ppxscal/embedding_network huggingface dataset:
Incorporating Data from Multiple Sensors for Localizing Nodes in Mobile Ad Hoc Networks
Authors: Rui Huang, Gergely V. Zaruba
Venue: IEEE Transactions on Mobile Computing (2007)

The ad hoc network localization problem deals with estimating the geographical location of all nodes in an ad hoc network focusing on those nodes that do not have a direct way (e.g., GPS) to determine their own location. Proposed solutions to the ad hoc localization problem assume that nodes are capable of measuring received signal strength (RSSI) and/or are able to do coarse (sectoring) or fine signal angle of arrival (AoA) measurements. Existing algorithms exploit different aspects of such sensory data to provide either better localization accuracy or higher localization coverage. However, there is a need for a framework that could benefit from the interactions of nodes with mixed types of sensors. In this paper, we study the behavior of RSSI and AoA sensory data in the context of the ad hoc localization problem using both geometric analysis and computer simulations. We show which type of sensor is better suited for what type of network scenario. We study how nodes using either, both, or none of these sensors could coexist in the same localization framework. We then provide a general particle filtering framework, the first of its kind, that allows heterogeneity in the types of sensory data to solve the localization problem. We show that when compared to localization scenarios where only one type of sensor is used, our framework provides significantly better localization results. Furthermore, our framework not only provides a location estimate for each non-anchor, but it also provides an implicit confidence measure as to how accurate this estimate is. This confidence measure enables nodes to further improve on their location estimates using a local, iterative one-hop simple message exchange without having to rely on synchronized multi-phase operations like in traditional multilateration methods.
A Novel Approach for Filtered Backprojection in Tomosynthesis Based on Filter Kernels Determined by Iterative Reconstruction Techniques
Authors: Jasmina Ludwig, Thomas Mertelmeier, Holger Kunze, Wolfgang Härer
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

Breast tomosynthesis is a new 3D imaging technique providing 3D slices of the breast. The computation of 3D slices from a set of 2D projections is performed with a reconstruction algorithm --- either a filtered backprojection (FBP) or an algebraic iterative reconstruction method. Both approaches yield different image characteristics of the reconstructed object. The algebraic method has the main disadvantage of a very long processing time. We experimentally developed a set of filter kernels for FBP, determined by iterative reconstruction providing similar image characteristics and quality as an algebraic reconstruction. Additionally we showed that it is possible to approximate these kernels by a polynomial function of order 4. Using clinical data sets we demonstrate how the image quality and the image impression can be varied by using different reconstruction methods.
Directed and motivated attention during processing of natural scenes
Authors: Vera Ferrari, Maurizio Codispoti, Rossella Cardinale, Margaret M. Bradley
Venue: Journal of Cognitive Neuroscience (2008)

Visual attention can be voluntarily oriented to detect target stimuli in order to facilitate goal-directed behaviors. Other visual stimuli capture attention because of motivational significance. The aim of the present study was to investigate the relationship between directed and motivated attention using event-related potentials. Affectively engaging pictures were presented either as target stimuli or as nontargets in a categorization task. Results indicated that both task relevance and emotional significance modulated the late positive potential (LPP) over centro-parietal sensors. Effects of directed and motivated attention on the LPP were additive, with the largest centro-parietal positivity found for emotional pictures that were targets of directed attention, and the least for neutral pictures that were nontargets. Taken together, the data provide new information regarding the relationship between motivated and directed attention, and suggest that the LPP reflects the operation of attentional neural circuits that are utilized by both top-down and bottom-up processes.
Analysis of FEC Function for Real-Time DV Streaming
Authors: Kazuhisa Matsuzono, Hitoshi Asaeda, Kazunori Sugiura, Osamu Nakamura, Jun Murai
Venue: Proceedings of the 3rd Asian conference on Internet Engineering: Sustainable Internet (2007)

