ppxscal/embedding_network huggingface dataset:
Measuring Psychophysiological Signals in Every-Day Situations
Authors: Walter Ritter
Venue: Proceedings of the 5th International on ConferenceUniversal Access in Human-Computer Interaction. Part II: Intelligent and Ubiquitous Interaction Environments (2009)

Psychophysiological signals enable computer systems to monitor the emotional state of a user. Such a system could adapt its behavior to reduce stress, give assistance, or suggest well-being tips. All of this should lead to a technology that is more user-friendly and more accessible to older people. Measuring physiological signals in research labs has been done for many years. In such a controlled environment the quality of signals is very high because of the optimal placement of electrodes by research staff. Analysis techniques can therefore rely on high quality data. Measuring physiological signals in real-life settings without the assistance of well-trained staff, is much more challenging because of artifacts and signal distortions.In this paper we discuss the approach taken in the Aladin project to cope with the inferior and unreliable quality of physiological signal measurements. We discuss a sensor design intended for every-day use and present the variance of skin conductance we experienced within measurements, between different measurements of the same individual as well as between different persons. Finally, we suggest using trends instead of absolute values as a basis for physiology-enhanced human-computer interaction "in the wild".
Featherweight Jigsaw: A Minimal Core Calculus for Modular Composition of Classes
Authors: Giovanni Lagorio, Marco Servetto, Elena Zucca
Venue: Proceedings of the 23rd European Conference on ECOOP 2009 --- Object-Oriented Programming (2009)

We present FJig, a simple calculus where basic building blocks are classes in the style of Featherweight Java, declaring fields, methods and one constructor. However, inheritance has been generalized to the much more flexible notion originally proposed in Bracha's Jigsaw framework. That is, classes play also the role of modules, that can be composed by a rich set of operators, all of which can be expressed by a minimal core.We keep the nominal approach of Java-like languages, that is, types are class names. However, a class is not necessarily a structural subtype of any class used in its defining expression.The calculus allows the encoding of a large variety of different mechanisms for software composition in class-based languages, including standard inheritance, mixin classes, traits and hiding. Hence, FJig can be used as a unifying framework for analyzing existing mechanisms and proposing new extensions.We provide two different semantics of an FJig program: flattening and direct semantics. The difference is analogous to that between two intuitive models to understand inheritance: the former where inherited methods are copied into heir classes, and the latter where member lookup is performed by ascending the inheritance chain. Here we address equivalence of these two views for a more sophisticated composition mechanism.
Precomputation-Based Rendering
Authors: Ravi Ramamoorthi
Venue:  (2009)

Precomputation-Based Rendering presents a unified mathematical view of precomputation-based rendering, while discussing its motivation, history and current and future research directions. It goes back to some of the early origins of precomputation-based rendering in replaying offline solutions for image relighting. Following this, it describes the new innovations in terms of environment maps and spherical harmonic convolution that inspired the PRT method of Sloan et al. in 2002, the approach that for the first time brought precomputation-based ideas into the mainstream of real-time rendering. It goes on to discuss a number of new innovations in this field over the past six years, to all-frequency effects, changing lighting and view, reflectance editing, dynamic scenes and lighting design. Precomputation-Based Rendering is an invaluable reference for students and computer graphics researchers. It will also be of interest to professional graphics practitioners.
A Novel Blind Watermarking Using Hybrid Embedding Technique
Authors: Wei-Hung Lin, Yuh-Rau Wang, Shi-Jinn Horng
Venue: Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing (2009)

This paper proposes a blind watermarking method which utilizes the Euclidean distance between adjacent coefficients in wavelet trees to improve robustness, and lower distortion. To decrease the probability of being detected or deleted, different combinations of significant or insignificant coefficients are proposed. We embed the watermark in either two significant or two insignificant coefficients. The value of detector is adaptable when a watermarked image is under different attacks. This can facilitate us to extract watermark more accurately. The experimental results show that the superiority of the proposed schemes and the advantages are demonstrated through comparison with conventional wavelet tree based watermarking.
A 3-Component Inverse Depth Parameterization for Particle Filter SLAM
Authors: Evren İmre, Marie-Odile Berger
Venue: Proceedings of the 31st DAGM Symposium on Pattern Recognition (2009)

