ppxscal/embedding_network huggingface dataset:
Scenario Discovery Using Nonnegative Tensor Factorization
Authors: Brett W. Bader, Andrey A. Puretskiy, Michael W. Berry
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

In the relatively new field of visual analytics there is a great need for automated approaches to both verify and discover the intentions and schemes of primary actors through time. Data mining and knowledge discovery play critical roles in facilitating the ability to extract meaningful information from large and complex textual-based (digital) collections. In this study, we develop a mathematical strategy based on nonnegative tensor factorization (NTF) to extract and sequence important activities and specific events from sources such as news articles. The ability to automatically reconstruct a plot or confirm involvement in a questionable activity is greatly facilitated by our approach. As a variant of the PARAFAC multidimensional data model, we apply our NTF algorithm to the terrorism-based scenarios of the VAST 2007 Contest data set to demonstrate how term-by-entity associations can be used for scenario/plot discovery and evaluation.
Multimedia Retrieval Algorithmics
Authors: Remco C. Veltkamp
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

After text retrieval, the next waves in web searching and multimedia retrieval are the search for and delivery of images, music, video, and 3D scenes. Not only the perceptual and cognitive aspects, but also many of the algorithmic and performance aspects are still badly understood. One relevant issue is the design of dissimilarity measures (distance functions) that have desired properties. Another aspect is the development of algorithms that can compute or approximate these distances efficiently. Indexing data structures and search algorithms are necessary to make the search more efficient than sequential browsing through large collections. Apart from provable properties of individual algorithms, the experimental verification of the performance of a complete retrieval system is important to analyse merits and drawbacks of certain approaches, and to compare various techniques.
Outlier Detection Based on the Distribution of Distances between Data Points
Authors: Vydunas Šaltenis
Venue: Informatica (2004)

A novel approach to outlier detection on the ground of the properties of distribution of distances between multidimensional points is presented. The basic idea is to evaluate the outlier factor for each data point. The factor is used to rank the dataset objects regarding their degree of being an outlier. Selecting the points with the minimal factor values can then identify outliers. The main advantages of the approach are: (1) no parameter choice in outlier detection is necessary; (2) detection is not dependent on clustering algorithms. To demonstrate the quality of the outlier detection, the experiments were performed on widely used datasets. A comparison with some popular detection methods shows the superiority of our approach.
An Incremental Feature Learning Algorithm Based on Least Square Support Vector Machine
Authors: Xinwang Liu, Guomin Zhang, Yubin Zhan, En Zhu
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

Incremental learning has been widely addressed in machine learning literature to deal with tasks where the learning environment is steadily changing or training samples become available one after another over time. Support Vector Machine has been successfully used in pattern recognition and function estimation. In order to tackle with incremental learning problems with new features, an incremental feature learning algorithm based on Least Square Support Vector Machine is proposed in this paper. In this algorithm, features of newly joined samples contain two parts: already existing features and new features. Using historic structural parameters which are trained from the already existing features, the algorithm only trains the new features with Least Square Support Vector Machine. Experiments show that this algorithm has two outstanding properties. First, different kernel functions can be used for the already existing features and the new features according to the distribution of samples. Consequently, this algorithm is more suitable to deal with classification tasks which can not be well solved by using a single kernel function. Second, the training time and the memory space can be reduced because the algorithm fully uses the structural parameters of classifiers trained formerly and only trains the new features with Least Square Support Vector Machine. Some UCI datasets are used to demonstrate the less training time and comparable or better performance of this algorithm than the Least Square Support Vector Machine.
The Return of Transactions
Authors: Rachid Guerraoui
Venue: Proceedings of the 22nd European conference on Object-Oriented Programming (2008)

Major chip manufacturers have recently shifted their focus from speeding individual processors to multiplying them on the same chip and shipping multicore architectures. Boosting the performance of programs will thus necessarily go through parallelizing them. This is not trivial and the average programmer will badly need abstractions for synchronizing concurrent accesses to shared memory objects. The transaction abstraction looks promising for this purpose and there is a lot of interest around its use in modern parallel programming. This talk will investigate whether the "return" of the old transaction idea brings any interesting research question, especially for the programming language community. 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
Inference Based on Distributed Representations Using Trajectory Attractors
Authors: Ken Yamane, Takashi Hasuo, Masahiko Morita
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