Due to the dissemination of high speed DSL and FTTH, real-time streaming applications transmitting high quality audio and video data have been commonly used on the Internet. These applications usually have strict requirements on delay and packet loss. However, it is difficult to fully satisfy the requirements in general, since the end users cannot guarantee the streaming quality on the best-effort Internet. In this paper, we investigate an FEC (Forward Error Correction) function on DV streaming. We study the relation between network bandwidth and FEC recovery rate upon data transmission, and the receiver's play quality and FEC calculation cost. Our experimental results given on top of our testbed network show that the FEC function can provide the best possible streaming quality, without leading the further disruption of video and audio irrespective of the available network bandwidth.
Taking Lessons from Teleconference to Improve Same Time, Same Place Interaction
Authors: Bridget Kane, Saturnino Luz
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Performance on an information gathering task is shown to be superior in teleconference. Analysis of errors in an exercise revealed the data sources used in co-located and teleconference scenarios. The use of a visual display for text data, in addition to the audio source, is demonstrated in both co-located and teleconference discussions. Audio was used as a source of information more frequently in teleconference which resulted in an overall improvement in task performance. The lesson learned from the higher performance in teleconference, can be applied to improve performance at co-located meetings. Providing appropriate visual data together within audio enhanced spaces can be expected to improve the communication event and reduce medical errors. Results support proposals for the incorporation of physical spaces to improve communication in everyday work in co-operative workplaces, such as hospitals.
Using Matrix Model to Find Association Rule Core for Diverse Compound Critiques
Authors: Li Yu
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

Dynamic critiquing approach is capable of automatically identifying useful compound critiques during each recommendation cycle, relative to the remaining cases. In current method, it is often too similar compound critiques are produced and presented to user. They limit the scope of the feedback options for the user. In this paper, a novel rule matrix model is proposed to find minimal association rule core for enhancing diverse compound critiques. All association rules generated though a frequent itemset are shown in elements of rule matrix, and minimal association rule core can be quickly determined though base elements in matrix. Association rule core is used to produce dynamic compound critiques. An example given better illustrates our method.
Schema-Guided Induction of Monadic Queries
Authors: Jérôme Champavère, Rémi Gilleron, Aurélien Lemay, Joachim Niehren
Venue: Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications (2008)

The induction of monadic node selecting queries from partially annotated XML-trees is a key task in Web information extraction. We show how to integrate schema guidance into an RPNI-based learning algorithm, in which monadic queries are represented by pruning node selecting tree transducers. We present experimental results on schema guidance by the DTD of HTML.
Estimates of Data Complexity in Neural-Network Learning
Authors: Věra Kůrková
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

Complexity of data with respect to a particular class of neural networks is studied. Data complexity is measured by the magnitude of a certain norm of either the regression function induced by a probability measure describing the data or a function interpolating a sample of input/output pairs of training data chosen with respect to this probability. The norm is tailored to a type of computational units in the network class. It is shown that for data for which this norm is "small", convergence of infima of error functionals over networks with increasing number of hidden units to the global minima is relatively fast. Thus for such data, networks with a reasonable model complexity can achieve good performance during learning. For perceptron networks, the relationship between data complexity, data dimensionality and smoothness is investigated.
Haskell, do you read me?: constructing and composing efficient top-down parsers at runtime
Authors: Marcos Viera, S. Doaitse Swierstra, Eelco Lempsink
Venue: ACM SIGPLAN Notices (2009)

The Haskell definition and implementation of read is far from perfect. In the first place read is not able to handle the associativities defined for infix operators. Furthermore, it puts constraints on the way show is defined, and especially forces it to generate far more parentheses than expected. Lastly, it may give rise to exponential parsing times. All this is due to the compositionality requirement for read functions, which imposes a top-down parsing strategy. We propose a different approach, based on typed abstract syntax, in which grammars describing the data types are composed dynamically. Using the transformation libraries described in a companion paper these syntax descriptions are combined and transformed into parsers at runtime, from which the required read function are constructed. In this way we obtain linear parsing times, achieve consistency with the defined associativities, and may use a version of show which generates far fewer parentheses, thus improving readability of printed values. The described transformation algorithms can be incorporated in a Haskell compiler, thus moving most of the work involved to compile time.
A Hybrid Clustering Algorithm Based on Multi-swarm Constriction PSO and GRASP
Authors: Yannis Marinakis, Magdalene Marinaki, Nikolaos Matsatsinis
Venue: Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery (2008)

This paper presents a new hybrid algorithm, which is based on the concepts of Particle Swarm Optimization (PSO) and Greedy Randomized Adaptive Search Procedure (GRASP), for optimally clustering N objects into K clusters. The proposed algorithm is a two phase algorithm which combines a Multi-Swarm Constriction Particle Swarm Optimization algorithm for the solution of the feature selection problem and a GRASP algorithm for the solution of the clustering problem. In this paper in PSO, multiple swarms are used in order to give to the algorithm more exploration and exploitation abilities as the different swarms have the possibility to explore different parts of the solution space and, also, a constriction factor is used for controlling the behaviour of particles in each swarm. The performance of the algorithm is compared with other popular metaheuristic methods like classic genetic algorithms, tabu search, GRASP, ant colony optimization and particle swarm optimization. In order to assess the efficacy of the proposed algorithm, this methodology is evaluated on datasets from the UCI Machine Learning Repository. The high performance of the proposed algorithm is achieved as the algorithm gives very good results and in some instances the percentage of the corrected clustered samples is very high and is larger than 98%.
Emergent Narrative as a Novel Framework for Massively Collaborative Authoring
Authors: Michael Kriegel, Ruth Aylett
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

