ppxscal/embedding_network huggingface dataset:
Constrained Power Control to Enhance the Capacity of Slotted DS-CDMA Cellular Systems
Authors: Chin Choy Chai, Kainan Zhou, Yong Huat Chew, Ke Li
Venue: Wireless Personal Communications: An International Journal (2009)

We propose and study the constrained power control scheme for direct sequence code division multiple access (DS-CDMA) systems supporting voice and data services. In the proposed scheme, the voice users are subject to the conventional power control, while the data users are subject to distance dependent transmit power constraint. Several power control profiles for data users are suggested to reduce interference within its own and neighboring cells. For given delay and outage probability requirements, we present an analytical framework to analyze the number of users that can be supported by the proposed scheme. The results are compared to the conventional power control scheme, where no such constraint is imposed. We derive new closed form expression for the interference correction factor for the constrained power control scheme. In addition, we show that the total interference power can be approximated by the log-normal distribution, and we evaluate the mean and variance of the log-normal distribution analytically. We also derive the distribution of the signal-to-noise ratios for voice and data users, which is useful in evaluating the user capacity for slotted DS-CDMA cellular systems with both delay and power constraints.
An Automata-based Approach for CTL*; With Constraints
Authors: Régis Gascon
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

We introduce a general definition for a family of branching-time logics that extend CTL* by allowing constraints between variables at the atomic level. These constraints allow to compare values of variables at different states of the model. We define an automata-theoretic approach to solve verification problems for such extensions. Our method is based on a finite abstraction of the infinite state space and a symbolic representation of the models that generalizes several approaches used for extensions of the linear-time logic LTL with constraints. We extend and combine several constructions involving alternating tree automata. We apply this approach to prove decidability and optimal complexity results for particular instances of CTL* extensions whenever an abstraction of the models verifying a ''nice'' property can be computed. These theoretical results generalize several results on LTL with constraints where such nice abstractions are used.
Model-driven development of composite context-aware web applications
Authors: Georgia M. Kapitsaki, Dimitrios A. Kateros, George N. Prezerakos, Iakovos S. Venieris
Venue: Information and Software Technology (2009)

Context-awareness constitutes an essential aspect of services, especially when interaction with end-users is involved. In this paper a solution for the context-aware development of web applications consisting of web services is presented. The methodology proposes a model based approach and advocates in favour of a complete separation of the web application functionality from the context adaptation at all development phases (analysis, design, implementation). In essence, context adaptation takes place on top of and is transparent to the web application business functionality. Starting from UML diagrams of independent web services and respective UML context models, our approach can produce a functional composite context-aware application. At execution level this independence is maintained through an adaptation framework based on message interception.
Collaboration in Opportunistic Networks
Authors: Andreas Heinemann
Venue:  (2007)

With the increasing integration of wireless short-range communication technologies in mobile devices, novel applications for spontaneous communication, interaction and collaboration are possible. In this book, we distinguish between active and passive collaboration. The devices help users become aware of each other and stimulate face-to-face conversation (active collaboration). Also, autonomous device communication for sharing information without user interaction is possible, i.e., devices pass information to other devices in their vicinity (passive collaboration). Spontaneous communication of mobile devices leads to so-called opportunistic networks, a new and promising evolution in mobile ad-hoc networking. They are formed by mobile devices which communicate with each other while users are in close proximity. This book investigates opportunistic networks in their entirety. The proposed concepts comprise system components, a node architecture, a system model and a simple one-hop communication paradigm for opportunistic network applications. One focus of this book is a profile-based data dissemination mechanism. Readers of this book would include graduate students and postgraduate researchers in both academia and industry, who wish to gain a deeper knowledge of opportunistic networks, its underlying idea and its potential capabilities. 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
Speeding up spatial approximation search in metric spaces
Authors: Karina Figueroa, Edgar Chavez, Gonzalo Navarro, Rodrigo Paredes
Venue: Journal of Experimental Algorithmics (JEA) (2009)

