home use this model to detect their particular set of conflicts which ensures that conflicts involving the entire context will eventually be detected. The design uses this model as its basis for conflict checking. The prototyped implementation of the entire system is based on Java.
The Evolution of Web Service-Flow
Authors: Yongzhong Cao, Qiulin Ding, Rigui Zhou
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

Web service-flow having dynamic, distributed andflexible characteristics makes the on-line managementdiffer from the classical workflow. This management ofWeb service-flow should not only run the service-flowaccurately, but should also evolve it dynamically and besure to provide a nice combination every time. At first,this paper extends the definition of WSF with a candidateset of services, and then a composite score functionregarding the capability of the service-flow is presented,according to the budget of combination, time limit and thecredit of service. Some candidates, which adapted well touser requirement and system environment, are selected byusing genetic algorithm, it enables the agent evolve theservice flow dynamically. Experimental result shows thatSELECTER not only gives the superior servicecombination efficiently, but also protects the systemintegrality.
A Comparative Study of Six Formal Models of Causal Ascription
Authors: Salem Benferhat, Jean-François Bonnefon, Philippe Chassy, Rui Silva Neves, Didier Dubois, Florence Dupin De Saint-Cyr, Daniel Kayser, Farid Nouioua, Sara Nouioua-Boutouhami, Henri Prade, Salma Smaoui
Venue: Proceedings of the 2nd international conference on Scalable Uncertainty Management (2008)

Ascribing causality amounts to determining what elements in a sequence of reported facts can be related in a causal way, on the basis of some knowledge about the course of the world. The paper offers a comparison of a large span of formal models (based on structural equations, non-monotonic consequence relations, trajectory preference relations, identification of violated norms, graphical representations, or connectionism), using a running example taken from a corpus of car accident reports. Interestingly enough, the compared approaches focus on different aspects of the problem by either identifying all the potential causes, or selecting a smaller subset by taking advantages of contextually abnormal facts, or by modeling interventions to get rid of simple correlations. The paper concludes by a general discussion based on a battery of criteria (several of them being proper to AI approaches to causality).
Topological Dynamics of 2D Cellular Automata
Authors: Mathieu Sablik, Guillaume Theyssier
Venue: Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms (2008)

Topological dynamics of cellular automata (CA), inherited from classical dynamical systems theory, has been essentially studied in dimension 1. This paper focuses on 2D CA and aims at showing that the situation is different and more complex. The main results are the existence of non sensitive CA without equicontinuous points, the non-recursivity of sensitivity constants and the existence of CA having only non-recursive equicontinuous points. They all show a difference between the 1D and the 2D case. Thanks to these new constructions, we also extend undecidability results concerning topological classification previously obtained in the 1D case.
Toward Dynamic Adoption for a User's Situation Information in a Context-Aware Workflow System
Authors: Yongyun Cho, Kyoungho Shin, Jongsun Choi, Jaeyoung Choi
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Recently, there are many studies to adopt the workflow model, which has been successively applied to traditional computing environments, into ubiquitous computing environments for context-aware and autonomous services. A service in the ubiquitous computing environments must be executed according to a user's situation information, which is generated dynamically from sensors. However, such existing workflow systems as FollowMe and uFlow to support context-aware services through workflow models, can't immediately adopt changes of a user's situation into a already on-going service workflow. In this paper, we propose a context-aware workflow system, for ubiquitous computing environments, which can apply changes of user's service demand or situation information into an on-going workflow without breaking its operation. To do this, the proposed system represents contexts described in a workflow as a RDF-based DItree (Document Instance tree). The system uses the tree information to recognize a exact position to be changed in the on-going workflow for user's situation changes, and to reconstruct only the position under the influence of the changes in the DItree. Therefore, the suggested system can quickly and efficiently apply a change of user's new situation into a on-going workflow without a lot loss of the time and the space, and can offer a context-aware service continuously, according to a new workflow.
Advanced interactive medical visualization on the GPU
Authors: Natalya Tatarchuk, Jeremy Shopf, Christopher DeCoro
Venue: Journal of Parallel and Distributed Computing (2008)

