ppxscal/embedding_network huggingface dataset:
Technical Expertise Development in Secondary Technical Schools: Effects of ICTenhanced 4C/ID Learning Environments
Authors: Frederick Kwaku Sarfo, Jan Elen
Venue: Proceedings of the Fourth IEEE International Workshop on Technology for Education in Developing Countries (2006)

This study assessed the effectiveness of powerful learning environments (PLE), developed in line with the specifications of the 4C/ID-model, and the additional effect of ICT for fostering the development of technical expertise in traditional Ghanaian classrooms. The study had a one by one by two pretest posttest quasi experimental design. Three functionally equivalent classes of students from three similar (secondary technical) schools were randomly exposed to three different treatments. The participants consisted of 144 (44, 47, 53) students (mean age was 18.1). The pilot study, served to validate and revise the materials, and to retrain teachers. The main study, consisted of six sessions, conducted in regular classrooms of three schools to test the formulated hypotheses. The results indicate that a 4C/ID PLE promotes the development of technical expertise in secondary technical education better than teaching designed in line with classical instructional design principles. Moreover, results reveal no significant difference of learning gains between the 4C/ID PLE with ICT group and the 4C/ID PLE without ICT group. Finally, the theoretical, research, and practical implications of the results for the instructional design and technology community as well as educational practice are discussed.
GPU Based Real-time Shadow Research
Authors: Yang Xiao, Jin Yicheng, Yin Yong, Wu Zhuoyu
Venue: Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation (2006)

Shadow can strengthen the reality of 3D virtual scene and provide important visual information for the objects' spacial relationship in the scene. This paper presents a GPU based method for all the process of shadow volume algorithm. It can achieve greater shadow performance in Ship-handling simulator than previous methods by migrating the silhouette extraction and shadow volume rending to GPU, and applying a series of techniques for culling, clipping, and simplifying shadow volume geometry. We make a series of optimization for the visual system of the ship-handling simulator such as limit the range of illumination, the alternation of z-pass and z-fail algorithm, using the ultra shadow technology and two sided stencil buffer to accelerate the rending of shadow.
Co-evolution of Agent Oriented Conceptual Models and Use Case Diagrams
Authors: Mohammad M. R. Bhuiyan, M. M. Zahidul Islam, Aneesh Krishna, Aditya Ghose
Venue: Proceedings of the Sixth International Conference on Quality Software (2006)

Agent--oriented conceptual modeling notations such as i* represents an interesting approach for modeling early phase requirements which includes organizational contexts, stakeholder intentions and rationale. On the other hand Use Case diagram is used for capturing functional requirements of the system. The integration of i* model and Use Case diagram closes the gap of capturing organizational requirements and system requirements. But in both contexts the requirements might change at any time. Any change made in one model must be reflected in the other. This paper proposes a methodology supporting the co-evolution of these two otherwise disparate approaches in a synergistic fashion.
Toward Developing Multiple Organs and Diseases Diagnosing Intellectual System referring to Knowledge Base and CT Images
Authors: Tetsuya Satos, Norihiro Abe, Kazuaki Tanaka, Yoshimasa Kinoshita, Shoujie He
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

The performance improvement of radiation diagnosis devices makes it possible to get detailed medical images. The objective of this research is to develop a computer aided diagnosis system that uses advanced information of images for various kinds of internal organs and diseases. In order to make the computer aided diagnosis system do the work, as it must presume position of internal organs, the spine is used as a landmark of positional presumption. The position of each spine is recognized from the CT data, and the lungs area is extracted based on the result. We think it possible for the computer aided diagnosis system to inform radiologists about abnormality regions when the image data processing algorithm about several organs is integrated with positional presumption of organs in the future.
Visualizing earth: what do scientists and students see?
Authors: Daniel Barstow, Susan J. Doubler, Katherine Frome Paget
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

Visualizing Earth, an NSF funded project, explores the educational power of remote-sensing and Geographic Information Systems as a way for students to investigate our planet, to learn about the geosciences, and to develop skills of geographic visualization, problem-solving, and investigative learning.
An initial algebra approach to term rewriting systems with variable binders
Authors: Makoto Hamana
Venue: Higher-Order and Symbolic Computation (2006)