Proximity searching consists of retrieving from a database those elements that are similar to a query object. The usual model for proximity searching is a metric space where the distance, which models the proximity, is expensive to compute. An index uses precomputed distances to speedup query processing. Among all the known indices, the baseline for performance for about 20 years has been AESA. This index uses an iterative procedure, where at each iteration it first chooses the next promising element (&ldquo;pivot&rdquo;) to compare to the query, and then it discards database elements that can be proved not relevant to the query using the pivot. The next pivot in AESA is chosen as the one minimizing the sum of lower bounds to the distance to the query proved by previous pivots. In this article, we introduce the new index iAESA, which establishes a new performance baseline for metric space searching. The difference with AESA is the method to select the next pivot. In iAESA, each candidate sorts previous pivots by closeness to it, and chooses the next pivot as the candidate whose order is most similar to that of the query. We also propose a modification to AESA-like algorithms to turn them into probabilistic algorithms. Our empirical results confirm a consistent improvement in query performance. For example, we perform as few as 60&percnt; of the distance evaluations of AESA in a database of documents, a very important and difficult real-life instance of the problem. For the probabilistic algorithm, we perform in a database of faces up to 40&percnt; of the comparisons made by the best alternative algorithm to retrieve the same percentage of the correct answer. Based on the empirical results, we conjecture that the new probabilistic AESA-like algorithms will become, as AESA had been for exact algorithms, a reference point establishing, in practice, a lower bound on how good a probabilistic proximity search algorithm can be.
GO! with Word 2007, Comprehensive
Authors: Shelley Gaskin, Annette Duvall
Venue:  (2007)

The primary goal of the GO! Series, aside from teaching computer applications, is ease of implementation, with an approach that is based on clearly-defined projects for students and a one of a kind supplements package. GO!s project-based approach clusters the learning objectives around the projects rather than around software features. Teaches students to solve real problems as they practice and learn the features. Ideal for students and individuals seeking an introduction to Internet Explorer.
Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering
Authors: Rong Pan, Martin Scholz
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

One-Class Collaborative Filtering (OCCF) is a task that naturally emerges in recommender system settings. Typical characteristics include: Only positive examples can be observed, classes are highly imbalanced, and the vast majority of data points are missing. The idea of introducing weights for missing parts of a matrix has recently been shown to help in OCCF. While existing weighting approaches mitigate the first two problems above, a sparsity preserving solution that would allow to efficiently utilize data sets with e.g., hundred thousands of users and items has not yet been reported. In this paper, we study three different collaborative filtering frameworks: Low-rank matrix approximation, probabilistic latent semantic analysis, and maximum-margin matrix factorization. We propose two novel algorithms for large-scale OCCF that allow to weight the unknowns. Our experimental results demonstrate their effectiveness and efficiency on different problems, including the Netflix Prize data.
Interactivity for mobile music-making
Authors: Georg Essl, Michael Rohs
Venue: Organised Sound (2009)

Mobile phones offer an attractive platform for interactive music performance. We provide a theoretical analysis of the sensor capabilities via a design space and show concrete examples of how different sensors can facilitate interactive performance on these devices. These sensors include cameras, microphones, accelerometers, magnetometers and multitouch screens. The interactivity through sensors in turn informs aspects of live performance as well as composition though persistence, scoring, and mapping to musical notes or abstract sounds.
An Integrated Framework for Comprehensive Collaborative Emergency Management
Authors: Fonny Sujanto, Andrzej Ceglowski, Frada Burstein, Leonid Churilov
Venue: Proceeding of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges (2008)

Effective decision making plays a paramount role for successful emergency management (EM). Decisions should include collaborating inputs and feedback from a wide range of relevant emergency stakeholders such as emergency agencies, government, experts and communities. Although this kind of collaborative decision making is ideal, the process can be lengthy and complex. While there has been substantial research in EM, there is a lack of integrated frameworks to structure these contributions. Without an integrated framework, the decision making process can be inefficient and suggestions of the stakeholders may be neglected or excluded inadvertently. This paper presents the “Integrated Framework for Comprehensive Collaborative Emergency Management” (IFCCEM). IFCCEM aims to provide a collaborative mechanism so that all agencies as well as communities can contribute in the decision making. IFCCEM is based on the 'All Hazards Approach' and can be used by all agencies. The developed framework is illustrated with an application for collaborative decision making.
Neural models predicting traction power consumption: support of e-energy telematic systems
Authors: Jindrich Sadil
Venue: Proceedings of the 2009 Euro American Conference on Telematics and Information Systems: New Opportunities to increase Digital Citizenship (2009)