It is considered that a key to overcoming the limitations of classical artificial intelligence is to process distributed representations of information without symbolizing them. However, conventional neural networks require local or symbolic representations to perform complicated processing. Here we present a brain-like inference engine consisting of a nonmonotone neural network that makes inferences based only upon distributed representations. This engine deduces a conclusion according to state transitions of the network along a trajectory attractor formed in a large-scale dynamic system. It has the powerful capability of analogical reasoning. We also construct a simple inference system and demonstrate its many advantages; for example, it can perform nonmonotonic reasoning simply and naturally.
On the Credal Structure of Consistent Probabilities
Authors: Fabio Cuzzolin
Venue: Proceedings of the 11th European conference on Logics in Artificial Intelligence (2008)

In this paper we introduce a novel, simpler form of the polytope of inner Bayesian approximations of a belief function, or "consistent probabilities". We prove that the set of vertices of this polytope is generated by all possible permutations of elements of the domain, mirroring a similar behavior of outer consonant approximations. 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
Spacial Localization in Wireless Sensor Networks Based on Beacon Selection
Authors: Shuo Xiao, Xueye Wei, Yu Wang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

The localization algorithm in wireless sensor network is always a hot spot. Information collected by the sensors is meaningless without the position of the sensors. Now, paying little attention to 3-D space, most of the algorithms are for 2-D space. In this paper we introduce a novel algorithm for 3-D space called OBS (Optimal Beacon Selection) algorithm. In this algorithm we launched the concept of position error parameter, with consideration of communication range and position accuracy of beacon. The experiment results show that this method can minimize the accumulation error and improve the location precision.
A Calibration Framework for Capturing and Calibrating Software Performance Models
Authors: Xiuping Wu, Murray Woodside
Venue: Proceedings of the 5th European Performance Engineering Workshop on Computer Performance Engineering (2008)

Software performance engineering could benefit from combining modeling and testing techniques, if performance models could be derived more cheaply and more easily. This work investigates how known testing and estimation methodologies can be combined in a calibration framework, to provide and maintain performance models in sync with a developing product or component library. There are two main aspects. The first addresses a major barrier in practice, the calibration of model parameters that represent quantities that cannot easily be measured directly. This work calibrates these "hidden parameters" efficiently using a Kalman Filter. The second is the exploitation of the filter estimator to control the calibration framework, for example to terminate a test when accuracy is sufficient, and to design tests for parameter coverage. The technique is demonstrated on simulated data and on an implemented Voice-over-IP (VoIP) system.
Efficient techniques for video shot segmentation and retrieval
Authors: Moon-Chuen Lee
Venue:  (2007)

Video segmentation is the first step to most content-based video analysis. In this thesis, several methods have been proposed to detect shot transitions including cut and wipe. In particular, a new cut detection method is proposed to apply multi-adaptive thresholds during three-step processing of frame-by-frame discontinuity values. A "likelihood value", which measures the possibility of the presence of a cut at each step of processing, is used to reduce the influence of threshold selection to the detection performance. A wipe detection algorithm is also proposed in our thesis to detect various wipe effects with accurate frame ranges. In the algorithm, we carefully model a wipe based on its properties and then use the model to remove possible confusion caused by motion or other transition effects. With the segmented video shots, video indexing and retrieval systems retrieve video shots using shot-based similarity matching based on the features of shot key-frames. Most shot-based similarity matching methods focus on low-level features such as color and texture. Those methods are often not effective enough in video retrieval due to the large gap between semantic interpretation of videos and the low level features. In this thesis, we propose an attention-driven video retrieval method by using an efficient spatiotemporal attention detection framework. Within the framework, we propose an efficient method for focus of attention (FOA) detection which involves combining adaptively the spatial and motion attention to form an overall attention map. Without computing motion explicitly, it detects motion attention using the rank deficiency of gray scale gradient tensors. We also propose an attention-driven shot matching method using primarily FOA. The matching method boosts the attended regions in the respective shots by converting attention values to importance factors in the process of shot similarity matching. Experiment results demonstrate the advantages of the proposed method in shot similarity matching.
History of the Design of the SAGE Computer-The AN/FSQ-7
Authors: Morton M. Astrahan, John F. Jacobs
Venue: IEEE Annals of the History of Computing (1983)

