ppxscal/embedding_network huggingface dataset:
Brain MR Image Segmentation Using Local and Global Intensity Fitting Active Contours/Surfaces
Authors: Li Wang, Chunming Li, Quansen Sun, Deshen Xia, Chiu-Yen Kao
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

In this paper, we present an improved region-based active contour/surface model for 2D/3D brain MR image segmentation. Our model combines the advantages of both local and global intensity information, which enable the model to cope with intensity inhomogeneity. We define an energy functional with a local intensity fitting term and an auxiliary global intensity fitting term. In the associated curve evolution, the motion of the contour is driven by a local intensity fitting force and a global intensity fitting force, induced by the local and global terms in the proposed energy functional, respectively. The influence of these two forces on the curve evolution is complementary. When the contour is close to object boundaries, the local intensity fitting force became dominant, which attracts the contour toward object boundaries and finally stops the contour there. The global intensity fitting force is dominant when the contour is far away from object boundaries, and it allows more flexible initialization of contours by using global image information. The proposed model has been applied to both 2D and 3D brain MR image segmentation with promising results.
Constructing Models with the Human-Usable Textual Notation
Authors: Louis M. Rose, Richard F. Paige, Dimitrios S. Kolovos, Fiona A. Polack
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

We present an implementation of the OMG's Human-Usable Textual Notation (HUTN) [6] that provides a generic concrete syntax for MOF-based metamodels. The notation is summarised. Ways in which HUTN can be applied in order to improve the productivity of Model-Driven Engineering are identified. The use of HUTN to improve the quality of test suites for verifying model management operations (such as model-to-model transformation) is described. We also present a comparison of generic and domain-specific concrete syntax with HUTN.
Sputtering of Ni/Ti/SiC ohmic contacts
Authors: Petr Machac, Bohumil Barda, Marie Hubickova
Venue: Microelectronic Engineering (2008)

The presented work describes the behaviour of contact structures of Ni/Ti type on 6H-SiC n-type prepared by the sputtering technology. Simultaneous deposition of Ni and Ti is better. Plasma cleaning improves adhesion of metals; however, contact resistivity is worse. The Ni(50)/Ti(th)-type metallization has the best electrical parameters at the titanium layer thickness of 100nm. The XPS analysis shows that the annealing reactions consume about 75nm or 120nm of SiC in the case of the Ni+Ti or the Ni/Ti metallization, respectively.
SafeSpection --- A Systematic Customization Approach for Software Hazard Identification
Authors: Christian Denger, Mario Trapp, Peter Liggesmeyer
Venue: Proceedings of the 27th international conference on Computer Safety, Reliability, and Security (2008)

Software is an integral part of many technical systems and responsible for the realization of safety-critical features contained therein. Consequently, software has to be carefully considered in safety analysis efforts to ensure that it does not cause any system hazards. Safety engineering approaches borrowed from systems engineering, like Failure Mode and Effect Analysis, Fault Tree Analysis, or Hazard and Operability Studies, have been applied on software-intensive systems. However, in order to be successful, tailoring is needed to the characteristics of software and the concrete application context. Furthermore, due to the manual and expert-dependent nature of these techniques, the results are often not repeatable and address mainly syntactic issues. This paper presents the concepts of a customization framework to support the definition and implementation of project-specific software hazard identification approaches. The key-concepts of the approach, generic guide-phrases, and tailoring concepts to create objective, project-specific support to detect safety-weaknesses of software-intensive systems are introduced.
A best-first anytime algorithm for computing optimal coalition structures
Authors: Chattrakul Sombattheera, Aditya Ghose
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

This work presents a best-first anytime algorithm for computing optimal coalition structures. The approach is novel in that it generates coalition structures based on coalition values, while existing algorithms base their generation on the structure (members and configurations) of coalitions. With our algorithm, coalition structures are generated by repeatedly choosing the best coalition, as determined using a novel metric called agent's contribution to coalition structure that we define. We have compared the performance of our algorithm against that of Rahwan et al [5] using 20 data distributions. Our results show that our algorithm almost always converges on an optimal coalition structure faster (although it terminates later in some cases). Empirically, our algorithm almost always yields better than or as good as Rahwan et al's results at any point in time.
The Practical Application of Fuzzy Information Analysis in Flood Forecasting
Authors: Lihua Feng, Weihu Hong
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

