ppxscal/embedding_network huggingface dataset:
A simulation methodology in modeling cell divisions with stochastic effects
Authors: Harsha K. Rajasimha, David C. Samuels, Richard E. Nance
Venue: Proceedings of the 36th conference on Winter simulation (2004)

We present a model to explain the effects of the long time between blood stem cell divisions and rapid cascades of progenitor cell divisions on the mitochondrial DNA drift. We allow four stochastic events in the system namely, mtDNA replication and degradation, cell division and death. To implement the conceptual model, we design two simulation models; one for a limited number of stem cells (20,000) over very long time scale (100 years) and another for the cell divisions of a progenitor cell resulting in a large number of blood cells (~10 million) over a shorter time span (25 days). Iterative enhancement with incremental builds constitutes the modeling methodology. We adopt the activity scanning conceptual framework for the model implementation. Initial transient and memory issues are resolved. By output data analysis, we conclude that the variation in mutation level occurs significantly due to time and less so due to cell divisions.
Oasis: A Mapping and Integration Framework for Biomedical Ontologies
Authors: Guanglei Song, Yu Qian, Ying Liu, Kang Zhang
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

More and more ontologies are emerging across bioinformatics domains to represent and define domain knowledge, such as gene ontology, anatomy ontology and disease ontology. To integrate these heterogeneous ontologies is becoming critically important for applications utilizing multiple ontologies. Because the entities described in the ontology often overlap with other entities in other ontologies, a mapping between two corresponding terms is required and becoming the key to the integration of heterogeneous ontologies. Based on a previously developed schema matching algorithm, this paper presents a framework for mapping and integration of heterogeneous biomedical ontologies. The framework detects possible false mappings intelligently and provides intuitive interfaces for users to customize mappings and for applications to integrate and access biomedical ontologies.
Web-Service Based Information Integration for e-Financial Planning System Matchmaking Decision Support
Authors: Kelvin K. K. Lee, Dickson K. W. Chiu, Patrick C. K. Hung
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

Gathering and using information extracted and integrated from heterogeneous source for decision making is not an easy task, especially for the decisions of investment or selection of insurance, which are the two main components of financial planning. Well organized financial planning is significant to achieve their various life goals and quality after retiring. However, most people have inadequate investment knowledge to choose suitable investment tools for them. In this paper, we present a conceptual model to formalize such financial requirements and solutions under risk as well as our implementation based on Web services, which are essential for an effective Electronic Financial Planning System (EFPS). This helps increase the quality of the consultation and decision support and lower the service costs due to process improvements.
Bilayer Segmentation of Live Video
Authors: A. Criminisi, G. Cross, A. Blake, V. Kolmogorov
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

This paper presents an algorithm capable of real-time separation of foreground from background in monocular video sequences. Automatic segmentation of layers from colour/contrast or from motion alone is known to be error-prone. Here motion, colour and contrast cues are probabilistically fused together with spatial and temporal priors to infer layers accurately and efficiently. Central to our algorithm is the fact that pixel velocities are not needed, thus removing the need for optical flow estimation, with its tendency to error and computational expense. Instead, an efficient motion vs nonmotion classifier is trained to operate directly and jointly on intensity-change and contrast. Its output is then fused with colour information. The prior on segmentation is represented by a second order, temporal, Hidden Markov Model, together with a spatial MRF favouring coherence except where contrast is high. Finally, accurate layer segmentation and explicit occlusion detection are efficiently achieved by binary graph cut. The segmentation accuracy of the proposed algorithm is quantitatively evaluated with respect to existing groundtruth data and found to be comparable to the accuracy of a state of the art stereo segmentation algorithm. Foreground/ background segmentation is demonstrated in the application of live background substitution and shown to generate convincingly good quality composite video.
NUITS: a novel user interface for efficient keyword search over databases
Authors: Shan Wang, Zhaohui Peng, Jun Zhang, Lu Qin, Sheng Wang, Jeffrey Xu Yu, Bolin Ding
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

The integration of database and information retrieval techniques provides users with a wide range of high quality services. We present a prototype system, called NUITS, for efficiently processing keyword queries on top of a relational database. Our NUITS allows users to issue simple keyword queries as well as advanced keyword queries with conditions. The efficiency of keyword query processing and the user-friendly result display will also be addressed in this paper.
Neuro-Fuzzy Fusion: A New Approach to Multiple Classifier System
Authors: Saroj K. Meher, Ashish Ghosh, B. Uma Shankar, Lorenzo Bruzzone
Venue: Proceedings of the 9th International Conference on Information Technology (2006)

