ppxscal/embedding_network huggingface dataset:
An Analysis of the Rule Weights and Fuzzy Reasoning Methods for Linguistic Rule Based Classification Systems Applied to Problems with Highly Imbalanced Data Sets
Authors: Alberto Fernández, Salvador García, Francisco Herrera, María José Jesús
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

In this contribution we carry out an analysis of the rule weights and Fuzzy Reasoning Methods for Fuzzy Rule Based Classification Systems in the framework of imbalanced data-sets with a high imbalance degree. We analyze the behaviour of the Fuzzy Rule Based Classification Systems searching for the best configuration of rule weight and Fuzzy Reasoning Method also studying the cooperation of some pre-processing methods of instances. To do so we use a simple rule base obtained with the Chi (and co-authors') method that extends the well-known Wang and Mendel method to classification problems.The results obtained show the necessity to apply an instance pre-processing step and the clear differences in the use of the rule weight and Fuzzy Reasoning Method.Finally, it is empirically proved that there is a superior performance of Fuzzy Rule Based Classification Systems compared to the 1-NN and C4.5 classifiers in the framework of highly imbalanced data-sets.
Conversation: Jay W. Forrester
Authors: Christopher Evans
Venue: IEEE Annals of the History of Computing (1983)

In 1972, when I was principal investigator for the Smithsonian-AFIPS Computer History Project, I asked Robert R. Everett, president of the Mitre Corporation, to host a gathering of key people from Project Whirlwind. The group, which included Jay W. Forrester, engaged in a freewheeling discussion about some of the major mile-stones that occurred during the evolution of that important first-generation computer. One of the topics I was most anxious to explore was the development of coincident-current magnetic-core memory, the advent of which -changed computer memory from the least reliable component in a computer to the most reliable. The discussion was lively but did not adequately portray what had happened in the magnetic-core-memory development. In 1975, when Christopher Evans recorded the tape we are excerpting here (with some editing), Jay Forrester related the history of the path leading to his technological breakthrough. -Henry S. Tropp The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Evolutionary Proactive P2P Worm: Propagation Modeling and Simulation
Authors: Yejiang Zhang, Zhitang Li, Zhengbing Hu, Qingfeng Huang, Chuiwei Lu
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

Computer worms evolved continually, faster and smarter. Proactive P2P worms with new "gene" propagate over logical P2P overlay networks defined by peer relationship. Observations suggest that the node degrees of an unstructured P2P network are power law distributed thus we model it as a power law undirected graph. We study propagation process of proactive P2P worm using a dynamic epidemic model. Specifically, we adopt discrete-time to conduct recursive analysis and deterministic approximation to describe propagation of proactive P2P worm. Then we carry out extensive simulation studies, which prove that the mathematical model matches simulation results well.
Clustering with Partial Information
Authors: Hans L. Bodlaender, Michael R. Fellows, Pinar Heggernes, Federico Mancini, Charis Papadopoulos, Frances Rosamond
Venue: Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science (2008)

The Correlation Clustering problem, also known as the Cluster Editing problem, seeks to edit a given graph by adding and deleting edges to obtain a collection of vertex-disjoint cliques, such that the editing cost is minimized. The Edge Clique Partitioning problem seeks to partition the edges of a given graph into edge-disjoint cliques, such that the number of cliques is minimized. Both problems are known to be NP-hard, and they have been previously studied with respect to approximation and fixed parameter tractability. In this paper we study these two problems in a more general setting that we term fuzzy graphs, where the input graphs may have missing information, meaning that whether or not there is an edge between some pairs of vertices of the input graph can be undecided.For fuzzy graphs the Correlation Clustering and Edge Clique Partitioning problems have previously been studied only with respect to approximation. Here we give parameterized algorithms based on kernelization for both problems. We prove that the Correlation Clustering problem is fixed-parameter tractable on fuzzy graphs when parameterized by (k,r), where k is the editing cost and r is the minimum number of vertices required to cover the undecided edges. In particular we show that it has a polynomial-time reduction to a problem kernel on O(k 2 + r) vertices. We provide an analogous result for the Edge Clique Partitioning problem on fuzzy graphs. Using (k,r) as parameters, where k bounds the size of the partition, and r is the minimum number of vertices required to cover the undecided edges, we describe a polynomial-time kernelization to a problem kernel on O(k 4·3 r ) vertices. This implies fixed-parameter tractability for this parameterization. Furthermore we also show that parameterizing only by the number of cliques k, is not enough to obtain fixed-parameter tractability. The problem remains, in fact, NP-hard for each fixed k > 2.
An Unbiased Second-Order Prior for High-Accuracy Motion Estimation
Authors: Werner Trobin, Thomas Pock, Daniel Cremers, Horst Bischof
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