The non-Gaussianity of the depth estimate uncertainty degrades the performance of monocular extended Kalman filter SLAM (EKF-SLAM) systems employing a 3-component Cartesian landmark parameterization, especially in low-parallax configurations. Even particle filter SLAM (PF-SLAM) approaches are affected, as they utilize EKF for estimating the map. The inverse depth parameterization (IDP) alleviates this problem through a redundant representation, but at the price of increased computational complexity. The authors show that such a redundancy does not exist in PF-SLAM, hence the performance advantage of the IDP comes almost without an increase in the computational cost.
A Shape Recognition Scheme for Wireless Sensor Networks Based on a Distance Field Method
Authors: Yang Yang, Satoshi Fujita, Sayaka Kamei
Venue: Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing (2009)

In this paper, we consider a problem of recognizing the shape of an event region in wireless sensor networks (WSNs). The basic idea of our algorithm is to focus on a distance field defined by the hop count from the boundary of the event region. By constructing such field, we can easily identify several critical points in the event region (e.g., local maximum and saddle point), which will be used to characterize the shape of the event region. The communication cost required for a shape recognition significantly decreases compared with a naive centralized scheme by selectively allowing those critical points to send a notification message to a data aggregation point. The performance of the proposed scheme is evaluated by simulation. The result of simulations indicates that: 1) accuracy of shape recognition depends on the density of the underlying WSN, while it is robust against the lack of sensors in a particular region in the field, and 2) the cost of shape recognition significantly decreases by applying the proposed scheme.
Look Smarter Than You Are with Essbase 11: An Administrator's Guide
Authors: Edward Roske
Venue:  (2009)

Learn how to be an Essbase Administrator: 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
A Historical Perspective on Computer Arithmetic
Authors: Stanley Mazor
Venue: Proceedings of the 2009 19th IEEE Symposium on Computer Arithmetic (2009)

My first experiences with decimal computer arithmetic in college (1963) influenced my subsequent career decisions and projects as described herein. Many popular early computers focused on commercial applications for which decimal arithmetic was appropriate. These digit-serial implementations did not minimize hardware cost, but provided the precision needed by the application. Decimal arithmetic as taught in elementary school is a fine starting point for describing computer operation, but for non-engineers the hardware realization of an adder is mysterious. Routing circuits, while not always practical, illustrate how two-bits can be added by using switches, relays, or MOSFET's. 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
Contract Monitoring in Agent-Based Systems: Case Study
Authors: Jiří Hodík, Jiří Vokřínek, Michal Jakob
Venue: Proceedings of the 4th International Conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing (2009)

Monitoring of fulfilment of obligations defined by electronic contracts in distributed domains is presented in this paper. A two-level model of contract-based systems and the types of observations needed for contract monitoring are introduced. The observations (inter-agent communication and agents' actions) are collected and processed by the contract observation and analysis pipeline. The presented approach has been utilized in a multi-agent system for electronic contracting in a modular certification testing domain.
Analysis on Saccade-Related Independent Components by Various ICA Algorithms for Developing BCI
Authors: Arao Funase, Motoaki Mouri, Yagi Tohru, Andrzej Cichocki, Ichi Takumi
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

Saccade-related electroencephalogram (EEG) signals have been the subject of application oriented research by our group toward developing a brain computer interface (BCI). Our goal is to develop novel BCI based on eye movements system employing EEG signals on-line. Most of the analysis of the saccade-related EEG data has been performed using ensemble averaging approaches. In signal processing method for BCI, raw EEG signals are analyzed. In ensemble averaging method which is major EEG analysis is not suitable for processing raw EEG signals. In order to process raw EEG data, we use independent component analysis. This paper presents extraction rate of saccade-related EEG signals by four ICA algorithms and six window size. In terms of extracting rates across ICA algorithms, The JADE and Fast ICA have good results. As you know, calculation time in Fast ICA is faster than calculation time in JADE. Therefore, in this case, Fast ICA is the best in order to extract saccade-related ICs. Next, we focus on extracting rates in each window. The windows not including EEG signals after saccade and the windows which has small window size has better extracting rates.
Demo abstract: Discovering services in mobile, flexible and heterogeneous wireless sensor networks
Authors: Aleksandar Kovacevic, Junaid Ansari, Petri Mahonen
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

Wireless Sensor Network applications (WSNs) are starting to enter into our daily life. Discovering sensor nodes and the services hosted by them is imperative to any large scale and flexible sensor network application. The heterogeneity and dynamics of wireless sensor networks and their applications are challenges for service discovery protocols. In this demonstration, we present a light-weight Service Discovery protocol (nanoSD) and its integration into a health care application with heterogeneous network architecture. NanoSD is a sensor network specific service discovery protocol that is specifically designed to be scalable and meet real WSN deployment challenges. Furthermore, it can easily be integrated with web-service based backend systems with very minimal resource costs.
Using lexical and relational similarity to classify semantic relations
Authors: Diarmuid Ó Séaghdha, Ann Copestake
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