Selection of a suitable classifier fusion scheme in the design of multiple classifier systems (MCSs) is a tedious task. To meet this we propose a neuro-fuzzy fusion (NFF) method for fusing the responses of a set of fuzzy classifiers. In the proposed method the output of the considered classifiers are fed to a neural network which performs the fusion task. Five labeled data sets, of which two are from remote sensing images, have been used for the performance comparison of various MCSs. Experimental study revealed the improved classification capability of the proposed NFF based MCS yielding consistently better results for all data sets.
ICONCHESS: an Interactive CONsultant for CHESS middlegames
Authors: Santos Gerardo Lazzeri, Rachelle Heller
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

Ever since Shannon [Shannon 50] published his proposal for a chess playing program, most programs have followed the brute force approach to chess, which relies on searching a large number of possible chess positions in order to produce a move that is appropriate for a given chess position. Programs that have dominated the computer chess scene through the years, such as those described in [Marsland et al. 90], rely primarily on fast search-based algorithms and/or special purpose chess hardware rather than on an intensive application of knowledge. A few systems have used a knowledge-based approach to deal with chess positions. Unfortunately, these programs [Wilkins 80], [Pitrat 77] have been able to deal only with very limited subsets of the game. The problem of teaching chess has also been rarely explored. In addition to the canned tutorials found with several commercial chess programs, the intelligent tutoring system UMRAO [Gadwal 90], and the Chessmaster's natural language advisor, while limited, are perhaps the most representative examples of the application of artificial intelligence (AI) techniques for teaching chess. Despite the limited effort in this direction, cognitive psychology research suggests the importance of different factors, such as inexact pattern recognition [De Groot 78], [Newell et al. 72], and high-level knowledge [Cooke et al. 93] which have been successfully handled by AI techniques, such as case-based reasoning (CBR) [Schank 89], and fuzzy logic in the creation of learning environments in other fields, [Schank et al. 94], [Edelson 92], [McNeill et al. 94]. ICONCHESS combines some of these techniques in a learning environment for chess middlegames.
Fighting the Semantic Gap on CBIR Systems through New Relevance Feedback Techniques
Authors: Agma J. M. Traina, Joselene Marques, Caetano Traina Jr.
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

This paper introduces two novel relevance feedback techniques that integrate a new way to implement the query center movement with a suitable weighting on the similarity function. These techniques integrated to a content-based image retrieval (CBIR) system, improves the precision of the results when using texture features up to 42%, and employing at most 5 iterations. Thus, the user satisfaction with the system is increased as our experiments demonstrated. Besides being effective, the new RF techniques are very fast as they take less than one second to reprocess the queries at each iteration. The experiments also show that with three iterations the users are satisfied with the query results, and the major gain in precision happens in the first iteration, achieving improvements of up to 30%, what lessens the user efforts and anxiety.
Fast Byzantine Consensus
Authors: Jean-Philippe Martin Lorenzo Alvisi
Venue: IEEE Transactions on Dependable and Secure Computing (2006)

We present the first protocol that reaches asynchronous Byzantine consensus in two communication steps in the common case. We prove that our protocol is optimal in terms of both number of communication steps and number of processes for two--step consensus. The protocol can be used to build a replicated state machine that requires only three communication steps per request in the common case. Further, we show a parameterized version of the protocol that is safe despite f Byzantine failures and, in the common case, guarantees two-step execution despite some number t of failures (t\le f). We show that this parameterized two-step consensus protocol is also optimal in terms of both number of communication steps and number of processes.
An ACO-based Approach to Improve C-means Clustering Algorithm
Authors: Wenliang Huang, Jin Gou, Huifeng Wu
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

This paper presents an improved C-means clustering algorithm based on ACO. The proposed method use pheromone to evaluate individual colony's iterative result. In contrast with the existing C-means clustering algorithm, method in the paper need not appoint the number and pre-centers of clusters beforehand and it updates pheromone according to the transfer process of data points among different temporary clusters so as to avoid the local optima and reduce the iterative times to find actual cluster centers. We test its convergence performance with CRM data sets from China Unicom Corp. The experimental results show feasibility of design rationale.
A constrained road-based VR navigation technique for travelling in 3D city models
Authors: Timo Ropinski, Frank Steinicke, Klaus Hinrichs
Venue: Proceedings of the 2005 international conference on Augmented tele-existence (2005)

In this paper we propose a novel navigation metaphor for the exploration of 3D city models in virtual environments. The presented metaphor supports intuitive navigation without disorientation through 3D city models in a manner similar to travelling in the real world. Based on a graph representation of the road network of a 3D city model camera paths are calculated and used to enable smooth camera motion. We will explain how smooth camera motions are computed and describe a user interface usable in both desktop-based as well as projection-based environments to specify travel destinations.
A New Token Based Protocol for Group Mutual Exclusion in Distributed Systems
Authors: Quazi Ehsanul Kabir Mamun, Hidenori Nakazato
Venue: Proceedings of the Proceedings of The Fifth International Symposium on Parallel and Distributed Computing (2006)