Virtually all variational methods for motion estimation regularize the gradient of the flow field, which introduces a bias towards piecewise constant motions in weakly textured areas. We propose a novel regularization approach, based on decorrelated second-order derivatives, that does not suffer from this shortcoming. We then derive an efficient numerical scheme to solve the new model using projected gradient descent. A comparison to a TV regularized model shows that the proposed second-order prior exhibits superior performance, in particular in low-textured areas (where the prior becomes important). Finally, we show that the proposed model yields state-of-the-art results on the Middlebury optical flow database.
Level Set Based Surface Capturing in 3D Medical Images
Authors: Bin Dong, Aichi Chien, Yu Mao, Jian Ye, Stanley Osher
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Brain aneurysm rupture has been reported to be directly related to the size of aneurysms. The current method used to determine aneurysm size is to manually measure the width of the neck and height of the dome on a computer screen. Because aneurysms usually have complicated shapes, using the size of the aneurysm neck and dome may not be accurate and may overlook important geometrical information. In this paper we present a level set based illusory surface algorithm to capture the aneurysms from the vascular tree. Since the aneurysms are described by level set functions, not only the volume but also the curvature of aneurysms can be computed for medical studies. Experiments and comparisons with models used for capturing illusory contours in 2D images are performed. This includes applications to clinical image data demonstrating the procedure of accurately capturing a middle cerebral artery aneurysm.
Multi-set DHT for Range Queries on Dynamic Data for Grid Information Service
Authors: Georges Costa, Salvatore Orlando, Marios D. Dikaiakos
Venue: Proceedings of the 1st international conference on Data Management in Grid and Peer-to-Peer Systems (2008)

Scalability is a fundamental problem for information systems when the amount of managed data increases. Peer to Peer systems are usually used to solve scalability problems as centralized approaches do not scale without large dedicated infrastructure. But most current Peer to Peer systems do not take into account that indexed data can be dynamic. Thus, we propose the Multi-set approach, which aims to find the best trade-off between DHT-based network and total replication. This approach is built over classical DHT Peer to Peer system. It can improve most of pure DHT Peer to Peer system by taking into account the dynamism of indexed data. Evaluation is done by modeling, simulation and experimentation on PlanetLab. The use case is an information service for Grid, where resource attributes are indexed.
Neural Network Capable of Amodal Completion
Authors: Kunihiko Fukushima
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

When some parts of a pattern are occluded by other objects, the visual system can often estimate the shape of missing portions from visible parts of the contours. This paper proposes a neural network model capable of such function, which is called amodal completion. The model is a hierarchical multi-layered network that has bottom-up and top-down signal paths. It contains cells of area V1, which respond selectively to edges of a particular orientation, and cells of area V2, which respond selectively to a particular angle of bend. Using the responses of bend-extracting cells, the model predicts the curvature and location of the occluded contours. Missing portions of the contours are gradually extrapolated and interpolated from the visible contours. Computer simulation demonstrates that the model performs amodal completion to various stimuli in a similar way as observed by psychological experiments.
The political subject of blogs
Authors: Eugenia Siapera
Venue: Information Polity (2008)

This article focuses on blogs as a new media form, and addresses the question of shifts in political subjectivity. The blog is seen as a new way of relating to the public sphere, and to other people, thereby involving new forms of subjectivity and political conduct. Two theories of subjectivity are discussed here, selected because of their explicit links between subjectivity and communication: these are Jurgen Habermas's inter-subjective construction of the subject, and Mark Poster's poststructuralist account of a decentred and fragmented subjectivity. These theoretical subjectivities are subsequently contrasted with the subjectivities enabled by the structural features of blogs. Thus, blog entries; the chronology of blogging; readers' comments; and hyperlinks (internal and external) are examined in terms of the type of subjectivity they support. The analysis reveals that the emerging blogging subjectivity is one that strives for autonomy and self-definition, in a way re-introducing the authorial subject, which was lost in the wake of the poststructuralist critique. On the other hand, the emerging blogging subject is not the originator of all meaning: rather meaning emerges in collaboration with others. The democratic promise of the blog might therefore be located in its potential to deliver an autonomous yet connected subject, and through this to found a new politics revolving around autonomy and solidarity. However, this promise can only be delivered if blogs explicitly address and problematise questions of power and its distribution - and in doing so, they must avoid the twin pitfalls of emotivism, the mere stating of unsupported personal opinions, and empty publicity, the spectacularisation of politics.
Techniques for Enhancing Pervasive Learning in Standard Natural Classroom
Authors: Chenping Lu, Jiaji Zhou, Liping Shen, Ruimin Shen
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