Many methods are available for computing semantic similarity between individual words, but certain NLP tasks require the comparison of word pairs. This paper presents a kernel-based framework for application to relational reasoning tasks of this kind. The model presented here combines information about two distinct types of word pair similarity: lexical similarity and relational similarity. We present an efficient and flexible technique for implementing relational similarity and show the effectiveness of combining lexical and relational models by demonstrating state-of-the-art results on a compound noun interpretation task.
IPv6 Network Comprehensive Deployment on Campus Network
Authors: Chen Yan-ge, Hu Zi-yi, Tan Shui-mu
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

IPv6 deployment on campus network will play a tremendous role in IPv6 network construction. For realizing all campus IPv6 network deployment, this article introduces a kind of IPv6 department scheme and put in practice in Xuchang University. At present we have established the pure IPv6 network, realizing IPv4 network and IPv6 network interconnection and intercommunication through the NAT-PT and ALG gateway, achieving the whole campus network prototype system of IPv4 /IPv6 basic services transition, and verifying the feasibility of the network scheme.
Are We Trapped by Majority Influences in Electronic Word-of-Mouth?
Authors: Yu Tong, Yinqing Zhong
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

Being an effective online mechanism to generate large-scale electronic Word-of-Mouth (EWOM), online feedback systems (OFS) offers a variety of system design cues to facilitate consumers' decision making. However, such cues may lead consumers to make inferences based on an overall picture of the majority opinion without scrutinizing the content of reviews. This study draws on theories of majority/minority influence and dual-process to explore the influences of OFS design cues on consumers' learning outcomes (i.e., awareness of product/service, confidence in judgment, intention to searching for additional information and intention to conform to majority). Numerical and power majority influences are examined through two design cues: review clustering format (list-clustering vs. pair-clustering) and source credibility (available vs. unavailable).
Research on a Virtual Data Integration on the Web
Authors: Cheng Chuanqing, Cheng Xuexian
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

Now the information systems grow so fast, this situation lets the communication among systems more complicate. So it will be very difficult to handle the logical business when the old way is used to define the different data and the complex, no- transplantable and humdrum way to handle them.This paper describes the virtual data’s conception and examples and proposes a scheme to integrate these data. The paper summarizes the overall characters of the all complex data, propose a new processing mode,which is the flat-form of the virtual data handling. An example is given to show how to do in a factual situation..
A first-order theory of Stanislavskian scene analysis
Authors: Leora Morgenstern
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

At the turn of the last century, Constantin Stanislavski developed a new system of acting, replacing the mannered gestures and forced emotion then popular with a more natural style. The core of his system lay in having actors perform a process of scene analysis, in which an actor would flesh out the circumstances of the play so that the character's motivations and actions would follow logically. This paper is an attempt to ground Stanislavski's method of scene analysis in a formal theory of action. We discuss the relations between Stanislavskian and formal AI theories of action and planning, give a formal definition of the end product of a scene analysis, and characterize the conditions under which a scene analysis is coherent.
Synchronized Oriented Mutations Algorithm for Training Neural Controllers
Authors: Vincent Berenz, Kenji Suzuki
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

Developing neural controllers for autonomous robotics is a tedious task as the desired state trajectory of the robot is very often not known in advance. This led to the large success of evolutionary algorithm in this field. In this paper we introduce SOMA (Synchronized Oriented Mutations Algorithm), which presents an alternative for rapidly minimizing the parameters characterizing a given individual. SOMA is characterized by its easy implementation and its flexibility: it can use any continuous fitness function and be applied to optimize neural network of diverse topologies using any kind of activation functions. Contrary to evolutionary approach, it is applied on a single individual rather than on a population. Because the procedure is very fast, it allows for rapid screening and selection of good candidates. In this paper, the efficiency of SOMA at training ordered connection feed forward networks on function modeling problem, classification problem and robotic controllers is investigated.
A Novel Multivariate Discretization Method for Mining Association Rules
Authors: Hantian Wei
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