We present an extension of first-order term rewriting systems. It involves variable binding in the term language. We develop systems called binding term rewriting systems (BTRSs) in a stepwise manner. First we present the term language, then formulate equational logic. Finally, we define rewriting systems. This development is novel because we follow the initial algebra approach in an extended notion of ¿-algebras in various functor categories. These are based on Fiore-Plotkin-Turi's presheaf semantics of variable binding and Lüth-Ghani's monadic semantics of term rewriting systems. We characterise the terms, equational logic and rewrite systems for BTRSs as initial algebras in suitable categories. Then, we show an important rewriting property of BTRSs: orthogonal BTRSs are confluent. Moreover, by using the initial algebra semantics, we give a complete characterisation of termination of BTRSs. Finally, we discuss our design choice of BTRSs from a semantic perspective.
A Quality Enhancement Model Considering Service Providers and Consumers Relation
Authors: Valbona Barolli, Heihachiro Fukuda, Leonard Barolli, Makoto Takizawa
Venue: Proceedings of the 17th International Conference on Database and Expert Systems Applications (2006)

In this paper, we provide an evaluation model for marketable quality and profitability of corporations. We apply the real values of some leading manufacturing corporations in Japan to our proposed model to analyze its accuracy. From the analysis, we concluded that the theoretical and real standard values of the marketable quality indicator were both 0.6 (that is 60%). From our further analysis, we extracted the turning point from economies of scale to enhancement of marketable quality. The turning point is almost the same with the theoretical standard values of marketable quality and the rate of operation.
An Improved Design and Implementation of Chinese Name Card Recognition System on Mobile Devices
Authors: Chi Cui
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

Since name card recognition based on built-in cameras has become popular people now pay more attention to the robustness and effectiveness of the system. In spite of the maturity of OCR some bottlenecks in lower processing level such as spatial correction and segmentation weak its power. Traditional models treating the card image as an orthogonal projection with only affine distortion are too simple and thus perspective correction is needed to enhance the recognition rate.Due to the complexity of the layout of Chinese name cards text segmentation also attaches strong significance to the performance. In this paper a improved name card recognition system would be devised and implemented. Two new algorithms for perspective correction and text segmentation would be proposed respectively.
Electrophysiological Correlates of Emotion-Induced Recognition Bias
Authors: Sabine Windmann, Marta Kutas
Venue: Journal of Cognitive Neuroscience (2001)

The question of how emotions influence recognition memory is of interest not only within basic cognitive neuroscience but from clinical and forensic perspectives as well. Emotional stimuli can induce a "recognition bias" such that individuals are more likely to respond "old" to a negative item than to an emotionally neutral item, whether the item is actually old or new. We investigated this bias using event-related brain potential (ERP) measures by comparing the processing of words given "old" responses with accurate recognition of old/new differences. For correctly recognized items, the ERP difference between old items (hits) and new items (correct rejections, CR) was largely unaffected by emotional violence. That is, regardless of emotional valence, the ERP associated with hits was characterized by a widespread positivity between 300 and 700 msec relative to that for CRs. By contrast, the analysis of ERPs to old and new items that were judged "old" (hits and false alarms [FAs], respectively) revealed a differential effect of valence by 300 msec: Neutral items showed a large old/new difference over prefrontal sites, whereas negative items did not. These results are the first clear demonstration of response bias effects on ERPs linked to recognition memory. They are consistent with the idea that frontal cortex areas may be responsible for relaxing the retrieval criterion for negative stimuli so as to ensure that emotional events are not as easily "missed" or forgotten as neutral events.
Adaptive Control of Extreme-scale Stream Processing Systems
Authors: Lisa Amini, Navendu Jain, Anshul Sehgal, Jeremy Silber, Olivier Verscheure
Venue: Proceedings of the 26th IEEE International Conference on Distributed Computing Systems (2006)

Distributed stream processing systems offer a highly scalable and dynamically configurable platform for time-critical applications ranging from real-time, exploratory data mining to high performance transaction processing. Resource management for distributed stream processing systems is complicated by a number of factorsprocessing elements are constrained by their producer-consumer relationships, data and processing rates can be highly bursty, and traditional measures of effectiveness, such as utilization, can be misleading. In this paper, we propose a novel distributed, adaptive control algorithm that maximizes weighted throughput while ensuring stable operation in the face of highly bursty workloads. Our algorithm is designed to meet the challenges of extreme-scale stream processing systems, where overprovisioning is not an option, by making the best use of resources even when the proffered load is greater than available resources. We have implemented our algorithm in a real-world distributed stream processing system and a simulation environment. Our results show that our algorithm is not only self-stabilizing and robust to errors, but also outperforms traditional approaches over a broad range of buffer sizes, processing graphs, and burstiness types and levels.
DNA Microarray Image Enhancement Using Conditional Sub-Block Bi-Histogram Equalization
Authors: Nader Saffarian, Ju Jia Zou
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