An emergent narrative is a narrative that is dynamically created through the interactions of autonomous intelligent virtual agents and the user. Authoring in such a system means programming characters rather than defining plot and can be a technically and conceptually challenging task. We are currently implementing a tool that helps the author in this task by training the characters through demonstration of example story lines (rehearsals), rather then explicit programming. In this paper we argue that this tool is best used by a group of authors, each providing an example story and that in order to achieve true emergence, collective authoring is required. We compare the rehearsal based authoring method of our authoring tool with other collaborative authoring efforts and underline why both the storytelling medium "emergent narrative" and our particular approach to authoring are better suited for massively collaborative authoring.
A Demonstration of Clustering in Protein Contact Maps for Alpha Helix Pairs
Authors: Robert Fraser, Janice Glasgow
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

The purpose of this work is to demonstrate that it is possible to cluster contact maps for pairs of alpha helices such that each of the clusters corresponds to a group of pairs of alpha helices with similar properties. The property of the configuration of helix pairs that was chosen for study is the packing attribute. The contact maps are compared to one another using a novel contact map comparison scheme based upon the locations of contacts in the contact maps. A k-nearest neighbours technique is used to perform the clustering, and the cosine between vectors corresponding to contact map regions was the distance metric. The clustering of contact maps to determine whether maps corresponding to similar packing values are placed into the same clusters yielded promising results.
Planar inverted -F antenna for wireless applications
Authors: S. Raghavan, N. Jayanthi
Venue: Proceedings of the 7th WSEAS International Conference on Instrumentation, Measurement, Circuits and Systems (2008)

The design of single feed dual band PIFA operating at 2.25 and 3.546 GHz is presented. Two dimensional method of moments (MOM) electromagnetic simulator, IE3D version: 12, is used in the design simulation of this dual band antenna. The result exhibit a proper operation of the antenna in terms of return loss, bandwidth, efficiency, gain at both bands. ISM, Bluetooth, Wi-max, IEEE 802.11b, 802.11g, 802.11n, 802.16e, WiFi, Wi-max are the most important applications within the above mentioned frequency bands.
Robust Speaker Identification for Meetings: UPC CLEAR'07 Meeting Room Evaluation System
Authors: Jordi Luque, Javier Hernando
Venue: Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers (2008)

In this paper, the authors describe the UPC speaker identification system submitted to the CLEAR'07 (Classification of Events, Activities and Relationships) evaluation. Firstly, the UPC single distant microphone identification system is described. Then the use of combined microphone inputs in two different approaches is also considered. The first approach combines signals from several microphones to obtain a single enhanced signal by means a delay and sum algorithm. The second one fuses the decision of several single distant microphone systems. In our experiments, the latter approach has provided the best results for this task.
Robustification of Microdata Masking Methods and the Comparison with Existing Methods
Authors: Matthias Templ, Bernhard Meindl
Venue: Proceedings of the UNESCO Chair in data privacy international conference on Privacy in Statistical Databases (2008)

The aim of this study was to compare different microdata protection methods for numerical variables under various conditions. Most of the methods used in this paper have been implemented in the R-package sdcMicro which is available for free on the comprehensive R archive network ( http://cran.r-project.org ). The other methods used can be easily applied using other R-packages. While most methods work well for homogeneous data sets, some methods fail completely when confidential variables contain outliers which is almost always the case with data from official statistics. To overcome these problems we have robustified popular methods such as microaggregation or shuffling which is based on a regression model. All methods have beed tested on bivariate data sets featuring different outlier scenarios. Additionally, a simulation study was performed.
PAS: A Wireless-Enabled, Cell-Phone-Incorporated Personal Assistant System for Independent and Assisted Living
Authors: Zheng Zeng, Sammy Yu, Wook Shin, Jennifer C. Hou
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Advances in networking, sensors, medical devices and smart phones have made it feasible to monitor and provide medical and other assistance to people either in their homes or outside. Aging populations will benefit from reduced costs and improved healthcare through assisted living based on these technologies. However, these systems challenge current state-of-the-art techniques for usability, reliability, and security. In this paper we present the PAS open architecture for assisted living, which allows independently developed third party components to collaborate. Furthermore, we incorporate cell phones in PAS as the local intelligence in order to enhance the robustness and ubiquity. We discuss key technological issues in assisted living systems, such as software architecture layout, power preserving, security and privacy; and results from our pilot study in a real assisted living facility are presented.
Using Hierarchical Task Network Planning Techniques to Create Custom Web Search Services over Multiple Biomedical Databases
Authors: Miguel García-Remesal
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