This paper deals with determination of relevant input data for models predicting electric traction power consumption. Furthermore, it deals with developing such models, which combine knowledge of classical physics with methods of artificial neural networks. It is possible to design control processes of railway traction effectively, based on these models. Real data of electric power consumption of traction substations in the Czech Republic within one year of train diagram 2006/2007 validity are used for verification of the models. These models can build support for e-energy telematic systems.
The Effects of a Pedagogical Agent in an Open Learning Environment
Authors: Geraldine Clarebout, Jan Elen
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

Multiple studies have reported beneficial effects of embedding pedagogical agents in learning environments [1]. Most of these studies relate to effects in well-structured learning environments. In contrast, this contribution investigates the effects of pedagogical agents in open learning environments. A group that receives advice from a pedagogical agent is compared to a no-agent group. Dependent variables were performance, score on a transfer test and the use of tools. While groups did not differ on the performance test, rather surprisingly, the no-agent group outperformed the agent group on the transfer test. The no-agent group also spends significantly more time on the information list than the agent group. Results suggest that the pedagogical agent made the environment even more complex, causing additional cognitive load for the participants.
Dynamic routing using the network of car drivers
Authors: Leon J. M. Rothkrantz
Venue: Proceedings of the 2009 Euro American Conference on Telematics and Information Systems: New Opportunities to increase Digital Citizenship (2009)

Since 1995 there is a project called "SmartRoad" running at TUDelft. The goal of the project is to design ICT solutions for traffic control and warning systems. In this paper we focus on dynamic routing systems. New in this project is that car drivers communicate with each other via an intelligent system implemented on the network of lamppost. By tracking individual car drivers the system gets real time information of traffic speed along the roads. Next a dynamic routing algorithm has been designed, which uses the dynamic traffic speed along road segments. The Ant Based Control (ABC-) routing algorithm is based on ideas from artificial life and computes the shortest traveling time from start to destination. A simulation environment has been implemented and experimental results of static and dynamic routing will be presented in this paper.
Enlargement of Measurement Range in a Fiber-Optic Ice Sensor by Artificial Neural Network
Authors: Wei Li, Jie Zhang, Ying Zheng, Lin Ye
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Artificial neural network (ANN) isemployed to present a fiber-optic ice sensor (FOIS) with wide measurement range. Comparing with existing FOIS signal processing methods, this approach is not limited by the double-valued problem of output curve. Instead, it performs a measurement range from front-slope areas to back-slope areas. Moreover, this approach also handles the nonlinear problem of the sensor. As an application of the ANN, a calibration experiment platform is set up. The training samples are employed to train the ANN, and the testing samples are applied to surveil the predict ability of the ANN. The results obtained demonstrate the applicability of the proposed approach.
Using Systematic Animation to Teach Dynamic Science Concepts
Authors: Talib Othman, Christirani Azhar Shah, Nabila Abdullah
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

It is argued that such animations should gradually facilitate students' comprehension in stages before they could construct complete mental model of the concepts being explained. Subjects were randomly assigned to an experimental group (N=45) and a control group (N=40). The experimental group received lessons through teacher's explanation using systematic step-by-step animation whilst the control group received lessons primarily based on teacher's explanation using prepared transparencies. The pre-test and post-test analyses revealed that students in the experimental group demonstrated better conceptual understanding compared to those in the control group, thus showing evidence of their stronger conceptual understanding in comparison to the students in the control group.
Crack reconstruction using a level-set strategy
Authors: Diego Álvarez, Oliver Dorn, Natalia Irishina, Miguel Moscoso
Venue: Journal of Computational Physics (2009)

We present a level-set based technique to recover key characteristics of a defect or crack (e.g. location, length and shape) in a two-dimensional material from boundary electrical measurements. The key feature of this work is to extend the usual level-set technique for modeling volumetric objects to very thin objects. Two level-set functions are employed: the first one models the location and form of the crack, and the second one models its length and connectivity. An efficient gradient based method is derived in order to define evolution laws for these two level-set functions which minimize the least squares data misfit. Numerical experiments show the utility of this method even in the presence of a significant noise level in the measurements. A finite element method is used to simulate the electric field behavior in the presence of very thin objects.
A Non-oscillatory Advection Operator for the Compatible Spectral Element Method
Authors: M. A. Taylor, A. St. Cyr, A. Fournier
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