Interactive visual analysis of a patient's anatomy by means of computer-generated 3D imagery is crucial for diagnosis, pre-operative planning, and surgical training. The task of visualization is no longer limited to producing images at interactive rates, but also includes the guided extraction of significant features to assist the user in the data exploration process. An effective visualization module has to perform a problem-specific abstraction of the dataset, leading to a more compact and hence more efficient visual representation. Moreover, many medical applications, such as surgical training simulators and pre-operative planning for plastic and reconstructive surgery, require the visualization of datasets that are dynamically modified or even generated by a physics-based simulation engine. In this paper we present a set of approaches that allow interactive exploration of medical datasets in real time. Our method combines direct volume rendering via ray-casting with a novel approach for isosurface extraction and re-use directly on graphics processing units (GPUs) in a single framework. The isosurface extraction technique takes advantage of the recently introduced Microsoft DirectX^(R)10 pipeline for dynamic surface extraction in real time using geometry shaders. This surface is constructed in polygonal form and can be directly used post-extraction for collision detection, rendering, and optimization. The resulting polygonal surface can also be analyzed for geometric properties, such as feature area, volume and size deviation, which is crucial for semi-automatic tumor analysis as used, for example, in colonoscopy. Additionally, we have developed a technique for real-time volume data analysis by providing an interactive user interface for designing material properties for organs in the scanned volume. Combining isosurface with direct volume rendering allows visualization of the surface properties as well as the context of tissues surrounding the region and gives better context for navigation. Our application can be used with CT and MRI scan data, or with a variety of other medical and scientific applications. The techniques we present are general and intuitive to implement and can be used for many other interactive environments and effects, separately or together.
Improved Likelihood Ratio Test Detector Using a Jointly Gaussian Probability Distribution Function
Authors: O. Pernía, J. M. Górriz, J. Ramírez, C. G. Puntonet, I. Turias
Venue: Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II (2007)

Currently, the accuracy of speech processing systems is stro- ngly affected by the acoustic noise. This is a serious obstacle to meet the demands of modern applications and therefore these systems often needs a noise reduction algorithm working in combination with a precise voice activity detector (VAD). This paper presents a new voice activity detector (VAD) for improving speech detection robustness in noisy environments and the performance of speech recognition systems. The algorithm defines an optimum likelihood ratio test (LRT) involving Multiple and correlated Observations (MO). The so defined decision rule reports significant improvements in speech/non-speech discrimination accuracy over existing VAD methods with optimal performance when just a single observation is processed. The algorithm has an inherent delay in MO scenario that, for several applications including robust speech recognition, does not represent a serious implementation obstacle. An analysis of the methodology for a pair-wise observation dependence shows the improved robustness of the proposed approach by means of a clear reduction of the classification error as the number of observations is increased. The proposed strategy is also compared to different VAD methods including the G.729, AMR and AFE standards, as well as recently reported algorithms showing a sustained advantage in speech/non-speech detection accuracy and speech recognition performance.
Flexible Adaptivity in AEHS Using Policies
Authors: Arne W. Koesling, Daniel Krause, Eelco Herder
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

In this paper, we show how existing adaptive educational hypermedia systems can be enhanced by policies. In traditional systems, the adaptation is based on predefined user and domain models and fairly restricted adaptation rules. Policies allow for sophisticated and flexible adaptation rules, provided by multiple stakeholders. We present the benefits and feasibility of the approach with AHA! as a hands-on example.
Distributed End-to-End QoS Contract Negotiation
Authors: Hélia Pouyllau, Stefan Haar
Venue: Proceedings of the 1st international conference on Autonomous Infrastructure, Management and Security: Inter-Domain Management (2007)

The Internet is based on an X-Domain topology: interconnected domains are managed by independent actors (Fig.1). Deploying critical services (e.g. VPN, video-conference etc.) over such a topology requires to be able to guarantee end-to-end QoS. For this, and to guarantee privacy, Service Level Agreements (SLAs), also called QoS contracts, are committed pairwise between domains. While local QoS control issues inside on each participating domain can be considered solved [4], open problems persist in the field of end-to-end QoS provisioning and monitoring for multi-domain services. The key factors to be taken into account are the heterogeneity, independence and privacy requirements of the individual domains.
QG/GA: A Stochastic Search for Progol
Authors: Stephen Muggleton, Alireza Tamaddoni-Nezhad
Venue: Inductive Logic Programming: 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers (2007)