In this paper, a new image enhancement approach is proposed, which has the ability to improve the gridding results in DNA microarray analysis. The proposed approach is implemented as a conditional sub-block bi-histogram equalization (CSBE). This is accomplished by first, decomposing an input image into a number of m x n sub-blocks. Second, the threshold of each sub-block is determined independently. Third, the sub-block is divided into two sub-images based on the threshold. Fourth, only pixels having value greater than the threshold are histogram equalized, and the two sub-images are then recombined. The proposed method is tested on various DNA microarray images, giving excellent results, compared to existing methods.
Classification of Cervix Lesions Using Filter Bank-Based Texture Mode
Authors: Yeshwanth Srinivasan, Brian Nutter, Sunanda Mitra, Benny Phillips, Eric Sinzinger
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

This paper explores the classification of texture patterns observed in digital images of the cervix. In particular, the problem of identifying and segmenting punctations and mosaic patterns is considered. First, the ability of large scale filter banks in characterizing punctations and mosaic structures is studied using texton models. However, texton-based models fail to consistently classify punctation and mosaic sections obtained from cervix images of different subjects. We present a novel method to segment punctations that combines matched filtering using a Gaussian template with Gaussian Mixture Models. Features extracted from the objects detected using this novel method on punctation and mosaic sections are shown to provide excellent classification between punctation and mosaicism. Results demonstrate the effectiveness of our approach in detecting punctations and separating punctation sections from mosaic sections.
Perfect simulation of monotone systems for rare event probability estimation
Authors: Jean-Marc Vincent
Venue: Proceedings of the 37th conference on Winter simulation (2005)

This paper deals with the estimation of rare event probabilities in finite capacity queueing networks. The traditional product form property of Markovian queueing networks usually vanishes when capacity of queues are finite and clients are blocked or rejected. A new efficient simulation method, derived from Propp & Wilson (Propp 1996), perfect simulation, is applied in the finite capacity queue context. An algorithm directly samples states of the network according to the stationary distribution. This method is adapted for simulation of rare events, typically when events are described by an increasing subset of the state space.Provided that events of the network are monotone, monotonicity techniques are used to reduce the sampling time. Moreover, a stopping mechanism has been developed to interrupt the simulation when an increasing set has been reached. Then, for the estimation of a monotonous reward function, the simulation time could be reduced drastically as in (Vincent and Marchand 2004).
Background Initialization in Cluttered Sequences
Authors: Andrea Colombari, Andrea Fusiello, Vittorio Murino
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

In this paper we propose a technique to robustly estimate the background in a cluttered sequence, i.e., a sequence where occluding objects persist in the same position for a considerable portion of time. As pixel-level heuristic are not sufficient in this case, we introduce spatial support. First the sequence is subdivided in patches that are clustered along the time-line in order to narrow down the number of background candidates. Then the background is grown incrementally by selecting at each step the best continuation of the current background, according to the principles of visual grouping. The method rests on sound principles in all its stages, and only few, intelligible parameters are needed. Experiments with real sequences illustrate the approach.
The Role of Theory and Experiment in Language Design--A 15 Year Perspective
Authors: Daniel E. Cooke, Brad Nemanich, J. Nelson Rushton
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

This paper highlights a 15-year research effort during which the executable specification language SequenceL has been researched and developed. The paper covers early insights into how iterative control structures are used as well as advances involving simple and general semantics.
A Boundary Integral Equation Method for Photonic Crystal Fibers
Authors: Min Hyung Cho, Wei Cai, Tsing-Hua Her
Venue: Journal of Scientific Computing (2006)

A boundary integral equation for the eigenmode of photonic crystal fibers is formulated and numerically solved using the Nyström method. The real and imaginary parts of the propagation constant, which are related to the dispersion and the confinement loss of fibers, are obtained using a secant method. This formulation is very flexible to handle the fiber geometry, and therefore can be applied to photonic crystal fibers with novel refractive index profile and hole geometry.
Interactive Feature Tracking using K-D Trees and Dynamic Programming
Authors: Aeron Buchanan, Andrew Fitzgibbon
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

A new approach to template tracking is presented, incorporating three distinct contributions. Firstly, an explicit definition for a feature track is given. Secondly, the advantages of an image preprocessing stage are demonstrated and, in particular, the effectiveness of highly compressed image patch data stored in k-d trees for fast and discriminatory image patch searches. Thirdly, the k-d trees are used to generate multiple track hypotheses which are efficiently merged to give the optimal solution using dynamic programming. The explicit separation of feature detection and trajectory determination creates the basis for the novel use of k-d trees and dynamic programming. Multiple appearances and occlusion handling are seamlessly integrated into this framework. Appearance variation through the sequence is robustly handled in an iterative process. The work presented is a significant foundation for a powerful off-line feature tracking system, particularly in the context of interactive applications.
Extend SRML schema based on DEVS: an executable DEVS language
Authors: Chen Liu, Qun Li, Wei-ping Wang, Yi-fan Zhu
Venue: Proceedings of the 37th conference on Winter simulation (2005)