The relationship between the peak stage and peak discharge is influenced by many factors in the flood system. Therefore, different peak discharges may occur under the same peak stage, while the same peak discharge may also occur under the different peak stages. If the peak stage set with similar peak discharges is taken as the fuzzy subset in the stage universe, then the membership function of these fuzzy subsets can be hypothesized to manifest a normal distribution graph. According to a k and b k , the mid-value of the universe element of the peak stage can be substituted into the normal distribution graph, and the fuzzy relational matrix can be obtained. Thus, the peak discharge can be calculated according to the peak stage using the fuzzy deduction theory. The relationship between the peak stage and peak discharge as Q = f(H) has an important impact on the determination of the peak discharge during the high-water level period in the flood forecast. In this paper, the fuzzy information analysis method is used to forecast the peak discharge, with the result in accordance with the actual event. This method can be seen as a new and effective method of flood prediction and forecasting.
Exploring Anti-Spam Models in Large Scale VoIP Systems
Authors: Pushkar Patankar, Gunwoo Nam, George Kesidis, Chita R. Das
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Although the problem of spam detection in email is well understood and has been extensively researched, a significant portion of emails today are spam. A most widely used method to detect spam involves content filtering, where the spam detector scans the received email for keywords. However, the same approach cannot be applied to detect Voice over IP (VoIP) spam, since a call has to be categorized as a legitimate or a spam (each to a degree with a certain reliability) before the connection is established. Also, spammers over IP can potentially generate orders of magnitude more spam volume, at far less cost, and with greater anonymity than telemarketers using the Public Switch Telephone Network (PSTN). The spam problem in VoIP is further compounded by the absence of a do-not-call-list, which has been the main reason for the reduction of spam calls in PSTN. Thus, the spam issue for VoIP is as important as those pertaining to quality-of-service (QoS) of the voice traffic itself. To this end, we propose two different anti-spam frameworks for large scale VoIP systems. The first one is a centralized SIP-based spam detection framework that relies on SIP messages during the call establishment phase to identify spam calls, and the second one is a distributed referral social network model, where a user is assigned a reputation score by its neighbors. Based on the reputation, a callee can decide either to accept or decline a call. Our simulation results indicate that the referral model can provide better anti-spam capabilities by isolating a spammer faster than the SIP based approach, and can also correctly identify spam calls over 98% of time.
Managing Context Information in Mobile Devices
Authors: Panu Korpipaa, Jani Mantyjarvi, Juha Kela, Heikki Keranen, Esko-Juhani Malm
Venue: IEEE Pervasive Computing (2003)

To make mobile devices truly context-aware, we must develop systematic techniques for applications to use the uncertain information gained from multiple sources. Instead of using raw measurement data, applications can use higher-level context abstractions. This article introduces a framework and an application programming interface for managing context information, especially sensor-based. The framework simplifies the development of context-aware mobile applications and facilitates information reuse and sharing.
Web 2.0 as syndication
Authors: Roger Clarke
Venue: Journal of Theoretical and Applied Electronic Commerce Research (2008)

There is considerable excitement about the notion of 'Web 2.0', particularly among Internet businesspeople. In contrast, there is an almost complete lack of formal literature on the topic. It is important that movements with such energy and potential be subjected to critical attention, and that industry and social commentators have the opportunity to draw on the eCommerce research literature in formulating their views. This paper assesses the available information about Web 2.0, with a view to stimulating further work that applies existing theories, proposes new ones, observes and measures phenomena, and tests the theories. The primary interpretation of the concept derives from marketers, but the complementary technical and communitarian perspectives are also considered. A common theme derived from the analysis is that of 'syndication' of content, advertising, storage, effort and identity.
Evolving Multi-creature Systems for All-to-All Communication
Authors: Rolf Hoffmann, Patrick Ediger
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

Several creatures are moving around in a cellular automata grid. At a certain point of time all creatures want to exchange their information with all others (all-to-all communication). The goal is to find an optimal rule for the movement of the creatures in order to exchange their information as fast as possible. The information exchange is only possible when the creatures meet each other and when they form certain defined local patterns (communication situations). Possible communication situations are exemplarily shown in Fig. 1. In the cases a, b, c the creatures are directly in contact. But it is a matter of definition whether such situations allow communication. For this investigation we have defined the communication patterns d, e, f. A reason could be that communication can only take place if a mediator/negotiator is used between them. Furthermore the mediator may perform a particular computation (e. g., average, maximum, priority select). Such conflicts occur when creatures want to move to the same target position, like vehicles which are meeting in a cross-way. The center of the crossing can be interpreted as the mediator.
A lightweight approach to datatype-generic rewriting
Authors: Thomas van Noort, Alexey Rodriguez, Stefan Holdermans, Johan Jeuring, Bastiaan Heeren
Venue: Proceedings of the ACM SIGPLAN workshop on Generic programming (2008)