The spectral element method is well known as an efficient way to obtain high-order numerical solutions on unstructured finite element grids. However, the oscillatory nature of the method's advection operator makes it unsuitable for many applications. One popular way to address this problem is with high-order discontinuous-Galerkin methods. In this work, an alternative solution which fits within the continuous Galerkin formulation of the spectral element method is proposed. Making use of a compatible formulation of spectral elements, a natural way to implement conservative non-oscillatory reconstructions for spectral element advection is shown. The reconstructions are local to the element and thus preserve the parallel efficiency of the method. Numerical results from a low-order quasi-monotone reconstruction and a higher-order sign-preserving reconstruction are presented.
Biometrics Method for Human Identification Using Electrocardiogram
Authors: Yogendra Narain Singh, P. Gupta
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

This work exploits the feasibility of physiological signal electrocardiogram (ECG) to aid in human identification. Signal processing methods for analysis of ECG are discussed. Using ECG signal as biometrics, a total of 19 features based on time interval, amplitudes and angles between clinically dominant fiducials are extracted from each heartbeat. A test set of 250 ECG recordings prepared from 50 subjects ECG from Physionet are evaluated on proposed identification system, designed on template matching and adaptive thresholding. The matching decisions are evaluated on the basis of correlation between features. As a result, encouraging performance is obtained, for instance, the achieved equal error rate is smaller than 1.01 and the accuracy of the system is 99%.
Effective Communications for Project Management, 1st edition
Authors: Ralph L. Kliem
Venue:  (2007)

This book examines elements of the communications process and describes the role that the Project Management Information System (PMIS) has in helping project managers become better communicators. In addition to describing how personality effects communications, the book details the seven elements of effective communications: applying active and effective listening; preparing the communications and establishing an issues management process; drafting and publishing documentation; conducting meetings; giving effective presentations; developing and deploying a project website; and building a project war room. Each chapter contains examples and checklists that can be adapted to each readers environment. 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
On Counting 3-D Matchings of Size k
Authors: Yunlong Liu, Jianer Chen, Jianxin Wang
Venue: Algorithmica (2009)

The computational complexity of counting the number of matchings of size k in a given triple set has been open. It is conjectured that the problem is not fixed parameter tractable. In this paper, we present a fixed parameter tractable randomized approximation scheme (FPTRAS) for the problem. More precisely, we develop a randomized algorithm that, on given positive real numbers &#x03b5; and &#x03b4;, and a given set S of n triples and an integer k, produces a number h in time O(5.483k n 2ln&#x2009;(2/&#x03b4;)/&#x03b5; 2) such that $$\mathop{\mathrm{Prob}}[(1-\epsilon)h_{0}\leq h\leq(1+\epsilon)h_{0}]\geq1-\delta,$$ where h 0 is the total number of matchings of size k in the triple set S. Our algorithm is based on the recent improved color-coding techniques and the Monte-Carlo self-adjusting coverage algorithm developed by Karp, Luby and Madras.
On the usefulness of supervised learning for vessel border detection in IntraVascular Imaging
Authors: Aura Hernàndez, Debora Gil, Petia Radeva
Venue: Proceeding of the 2005 conference on Artificial Intelligence Research and Development (2005)

IntraVascular UltraSound (IVUS) imaging is a useful tool in diagnosis of cardiac diseases since sequences completely show the morphology of coronary vessels. Vessel borders detection, especially the external adventitia layer, plays a central role in morphological measures and, thus, their segmentation feeds development of medical imaging techniques. Deterministic approaches fail to yield optimal results due to the large amount of IVUS artifacts and vessel borders descriptors. We propose using classification techniques to learn the set of descriptors and parameters that best detect vessel borders. Statistical hypothesis test on the error between automated detections and manually traced borders by 4 experts show that our detections keep within inter-observer variability.
Dynamic Texture Based Gait Recognition
Authors: Vili Kellokumpu, Guoying Zhao, Stan Z. Li, Matti Pietikäinen
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

We present a novel approach for human gait recognition that inherently combines appearance and motion. Dynamic texture descriptors, Local Binary Patterns from Three Orthogonal Planes (LBP-TOP), are used to describe human gait in a spatiotemporal way. We also propose a new coding of multiresolution uniform Local Binary Patterns and use it in the construction of spatiotemporal LBP histograms. We show the suitability of the representation for gait recognition and test our method on a popular CMU MoBo dataset. We then compare our result to the state of the art methods.