This paper analyzes the significance of the representation and reusability of SRML when being used in simulation models as well as its drawbacks. The paper also discusses the ways to extend SRML schema based on DEVS. The emphasis is placed on the elaboration of mapping DEVS onto SRML schema to formulate SRML's basic syntax and semantics for the structure and behavior representation of atomic model and coupled model. The model structure, such as property, input interface, output interface and sub-model composition, are described by a group of XML marks. The model behavior, such as external transition, internal transition, output and time-advance functions are described by script language and a group of standard interface offered by SRML simulator in Script marks. The paper then reviews the SRML element architecture and finally gives a simulation demo of using SRML to build differential equation model.
A network layer approach to enable TCP over multiple interfaces
Authors: Kameswari Chebrolu, Bhaskaran Raman, Ramesh R. Rao
Venue: Wireless Networks (2005)

The mobile Internet is set to become ubiquitous with the deployment of various wireless technologies. When heterogeneous wireless networks overlap in coverage, a mobile terminal can potentially use multiple wireless interfaces simultaneously. In this paper, we motivate the advantages of simultaneous use of multiple interfaces and present a network layer architecture that supports diverse multi-access services. Our main focus is on one such service provided by the architecture: Bandwidth Aggregation (BAG), specifically for TCP applications.While aggregating bandwidth across multiple interfaces can improve raw throughput, it introduces challenges in the form of packet reordering for TCP applications. When packets are reordered, TCP misinterprets the duplicate ACKS received as indicative of packet loss and invokes congestion control. This can significantly lower TCP throughput and counter any gains that can be had through bandwidth aggregation. To improve overall performance of TCP, we take a two-pronged approach: (1) We propose a scheduling algorithm that partitions traffic onto the different paths (corresponding to each interface) such that reordering is minimized. The algorithm estimates available bandwidth and thereby minimizes reordering by sending packet pairs on the path that introduces the least amount of delay. (2) A buffer management policy is introduced at the client to hide any residual reordering from TCP. We show through simulations that our network-layer approach can achieve good bandwidth aggregation under a variety of network conditions.
Risks of Untrustworthiness
Authors: Peter G. Neumann
Venue: Proceedings of the 22nd Annual Computer Security Applications Conference (2006)

This paper revisits the risks of untrustworthiness, and considers some incidents involving computer-based systems that have failed to live up to what had been expected of them. The risks relate to security, reliability, survivability, human safety, and other attributes, and span a variety of applications and critical infrastructures -- such as electric power, telecommunications, transportation, finance, medical care, and elections. The range of causative factors and the diversity of the resulting risks are both enormous. Unfortunately, many of the problems seem to recur far too often. Various lessons therefrom and potential remedies are discussed.
Anticipatory Gain Modulation in Preparation for Smooth Pursuit Eye Movements
Authors: Hiromitsu Tabata, Kenichiro Miura, Kenji Kawano
Venue: Journal of Cognitive Neuroscience (2005)

We studied the effect of the probability of required tracking on the gain of visuomotor transmission for pursuit initiation in monkeys. We recorded the ocular responses to a brief movement (perturbation) of a target located at an eccentric position from the central fixation spot. As soon as the central fixation spot went off, the animal was required to make a saccade to the target if it remained stationary or to track if it moved. The probability of an upcoming ramp motion of the target (horizontal, 20&deg;/sec), requiring pursuit, was varied (target motion probability [TMP] = 0, 0.25, 0.5, 0.75, and 1, which was fixed in a block). We found that the magnitude of the response to the perturbation increased gradually as the TMP increased. The initial pursuit response and the perturbation response showed very similar dependence on the TMP, suggesting that the response to the perturbation could be used as an index of the gain of visuomotor transmission for pursuit initiation. We also found that the changes in the ocular responses after the TMP was changed from one probability to another occurred rapidly (decay constant of only a few trials). These results suggest that the gain of visuomotor transmission in preparing for pursuit is rapidly modulated in accordance with the anticipated future need for pursuit.
Ensemble Tracking
Authors: Shai Avidan
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

We consider tracking as a binary classification problem, where an ensemble of weak classifiers is trained online to distinguish between the object and the background. The ensemble of weak classifiers is combined into a strong classifier using AdaBoost. The strong classifier is then used to label pixels in the next frame as either belonging to the object or the background, giving a confidence map. The peak of the map and, hence, the new position of the object, is found using mean shift. Temporal coherence is maintained by updating the ensemble with new weak classifiers that are trained online during tracking. We show a realization of this method and demonstrate it on several video sequences.