In this paper we present a new token based protocol for group mutual exclusion in distributed systems. The protocol uses one single token to allow multiple processes to enter the critical section for a common session. One of the significant characteristics of the protocol is - concurrency, throughput and waiting time can be regulated adjusting the time period for which a session is declared. The minimum and the maximum number of messages to enter the CS is 0 and ( n + 2) respectively where n is the total number of processes in the system. Moreover, simulation results show that the protocol, on average case, considerably reduces the number of messages per entry to the CS and also requires much lower waiting times. The maximum concurrency the protocol supports is n. The protocol also ensures no starvation in the system. Furthermore, this algorithm works out for the Extended Group Mutual Exclusion problem as well.
Modelling enterprise architectures: an approach based on linking metaphors and ontologies
Authors: Gerald R. Khoury, Simeon J. Simoff, John Debenham
Venue: Proceedings of the 2005 Australasian Ontology Workshop - Volume 58 (2005)

This paper describes a new approach to modelling enterprise architectures. By viewing enterprise models as metaphors and then linking these metaphors, in a structured way, to ontologies, we propose that unified languages can be developed to describe a wide variety of enterprise structures. This overcomes a serious shortcoming with contemporary approaches to enterprise modelling. This approach is operationalised and applied to develop a new unified modelling language that demonstrates the application of this methodology.
Non-linear system identification using Bayesian inference
Authors: K. J. Pope, P. J. W. Rayner
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

Many real world systems can only be described well by non-linear models. The analysis and use of non-linear models can be very difficult and time consuming. An attractive class of models is one whose analysis can be based directly on linear systems analysis. One such class comprises models that are linear-in-the-parameters. Such models tend to have extremely large numbers of parameters, although only a handful may be relevant for any particular data set. An algorithm is described that enables the important parameters of a model to be found. Bayesian inference is used to give a consistent framework for fitting models and selecting between competing models. Simulations are given illustrating the problems of parameter estimation and model selection.
Real Time Localization and 3D Reconstruction
Authors: E. Mouragnon, Maxime Lhuillier, M. Dhome, F. Dekeyser, P. Sayd
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

In this paper we describe a method that estimates the motion of a calibrated camera (settled on an experimental vehicle) and the tridimensional geometry of the environment. The only data used is a video input. In fact, interest points are tracked and matched between frames at video rate. Robust estimates of the camera motion are computed in real-time, key-frames are selected and permit the features 3D reconstruction. The algorithm is particularly appropriate to the reconstruction of long images sequences thanks to the introduction of a fast and local bundle adjustment method that ensures both good accuracy and consistency of the estimated camera poses along the sequence. It also largely reduces computational complexity compared to a global bundle adjustment. Experiments on real data were carried out to evaluate speed and robustness of the method for a sequence of about one kilometer long. Results are also compared to the ground truth measured with a differential GPS.
Bitrate maximizing per group equalization for DMT-based systems
Authors: Koen Vanbleu, Geert Ysebaert, Gert Cuypers, Marc Moonen
Venue: Signal Processing (2006)

In a previous paper, we proposed a bitrate maximizing design criterion for time-domain equalizers (TEQ) in DMT transceivers to shorten the channel impulse response, as needed in, e.g., ADSL receivers. The proposed criterion truly maximizes the bitrate, as it is based on an exact formulation of the subchannel SNR as a function of the TEQ taps. In this paper, we show how the BM-TEQ design can be used in a bitrate maximizing per group equalizer (BM-PGEQ): the active tones are divided into groups and each group is provided with a bitrate maximizing equalizer. This BM-PGEQ design allows for a trade-off between memory requirement and performance, keeping computational complexity during data transmission roughly at the same level. It encompasses the BM-TEQ design and the so-called per tone equalization scheme (PTEQ) as extreme cases. We also present an adaptation algorithm to design the BM-TEQ and BM-PGEQ. Through simulation, we show that the BM-PGEQ scheme outperforms an earlier presented tone grouping scheme where the whole tone group was assigned the PTEQ of the group center tone. The BM-PGEQ scheme appears as a useful intermediate between BM-TEQ and PTEQ and closely approaches the PTEQ performance for as few as four tone groups in an ADSL scenario, even in harsh environments with narrowband interference and crosstalk.
Energy consumption trade-offs in power constrained networks
Authors: Katia Obraczka
Venue:  (2006)