This paper tells the story of the development of the SAGE (Semi-Automatic Ground Environment) air-defense computer, the AN/FSQ-7. At the time of its operational deployment in 1958, the AN/FSQ-7 was the first large-scale, real-time digital control computer supporting a major military mission. The AN/FSQ-7 design, including its architecture, components, and computer programs, drew on research and development programs throughout the United States, but mostly on work done at MIT's Project Whirlwind and at IBM.
Spatial and Behavioral Types in the Pi-Calculus
Authors: Lucia Acciai, Michele Boreale
Venue: Proceedings of the 19th international conference on Concurrency Theory (2008)

We present a framework that combines ideas from spatial logics and Igarashi and Kobayashi's behavioural type systems, drawing benefits from both. In our approach, type systems for the pi-calculus are introduced where newly declared (restricted) names are annotated with spatial process properties, predicating on those names, that are expected to hold in the scope of the declaration. Types are akin to ccs terms and account for the processes abstract behaviour and "shallow" spatial structure. The type systems relies on spatial model checking, but properties are checked against types rather than against processes. The considered class of properties is rather general and, differently from previous proposals, includes both safety and liveness ones, and is not limited to invariants.
Methodology to Evaluate the Functionality of Specification Languages
Authors: Jelena Gasperovic, Albertas Caplinskas
Venue: Informatica (2006)

The paper proposes a methodology for evaluation of specification language functionality characteristics. It describes background of the proposed methodology, discusses the methodology in detail, and shortly describes experimental results obtained using the proposed methodology to evaluate the functionality of Z and UML languages.
Embodied interaction and user experience: a study of interactive, three-dimensional graphics in procedural information
Authors: Robert Krull
Venue:  (2007)

This dissertation describes the collection of data from observing a new mediation method for procedural information. The mediation is accomplished with experimental software designed by the researcher, called SphereView . Examined will be the user effects of delivering information virtually, via a human-computer interaction (HCI) with interactive, 3D graphics, as users follow that information in an assembly task. I follow a protocol informed by situated action as described by Suchman (1987), to observe individual users performing purposeful action, in situ. One third of users will work with still graphics set to 45&deg; angles; one third will work with interactive, 3D graphics; and one third will work with interactive, 3D graphics with automatic presets to 45&deg; angles. Among other dependent measures, time to build and accuracy rates will be compared between groups. The distribution of user angular preferences will be compared to angles prescribed from relevant literature (Blanz et al., 1996; Heiser et al., 2002; Agrawala et al., 2003; Heiser and Tversky, 2004). Additionally, data from Likert scales will look for differences in user experience. The graphical instructions are viewed on Dell 18-inch flat-screen monitor and manipulated with a mouse (click and drag). The data from this research may reveal new insights into users&rsquo; exploratory behavior, when they are presented with interactive, 3D graphical instructions, as a tool. Data about user image angle preferences may help inform 2D presentation of information. Visual data may inform us about the users&rsquo; experience of reading to do something.&ldquo;Even the mere act of manipulating and rearranging the data in an interactive graphic has value&mdash;the user becomes a participant in the discovery process, not just a passive observer. This can be invaluable. [T]he process of manipulating &hellip; puts [the user] face-to-face with aspects of the data that she may never have noticed on paper.&rdquo; Designing Interfaces, Jennifer Tidwell, O&rsquo;Reilly Media, 2006
Evaluation of an intelligent e-tool for deaf children: extended abstract
Authors: Rosella Gennari, Ornella Mich
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

LODE is a web tool for deaf children, which aims at stimulating global reasoning on written e-stories. This paper reports on an initial prototype application of LODE. First, we motivate the need of an e-tool such as LODE for deaf children, then we report on the assessment of the prototype with expert users and two deaf children, laying the groundwork for the final evaluation and development of LODE.
Multi-Site Retrieval of Declustered Data
Authors: Ali Saman Tosun
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Declustering techniques reduce query response times through parallel I/O by distributing data among multiple devices. Recently, replication based approaches were proposed to further reduce the response time. All of the replication based schemes assume that replication is done at a single site. In this paper, we consider replicated data stored at multiple sites. We formulate multi-site retrieval problem as a maximum flow problem and solve it using maximum flow techniques. We propose a low complexity online algorithm for the problem. We investigate the proposed scheme using various replication schemes, query types and query loads. Proposed scheme can easily be extended to nonuniform data and to any number of sites. Experimental results show that replication using orthogonal allocation performs the best under various settings.
Mapping Image Low-Level Descriptors to Semantic Concepts
Authors: Anca Ion, Liana Stanescu, Dan Burdescu, Stefan Udristoiu
Venue: Proceedings of the 2008 The Third International Multi-Conference on Computing in the Global Information Technology (iccgi 2008) (2008)