Data mining aims at discovering useful patterns in large datasets. In this paper, we present a novel multivariate discretization method for finding association patterns based on clustering and genetic algorithm. This method consists of two steps. Firstly we adopt a density-based clustering technique to identify the regions that possibly hide the interesting patterns from data space. Confined to the data in these regions, we then develop a genetic algorithm to simultaneously discretize multi-attributes according to entropy criterion. The effectiveness of the proposed method is demonstrated with the experiment on a real data set.
Pattern Mining with Natural Language Processing: An Exploratory Approach
Authors: Ana Cristina Mendes, Cláudia Antunes
Venue: Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition (2009)

Pattern mining derives from the need of discovering hidden knowledge in very large amounts of data, regardless of the form in which it is presented. When it comes to Natural Language Processing (NLP), it arose along the humans' necessity of being understood by computers. In this paper we present an exploratory approach that aims at bringing together the best of both worlds. Our goal is to discover patterns in linguistically processed texts, through the usage of NLP state-of-the-art tools and traditional pattern mining algorithms.Articles from a Portuguese newspaper are the input of a series of tests described in this paper. First, they are processed by an NLP chain, which performs a deep linguistic analysis of text; afterwards, pattern mining algorithms Apriori and GenPrefixSpan are used. Results showed the applicability of sequential pattern mining techniques in textual structured data, and also provided several evidences about the structure of the language.
PASS Approximation
Authors: Uriel Feige, Nicole Immorlica, Vahab S. Mirrokni, Hamid Nazerzadeh
Venue: Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (2009)

We introduce a new framework for designing and analyzing algorithms. Our framework applies best to problems that are inapproximable according to the standard worst-case analysis. We circumvent such negative results by designing guarantees for classes of instances, parameterized according to properties of the optimal solution. We also make sure that our parameterized approximation, called PArametrized by the Signature of the Solution (PASS) approximation, is the best possible. We show how to apply our framework to problems with additive and submodular objective functions such as the capacitated maximum facility location problems. We consider two types of algorithms for these problems. For greedy algorithms, our framework provides a justification for preferring a certain natural greedy rule over some alternative greedy rules that have been used in similar contexts. For LP-based algorithms, we show that the natural LP relaxation for these problems is not optimal in our framework. We design a new LP relaxation and show that this LP relaxation coupled with a new randomized rounding technique is optimal in our framework.In passing, we note that our results strictly improve over previous results of Kleinberg, Papadimitriou and Raghavan [JACM 2004] concerning the approximation ratio of the greedy algorithm.
Old resolution meets modern SLS
Authors: Anbulagan Anbulagan, Duc Nghia Pham, John Slaney, Abdul Sattar
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

Recent work on Stochastic Local Search (SLS) for the SAT and CSP domains has shown the importance of a dynamic (non-markovian) strategy for weighting clauses in order to escape from local minima. In this paper, we improve the performance of two best contemprorary clause weighting solvers, PAWS and SAPS, by integrating a propositional resolution procedure. We also extend the work to AdaptNovelty+, the best non-weighting SLS solver in the GSAT/WalkSAT series. One outcome is that our systems can solve some highly structured problems such as quasigroup existence and parity learning problems which were previously thought unsuitable for local search and which are completely out of reach of traditional solvers such as GSAT. Here we present empirical results showing that for a range of random and real-world benchmark problems, resolution-enhanced SLS solvers clearly outperform the alternatives.
Identification and Validation of Spatio-Temporal Associations in Wireless Sensor Networks
Authors: Bakhtiar Qutub Ali, Niki Pissinou, Kia Makki
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

Wireless sensor networks (WSN) consist of largenumbers of sensor nodes embedded in physical space for continuously sensing/monitoring a specified physical phenomenon. Typically, WSN requires spatially dense sensor deployment to satisfactorily respond to the requirements of the application. The spatial proximity of nodes and the temporal behaviour of the sensing operation causes the observations sensed to be associated spatio-temporally. However, due to unfavourable environmental conditions and low energy resources available in WSN, there are instances when the nodes lie with in the same spatial space and measure the same attribute yet the observations sensed bythem are not related. No mechanism is present that identifies the degree of association or disassociation between them.In this paper we propose a methodology that uses conceptsfrom computational geometry to identify and isolate relevantspatially related subsets from a given universal set of nodes in WSN, and validate the existence of spatio-temporal associations among the observations sensed by them. The node identification process is achieved by employing classical object intersection solutions from computational geometry and the validation process is achieved by using similarity verification methods. By means of simulations on real time data we demonstrate the procedure for identification and validation by using Jaccard’s coefficient, Cosine similarity and Pearson product correlation coefficient.