The main goal of this work is to understand the energy consumption trade-offs between computation and communication in power constrained networks in general, and in visual sensor networks, in particular. In order to do so, we need to evaluate and model: energy spent to process data by sensors (e.g., how much energy vision algorithms require, etc.), as well as energy required for communications. The first step is to develop an accurate model for energy consumption due to communications. Such energy model must be as close to reality as possible, taking into account all radio states, i.e., energy spent not only while transmitting and receiving a packet, but also while in idle, overhearing, or sleep modes. We have developed such a model and used it to instrument the QualNet and GloMoSim network simulators. We have used QualNet/GloMoSim instrumented with our model to compare energy consumption of power-aware MAC protocols, multi-hop ad-hoc wireless networks routing protocols, and to evaluate an analytical model of energy consumption in single-hop IEEE 802.11 ad-hoc networks. Next, we look at a model that also includes processing and sensing tasks, besides communication. Since we were targeting power constrained networks, we had to look into a typical platform for wireless mobile applications: a laptop. This step provided a good opportunity to define our methodology, which determines the energy consumption of basic tasks. From this point on, we focused on Visual Sensor Networks. We designed and implemented a wireless camera network testbed, Meerkats, which is based on the Stargate platform. We followed the same methodology developed for the laptops' testbed to characterize the energy consumption of the Meerkats' node. Along this work, we also extended and validate the on-board battery monitoring capability on the Stargate. Following this step, we tailored the tasks to the ones representative of activities carried out by wireless camera networks targeting surveillance applications. Given this set of tasks (which we call elementary tasks), a quantitative power consumption and temporal analysis of set of duty cycles that apply to the Meerkats testbed was done. Then we used what we learned from the duty cycle analysis along with a set of experiments on the Meerkats testbed to understand how a framework for lifetime prediction can be build. We proposed a simple deterministic lifetime prediction model based on task composition, which we validate using the experiments executed on the Meerkats testbed. Finally, we consider a set of possible duty cycles given requirements for the Meerkats testbed and analyze how they affect the node lifetime. (Abstract shortened by UMI.)
Intact Recollection Memory in High-performing Older Adults: ERP and Behavioral Evidence
Authors: Audrey Duarte, Charan Ranganath, Celina Trujillo, Robert T. Knight
Venue: Journal of Cognitive Neuroscience (2006)

Numerous behavioral studies have suggested that normal aging has deleterious effects on episodic memory and that recollection is disproportionately impaired relative to familiarity-based recognition. However, there is a wide degree of variability in memory performance within the aging population and this generalization may not apply to all elderly adults. Here we investigated these issues by using event-related potentials (ERPs) to measure the effects of aging on the neural correlates of recollection and familiarity in older adults with recognition memory performance that was equivalent to (old-high) or lower than (old-low) that of young adults. Results showed that, behaviorally, old-high subjects exhibited intact recollection but reduced familiarity, whereas old-low subjects had impairments in both recollection and familiarity, relative to the young. Consistent with behavioral results, old-high subjects exhibited ERP correlates of recollection that were topographically similar to those observed in young subjects. However, unlike the young adults, old-high subjects did not demonstrate any neural correlates of familiarity-based recognition. In contrast to the old-high group, the old-low group exhibited neural correlates of recollection that were topographically distinct from those of the young. Our results suggest that the effects of aging on the underlying brain processes related to recollection and familiarity are dependent on individual memory performance and highlight the importance of examining performance variability in normal aging.
An environment for supporting independent, individualized learning and problem solving
Authors: Susan M. William, Ray Bariess, Brian J. Reiser
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

We have been investigating ways of supporting middle-school students who are learning mathematics by constructing unique solutions to complex problems. This work addresses three needs in supporting independent, individualized learning and problem solving: realistic, complex contexts for learning, structured problem-solving activities that make complex problems more manageable for novices, and readily-available guidance for students during problem solving.Learning is problem-based. Students are asked to design and layout a playground in order to learn to measure, draw to scale, and compute perimeter, area, and volume. The curriculum encourages an iterative approach to problem solving in which students create designs, give each other feedback, and revise their work. To support their problem solving, a software environment provides a simple model of the design task that aids students in identifying sub-goals, brainstorming questions that provide general procedural hints, and two structured multimedia databases: A student database is used to record students' designs, annotated with procedures used, new concepts learned, design rationale, and evaluations. A performance support database provides an archive of previously created designs with associated conceptual and procedural information.
From the Newsstand
Authors: Alison Skratt
Venue: IEEE Internet Computing (2006)

A round-up of Internet-related stories in IEEE Computer Society and trade press.