Standard Natural Classroom (SNC) is a real-time classroom based on smart space and design principles of e-learning, aiming at creating face-to-face, interactive and pervasive learning scene for students who are far from live classroom. We use various techniques in developing different kinds of components in SNC. Two components among them are specially described in this paper: E-pen and Emotion Understanding. E-pen focuses on helping teachers mark on the projection screen and several recognition algorithms are mentioned, while Emotion Understanding focuses on affective learning and is used to estimate students' emotion.
Automatic Recovery of the Left Ventricular Blood Pool in Cardiac Cine MR Images
Authors: Marie-Pierre Jolly
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

We present a method for automatic localization and rough segmentation of the left ventricle blood pool in cardiac cine magnetic resonance images. The method first detects the whole heart using time-based Fourier analysis. It then segments the left ventricle blood pool by grouping connected components across slices using isoperimetric clustering. The system was tested on 253 datasets and failed in only 2 cases.
A Novel Collaborative Filtering Mechanism for Product Recommendation in P2P Networks
Authors: Fuyong Yuan, Jian Liu, Chunxia Yin, Yulian Zhang, Nan Shen
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

With the fast development of Internet, many recommender systems have emerged in e-commerce applications to support the product recommendation. However, most centralized recommender systems based on collaborative filtering can't work effectively when large number of users require to them. In P2P networks, this paper proposes a PRBOCF (Product Recommendation Based On Collaborative Filtering), which is a scalable mechanism to recommend products in distributed way. In PRBOCF, as two main parts of product information, image and text are weighted respectively and their features are represented by one vector. For increasing the quality of representing the text of product according to the Vector Space Model, WordNet v2.0 is employed to deal with the relationship of words in the text. Then a peer's preference is represented by a feature space consisting of all the vectors of its saved products information. For acquiring the recommender systems scalable and best quality of recommendation, PRBOCF makes product recommendation by searching for neighbor peers with similar preference through local information of recent ratings. Finally, the simulation results are discussed.
Interface design and emotions experienced on B2C Web sites: Empirical testing of a research model
Authors: Jean íthier, Pierre Hadaya, Jean Talbot, Jean Cadieux
Venue: Computers in Human Behavior (2008)

This paper examines the impact of four Web site interface features on the cognitive process that trigger online shoppers' emotions, operationalized as mental states of readiness that arise from appraisal of events and considered as direct antecedents to approach or avoidance behaviors. A research model was tested with data collected from 215 Web shopping episodes for low-touch merchandise. Results show that shoppers experienced all six emotions posited in the model. The emotions of liking and joy were experienced intensively by a substantial number of shoppers. The results also demonstrate that interface features - key components of the usability of a Web site - influenced the three cognitive appraisals illustrated in the research model. Moreover, the cognitive appraisals of situational state and control potential impacted the six emotions examined. This paper also highlights several theoretical contributions and managerial implications that should help managers and Web site managers improve the interface design of their Web sites in order to facilitate information gathering and better support online shopping processes.
Streaming Scenes to MPEG-4 Video-Enabled Devices
Authors: Yuval Noimark, Daniel Cohen-Or
Venue: IEEE Computer Graphics and Applications (2003)

MPEG-4 is an object-based standard for compressing multimedia content. In particular, it describes the means for representing video as objects and compressing each one of them. Pervasive devices can decode and present MPEG-4 content for mobile entertainment. The authors present a technique for streaming synthesized 3D computer graphics scenes to such devices. The technique improves the quality of the resulting video for a given network bandwidth. The authors also describe how to further improve the compression ratio by using object-based approach.
When Overlapping Unexpectedly Alters the Class Imbalance Effects
Authors: V. García, R. A. Mollineda, J. S. Sánchez, R. Alejo, J. M. Sotoca
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

This paper makes use of several performance metrics to extend the understanding of a challenging imbalanced classification task. More specifically, we refer to a problem in which the minority class is more represented in the overlap region than the majority class, that is, the overall minority class becomes the majority one in this region. The experimental results demonstrate that the use of a set of appropriate performance measures allows to figure out such an atypical case.
Regression Model Based on Fuzzy Random Variables
Authors: Shinya Imai, Shuming Wang, Junzo Watada
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