Previous implementations of generic rewriting libraries have a number of limitations: they require the user to either adapt the datatype on which rewriting is applied, or the rewriting rules are specified as functions, which makes it hard or impossible to document, test, and analyse them. We describe a library that demonstrates how to overcome these limitations by defining rules in terms of datatypes, and show how to use a type-indexed datatype to automatically extend a datatype for syntax trees with a case for metavariables. We then show how rewrite rules can be implemented without any knowledge of how the datatype is extended with metavariables. We use Haskell, extended with associated type synonyms, to implement both type-indexed datatypes and generic functions. We analyse the performance of our library and compare it with other approaches to generic rewriting.
Feature-based texture synthesis and hierarchical tensor approximation
Authors: Yizhou Yu
Venue:  (2007)

Texture synthesis has always been an interesting research topic in Graphics. Neighborhood-based algorithms have two common stages: search for most similar neighborhoods in the sample texture; merge a local neighborhood into the (partially) synthesized output texture. When the first stage can not find good neighbors, the second stage may generate seams. We propose to extract a feature map from the input texture and synthesize a feature map for output. We develop novel algorithms to perform feature matching and alignment. This approach significantly reduces feature discontinuities and related artifacts. For 3D surfaces, things get more complicated as continuity constraints restrict the variability of synthesized textures. We propose to relax the restrictions and decompose synthesis into two stages: feature map synthesis and Laplacian texture reconstruction. Experiments indicate that this relaxation can produce desirable results for regular texture synthesis as well as texture mixing from multiple sources. Visual data approximation is another important issue in Graphics. We propose hierarchical tensor approximation to expose multi-scale and inhomogeneous structures in visual datasets. The blocks on each level in the hierarchy are pruned and approximated as a tensor ensemble, and residual tensors are subdivided to form the next level in the hierarchy. Experiments prove that the hierarchical multilinear models can achieve higher compression ratios and quality on high-dimensional visual data than wavelet (packet) transforms and single-level tensor approximation. Finally, we propose to apply multilinear models to wavelet domain to reduce overhead. High-frequency wavelet sub-bands are subdivided into small blocks most of which get pruned. The blocks are usually correlated especially when properly classified. Different channels and sub-bands may exhibit strong redundancy as well. We reorganize the subdivided blocks into small tensors, classify the unpruned ones and approximate each cluster as a tensor ensemble. Experiments on images and medical volume data indicate that this approach achieves better approximation quality than wavelet (packet) transforms and hybrid linear models.
Improved Weighted Centroid Localization in Smart Ubiquitous Environments
Authors: Stephan Schuhmann, Klaus Herrmann, Kurt Rothermel, Jan Blumenthal, Dirk Timmermann
Venue: Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing (2008)

Location-awareness is highly relevant subject in ubiquitous computing, as many applications exploit location information to provide adequate services or adapt to a changing physical environment. While GPS provides reliable outdoor localization, indoor positioning systems present a bigger challenge. Many indoor localization systems have been proposed. However, most of them rely on customized hardware or presume some dedicated infrastructure. In this paper, we focus on WLAN-based localization in smart ubiquitous environments. We propose an improved scheme of the Weighted Centroid Localization (WCL) algorithm that is robust and provides higher location accuracy than the original WCL algorithm. The improvements are based on the use of dynamic weighting factors that are solely dependent on the correlation of the Received Signal Strength Indicators of the received beacon signals. Compared to the original WCL scheme, our approach does not increase requirements to the environment. Real-world experiments in a typical environment that we report on in this paper confirm that the increased location accuracy determined in previous calculations is reproducible in a realistic noisy environment. This provides a simple, cost-efficient, and battery-conserving, but yet adequate technique for getting the accurate location information of mobile devices.
Variable Selection for Multivariate Time Series Prediction with Neural Networks
Authors: Min Han, Ru Wei
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