A search approach is presented, based on a novel algorithm called QG (Quick Generalisation). QG carries out a random-restart stochastic bottom-up search which efficiently generates a consistent clause on the fringe of the refinement graph search without needing to explore the graph in detail. We use a Genetic Algorithm (GA) to evolve and re-combine clauses generated by QG. Initial experiments with QG/GA indicate that this approach can be more efficient than standard refinement-graph searches, while generating similar or better solutions.
Image Reconstruction Using a Modified Sparse Coding Technique
Authors: Li Shang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

A novel image reconstruction method for natural images using a modified sparse coding (SC) algorithm is proposed by us. This SC algorithm exploited the maximum Kurtosis as the maximizing sparse measure criterion, and a fixed variance term of sparse coefficients is used to yield a fixed information capacity. The experimental results show that using our algorithm, the natural images' feature basis vectors can be successfully extracted. Furthermore, compared with the standard SC method, the experimental results show that our algorithm is indeed efficient and effective in performing image reconstruction task.
Weak Proof-Number Search
Authors: Toru Ueda, Tsuyoshi Hashimoto, Junichi Hashimoto, Hiroyuki Iida
Venue: Proceedings of the 6th international conference on Computers and Games (2008)

The paper concerns an AND/OR-tree search algorithm to solve hard problems. Proof-number search is a well-known powerful search algorithm for that purpose. Its depth-first variants such as PN*, PDS, and df-pn work very well, in particular in the domain of shogi mating problems. However, there are still possible drawbacks. The most prevailing one is the double-counting problem. To handle this problem the paper proposes a new search idea using proof number and branching factor as search estimators. We call the new method Weak Proof-Number Search. The experiments performed in the domain of shogi and Othello show that the proposed search algorithm is potentially more powerful than the original proof-number search or its depth-first variants.
A user profile-based personalization system for digital multimedia content
Authors: Diana Weiß, Johannes Scheuerer, Michael Wenleder, Alexander Erk, Mark Gülbahar, Claudia Linnhoff-Popien
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

With the steadily increasing amount of digital multimedia content, the user will be more and more overstrained. This applies to content being permanently available like videos of online video services as well as broadcast content like in the TV or radio domain. A promising solution for this problem is personalization. In the context of this paper, we refer to the selection and recommendation of content with respect to user's interests and preferences as personalization. These recommendations can either be presented to the user herself or be further used by services like a personalized electronic program guide (EPG) in the TV domain or for automated and personalized selection of content of online video services. This paper introduces an approach to personalize digital multimedia content based on user profile information. For this, two main mechanisms were developed: a profile generator that automatically creates user profiles representing the user preferences, and a content-based recommendation algorithm that estimates the user's interest in unknown content by matching her profile to metadata descriptions of the content. Both features are integrated into a personalization system.
Towards a Toolkit for the Analysis and Design of Systems with Self-Management Capabilities
Authors: Ralf Koenig, Heinz-Gerd Hegering
Venue: Proceedings of the 1st international conference on Autonomous Infrastructure, Management and Security: Inter-Domain Management (2007)

Systems with more and more sophisticated self-management capabilities are introduced in many application domains, such as robotics, the military, aerospace, ground vehicles, IT network and systems management. So far, descriptions of such systems are neither decomposed into common modules nor aligned to a common reference model. For this reason, it is hard to compare them regarding common cross-domain properties of systems with self-management capabilities (SwSMC). It is also hard to transfer design knowledge from one application domain to another. A review of related work reveals few publications with guidance to analytical decomposition into functional modules and the identification of patterns specific to the structure and behavior as well as design and use of self-management capabilities.To approach this problem, by using cross-domain evaluation criteria and identification of common patterns we can achieve uniformly structured system descriptions. The approach will be implemented by a common system model of SwSMC, an evaluation sheet for such systems, an evaluation results repository, a pattern catalogue and a set of recommendations how to apply the patterns during the design of such systems and keeping an eye on effectiveness and efficiency. So far, a system model and the evaluation sheet have been created, and some evaluations of research prototypes have been carried out. Despite the low number of evaluations so far, first patterns stand out.