Our goal is to organize the image contents semantically. In this paper, we propose a method to classify the images semantically, using the C-Fuzzy algorithm to segment the natural scenes into perceptually uniform regions. The low-level characteristics that are taken into account are: color, texture, shape, absolute spatial arrangement, spatial coherency, and dimension. Since humans are the ultimate users of most image retrieval systems, it is important to organize the contents semantically, according to meaningful categories. This requires an understanding of the important semantic categories that humans use for image classification, and the extraction of meaningful image features that can discriminate between these categories. A lot of experiments, in which the human subjects had to group images into semantic categories and to explain the criteria for their choice, were realized. From these experiments, we identify the semantic categories (landscapes, animals, flowers, etc), the semantic indicators or intermediate descriptors and their visual characteristics.
Review of combinatorial optimization: packing and covering
Authors: Gérard Cornuéjols
Venue: ACM SIGACT News (2008)

This book is based on a series of ten lectures given by Cornuéjols at a CBMS-NSF regional conference in 1999. It is a monograph on the polyhedral combinatorics of packing and covering problems. The fundamental approach is to formulate a combinatorial optimization problem as an integer linear programming problem and then determine conditions under which the feasible region of the linear programming (LP) relaxation of the problem has integral vertices. In such cases, the problem can be solved efficiently by simply solving the LP relaxation.
Efficient Unit-Selection in Text-to-Speech Synthesis
Authors: Aleš Mihelič, Jerneja Žganec Gros
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

This paper presents a method for selecting speech units for polyphone concatenative speech synthesis, in which the simplification of procedures for search paths in a graph accelerated the speed of the unit-selection procedure with minimum effects on the speech quality. The speech units selected are still optimal; only the costs of merging the units on which the selection is based are less accurately determined. Due to its low processing power and memory footprint requirements, the method is applicable in embedded speech synthesizers.
Design of Adaptive Model Predictive Controller for Wireless Sensor Networks
Authors: Chen Yi, Chen Li, Li Rong, Gao Ge
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

In wireless sensor networks, the network state beacon exchange rate is vital to determine the quality of service (QoS) performance of network state. It is important to schedule this parameter adaptively due to the dynamic nature of the networks. In this paper, an adaptive self-control model for wireless sensor (ASMW) is presented which model the whole wireless networks as a closed-loop system. The model is independent of the precision of the model parameters but operates adaptively. The simulation results show that the ASMW model is able to improve the performance of wireless networks effectively in adjusting the value of the beacon exchange rate to the reference value and uncomplicated to be implied in hardware.
A Smart Communication System for Avatar Agents in Virtual Environment
Authors: Soo-Hyun Park, Seung-Hyun Ji, Dong-Sung Ryu, Hwan-Gue Cho
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

This paper propose a virtual communication system for avatar agents using geometry topology. Current virtual communication systems have several problems and limitations since they use only 2-dimensional dialog box and word balloons though they provide 3-dimensional virtual environment to communicate in virtual space. To solve these problems, modern virtual communication systems have developed artificial chatting techniques such as 'One-to-One Chatting' and 'Group Chatting'. We propose a novel communication system for avatar agents using geometry topology information such as distances and directions between avatar agents without artificial chatting techniques. The main contribution of our work is threefold. First, we display 'Partial Talk' and 'Complete Talk' by using geometry topology so that make more realistic and natural conversation without artificial complex communication architecture. Second, we design a greedy algorithm for placing the word balloons in 3-dimensional virtual space. Finally, we propose a method to analyze order of dialogs and to construct talk sequence graph.
Cooperative Dynamics in Spatially Structured Populations
Authors: Lihui Shang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

The evolution of cooperative behaviors of small-world networking agents in a snowdrift game mode is investigated, where two agents (nodes) are connected with probability depending on their spatial Euclidean lattice distance in the power-law form controlled by an exponent ¿. Extensive numerical simulations indicate that the game dynamics crucially depends on the spatial topological structure of underlying networks with different values of the exponent ¿. Especially, in the distance-independent case of ¿=0, the small-world connectivity pattern contributes to an enhancement of cooperation compared with that in regular lattices, even with a high cost-to-benefit ratio r. However, with the increment of ¿ > 0, when r ¿ 0.4, the spatial distance-dependent small-world (SDSW) structure tends to inhibit the evolution of cooperation in the snowdrift game.