This paper proposes a variable selection algorithm based on neural networks for multivariate time series prediction. Sensitivity analysis of the neural network error function with respect to the input is developed to quantify the saliency of each input variables. Then the input nodes with low sensitivity are pruned along with their connections, which represents to delete the corresponding redundant variables. The proposed algorithm is tested on both computer-generated time series and practical observations. Experiment results show that the algorithm proposed outperformed other variable selection method by achieving a more significant reduction in the training data size and higher prediction accuracy.
Hybrid machine learning to improve predictive performance
Authors: Sung Ho Ha, Jong Sik Jin, Seong Hyeon Joo
Venue: Proceedings of the WSEAS International Conference on Applied Computing Conference (2008)

Yield management in semiconductor manufacturing companies requires accurate yield prediction and continual control. This paper presents a hybrid method of combining machine learning techniques to detect high and low yields. In the real applications, the hybrid method provides more accurate yield prediction than other methods.
NAPX: A Polynomial Time Approximation Scheme for the Noah's Ark Problem
Authors: Glenn Hickey, Paz Carmi, Anil Maheshwari, Norbert Zeh
Venue: Proceedings of the 8th international workshop on Algorithms in Bioinformatics (2008)

The Noah's Ark Problem (NAP) is an NP-Hard optimization problem with relevance to ecological conservation management. It asks to maximize the phylogenetic diversity (PD) of a set of taxa given a fixed budget, where each taxon is associated with a cost of conservation and a probability of extinction. NAP has received renewed interest with the rise in availability of genetic sequence data, allowing PD to be used as a practical measure of biodiversity. However, only simplified instances of the problem, where one or more parameters are fixed as constants, have as of yet been addressed in the literature. We present NAPX, the first algorithm for the general version of NAP that returns a 1 ¿ ¿ approximation of the optimal solution. It runs in $O\left(\frac{n B^2 h^2 \log^2n}{\log^2(1 - \epsilon)}\right)$ time where n is the number of species, and B is the total budget and h is the height of the input tree. We also provide improved bounds for its expected running time.
Context Enabled Semantic Granularity
Authors: Riccardo Albertoni, Elena Camossi, Monica Martino, Franca Giannini, Marina Monti
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

In this paper we propose a powerful ontology driven method that eases the browsing of any repository of information resources described by an ontology: we provide a flexible semantic granularity method for the navigation of a repository according to different levels of abstraction, i.e. granularities. The granularity is explicitly parameterised according to the criteria induced by the context.
Linkability Analysis of Some Blind Signature Schemes
Authors: Jianhong Zhang, Jian Mao
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

Blind signature is a cryptographical technique and allows a user to obtain signatures from an authority on any document, in such a way that the authority learns nothing about the message that is being signed. The blindness is an important property which distinguishes the blind signature from other signature schemes. In this work, we analyze security of two ID-based blind signature schemes [1,16] and a blind signature scheme[20] based on witness indistinguishable signature, and show that the three schemes don't satisfy blindness, in other words, the signer is able to link a valid message-signature pair obtained by some user. It means that the three blind signature schemes are insecure.
A Space-Efficient Probabilistic Simulation Algorithm
Authors: Lijun Zhang
Venue: Proceedings of the 19th international conference on Concurrency Theory (2008)

In the context of probabilistic automata, time efficient algorithms for probabilistic simulations have been proposed lately. The space complexity thereof is quadratic in the size of the transition relation, thus space requirements often become the practical bottleneck. In this paper, we exploit ideas from [3] to arrive at a space-efficient algorithm for computing probabilistic simulations based on partition refinement. Experimental evidence is given that not only the space-efficiency is improved drastically. The experiments often require orders of magnitude less time.
Utility-Based Opportunistic Routing in Multi-Hop Wireless Networks
Authors: Jie Wu, Mingming Lu, Feng Li
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Recently, opportunistic routing (OR) has been widely used to compensate for the low packet delivery ratio of multi-hop wireless networks. Previous works either provide heuristic solutions without optimality analysis, or assume that unlimited retransmission is available for delivering a data packet. In this paper, we apply OR to a utility-based routing where the successful delivery of a datapacket generates benefit. The objective is to maximize utility, defined as a function of benefit and cost of transmission. As the link reliability of each relay determines eventual packet delivery and hence utility, OR offers the ability to increase reliability through opportunistic relays. We explore the optimality of utility-based routing through OR without allowing retransmission, and observe that the optimal scheme requires exhaustive searching of all paths from source to destination. We then propose a heuristic solution to select relays and determine priorities among them. Finally, we provide distributed implementations for both schemes. Simulations on NS-2 and our customized simulator are conducted to verify the effectiveness of the heuristic compared with the optimal.