In real-world regression problems, various statistical data may be linguistically imprecise or vague. Because of such co-existence of random and fuzzy information, we can not characterize the data only by random variables. Therefore, one can consider the use of fuzzy random variables as an integral component of regression problems.The objective of this paper is to build a regression model based on fuzzy random variables. First, a general regression model for fuzzy random data is proposed. After that, using expected value operators of fuzzy random variables, an expected regression model is established. The expected regression model can be developed by converting the original problem to a task of a linear programming problem. Finally, an explanatory example is provided.
Improving Piecewise-Linear Registration Through Mesh Optimization
Authors: Vicente Arévalo, Javier González
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

Piecewise-linear methods accomplish the registration by dividing the images in corresponding triangular patches, which are individually mapped through affine transformations. For this process to be successful, every pair of corresponding patches must lie on projections of a 3D plane surface; otherwise, the registration may generate undesirable artifacts, such as broken lines, which diminish the registration quality. This paper presents a new technique for improving the registration consistency by automatically refining the topology of the corresponding triangular meshes used by this method. Our approach iteratively modifies the connectivity of the meshes by swapping edges. For detecting the edges to be swapped, we analyze the local registration consistency before and after applying the action, employing for that the mutual information (MI), a metric for registration consistency significantly more robust than other well-known metrics such as normalized cross correlation (NCC) or sum of square differences (SSD). The proposed method has been successfully tested with different sets of test images, both synthetic and real.
Thread Quantification for Concurrent Shape Analysis
Authors: J. Berdine, T. Lev-Ami, R. Manevich, G. Ramalingam, M. Sagiv
Venue: Proceedings of the 20th international conference on Computer Aided Verification (2008)

In this paper we address the problem of shape analysis for concurrent programs. We present new algorithms, based on abstract interpretation, for automatically verifying properties of programs with an unbounded number of threads manipulating an unbounded shared heap.Our algorithms are based on a new abstract domain whose elements represent thread-quantified invariants: i.e., invariants satisfied by all threads. We exploit existing abstractions to represent the invariants. Thus, our technique lifts existing abstractions by wrapping universal quantification around elements of the base abstract domain. Such abstractions are effective because they are thread modular: e.g., they can capture correlations between the local variables of the same thread as well as correlations between the local variables of a thread and global variables, but forget correlations between the states of distinct threads. (The exact nature of the abstraction, of course, depends on the base abstraction lifted in this style.)We present techniques for computing sound transformers for the new abstraction by using transformers of the base abstract domain. We illustrate our technique in this paper by instantiating it to the Boolean Heap abstraction, producing a Quantified Boolean Heap abstraction. We have implemented an instantiation of our technique with Canonical Abstraction as the base abstraction and used it to successfully verify linearizability of data-structures in the presence of an unbounded number of threads.
New Challenges in Model Checking
Authors: Gerard J. Holzmann, Rajeev Joshi, Alex Groce
Venue: 25 Years of Model Checking: History, Achievements, Perspectives (2008)

In the last 25 years, the notion of performing software verification with logic model checking techniques has evolved from intellectual curiosity to accepted technology with significant potential for broad practical application. In this paper we look back at the main steps in this evolution and illustrate how the challenges have changed over the years, as we sharpened our theories and tools. Next we discuss a typical challenge in software verification that we face today --- and that perhaps we can look back on in another 25 years as having inspired the next logical step towards a broader integration of model checking into the software development process.
The Design Space of Information Presentation: Formal Design Space Analysis with FCA and Semiotics
Authors: Michael May, Johannes Petersen
Venue: Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications (2007)

A semiotic approach to the design space of information presentation is presented in which Formal Concept Analysis (FCA) is used to represent and explore attributes of abstract sign types and the media (graphical, haptic, acoustic, gestic) through which they are presented as specific representational forms. Early taxonomies in design have typically been incomplete (in only considering graphics) and inconsistent (in the absence of separation between media and sign types). With digital multimedia and the future "semantic web", we need a consistent taxonomy to support component-based flexible (adaptive, tailorable) presentations with a clear separation between (a) the content forms of data, (b) the representational forms through which data is expressed, (c) the combination of media of presentation, and (d) the specific layout within the constraints of the presentation devices and the ergonomic and aesthetic choices of designers and users.