We present a novel method to create complex search services over public online biomedical databases using hierarchical task network planning techniques. In the proposed approach, user queries are regarded as planning tasks (goals), while basic query services provided by the databases correspond to planning operators (POs). Each individual source is then mapped to a set of POs that can be used to process primitive (simple) queries. Advanced search services can be created by defining decomposition methods (DMs). The latter can be regarded as "recipes" that describe how to decompose non-primitive (complex) queries into sets of simpler subqueries following a divide-and-conquer strategy. Query processing proceeds by recursively decomposing non-primitive queries into smaller queries, until primitive queries are reached that can be processed using planning operators. Custom web search services can be created from the generated planners to provide biomedical researchers with valuable tools to process frequent complex queries.
Efficient Routing Scheme Using Pivot Node in Wireless Sensor Networks
Authors: Jung-Seok Lee, Jung-Pil Ryu, Ki-Jun Han
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

We propose an efficient routing for wireless sensor networks, called pivot routing. Pivot routing establishes the data paths while query is propagated. Source node selects a data path and transmits data packets to the sink via pivot nodes. Because subsequent query and data packets are transmitted along pivot nodes, control message overhead decreases considerably. Network lifetime also increases since the energy consumption of communication is reduced at sensor node. Simulation results show good aspects of control overhead and network lifetime.
Developing Value Framework of Ubiquitous Computing
Authors: Jungwoo Lee, Younghee Lee, Jaesung Park
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

In this study, a value framework for ubiquitous computing is developed and presented. Using `value focused thinking' approach suggested by Keeney, twenty-two potential users of ubiquitous computing were interviewed and 435 statements describing values expected from ubiquitous technology were obtained from these interviews. Subsequent purification and redundancy removal reduces these 435 statements into 166 objectives that these users have in their mind when thinking about ubiquitous computing. These 166 objectives were factorized into 35 objectives through clustering by three experts. These 35 objectives were classified into a means-ends network diagram by analyzing reciprocal relationships among them in a focus group activity of another three experts. Resulting means-ends network reveals a value framework inherent in users' perception about ubiquitous computing technologies. This framework will be useful as a reference in developing new business models for ubiquitous computing as well as developing useful technologies themselves.
Some lessons learned in conducting software engineering surveys in china
Authors: Junzhong Ji, Jingyue Li, Reidar Conradi, Chunnian Liu, Jianqiang Ma, Weibing Chen
Venue: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (2008)

Component-Based Software Engineering (CBSE) with Open Source Software and Commercial-Off-the-Shelf (COTS) components, Open Source Software (OSS) based development, and Software Outsourcing (SO) are becoming increasingly important for the Chinese software industry. It is therefore necessary to establish pragmatic and possibly nation-specific guidelines for Chinese software companies regarding the use of CBSE, OSS, and SO. Such guidelines should be based on insights from actual practice, which are in our case, obtained through surveys. A European state-of-the-practice survey on COTS- and OSS-oriented CBSE was conducted in Germany, Italy, and Norway in 2004-2005. We repeated similar surveys in China, with an extended survey on OSS and SO. We encountered many difficulties in conducting the surveys, but in most cases managed to find working solutions. We report on the lessons learned while conducting these surveys. In particular, we address issues relating to sampling, contacting respondents, data collection, and data validation. The main lessons are: 1) it was necessary to cooperate with a third-party organization with close relations to Chinese software companies; 2) it was necessary to assign researchers to this third-party organization to facilitate data collection and to control the quality of the data collected; and 3) an email survey, after an initial telephone call to establish contact, was the best method for getting questionnaires completed by Chinese respondents.
Multi-dimensional option pricing using radial basis functions and the generalized Fourier transform
Authors: Elisabeth Larsson, Krister hlander, Andreas Hall
Venue: Journal of Computational and Applied Mathematics (2008)

We show that the generalized Fourier transform can be used for reducing the computational cost and memory requirements of radial basis function methods for multi-dimensional option pricing. We derive a general algorithm, including a transformation of the Black-Scholes equation into the heat equation, that can be used in any number of dimensions. Numerical experiments in two and three dimensions show that the gain is substantial even for small problem sizes. Furthermore, the gain increases with the number of dimensions.