ppxscal/embedding_network huggingface dataset:
Capacity Theory as a Model of Cortical Behavior
Authors: Todd C. Handy
Venue: Journal of Cognitive Neuroscience (2000)

Growing evidence suggests that a more complete understanding of cortical function requires developing cognitive models that are predictive of multivariate neural behavior (e.g., Raichle, 2000; Shulman et al., 1997). Towards this end, one approach is to interpret population-specific activity in cortex from the perspective of capacity theories of selective attention (e.g., Handy, Hopfinger, & Mangun, in press). In brief, the model is founded on the ideas that (1) processing capacity is limited and (2) different processes may draw on different capacities (e.g., Boles & Law 1998; Polson & Friedman, 1988; see Kramer & Spinks, 1991). Testable hypotheses are then based on whether manipulations of process-specific load will lead to negative or positive covariation between different function-related clusters of activation in cortex - the predicted pattern depends on whether or not the clusters in question are assumed to share a common processing capacity. Expanding on these ideas, the current article addresses several recent issues that have arisen in the effort to apply capacity theory to the study of cortical function.
Toward automatic code generation based on real-time process algebra (rtpa)
Authors: Xinming Tan
Venue:  (2006)

This research is aimed at automatic code generation from Real-Time Process Algebra (RTPA) [Wang2002a] specifications. The work presented in this thesis covers the formal description of the RTPA syntaxes and semantics, and their processing and code generation. The lexical and syntactical analyses and type checking of RTPA specifications, the construction of abstract syntax trees, the runtime support for RTPA real-time features, and the C++ code generator are systematically studied. RTPA is designed to deal with a rich set of fundamental real-time processes such as timing, interrupt, concurrency, and event/time-driven behaviors. In order to implement the real-time processes of RTPA, the C++ code generation is implemented in two phases: the first phase parses the concrete syntaxes of RTPA specifications resulting in the corresponding abstract syntax trees; the second phase generates code from the abstract syntax trees of RTPA specifications. The syntax of RTPA is formally described by EBNF notations, which is used to design and implement the RTPA lexer, parser and type checker with the support of the ANTLR tool. Real-time kernel techniques are used in the implementation of the RTPA runtime library to guarantee timeliness and predictability. The denotational semantics of RTPA is studied to formally express the semantics of RTPA processes because some of them cannot be described adequately in conventional denotational semantics paradigms. The time dimension is introduced and modeled by the elapse of process execution. The system environment encompasses states of all variables. The duration is introduced as a pair of time interval and the environment to represent the changes of the environment during a given time interval. Temporal ordered durations and operations on them are used to denote process executions. The implementation of the RTPA lexer, parser, type checker, and RTPA-to-C++ code generator provides an important tool for RTPA recognition and for generating executable code based on formal specifications of system architectures and behaviors in RTPA. The case studies carried out in this research show that the approach to C++ code generation from RTPA specifications is achievable and practical, which can seamlessly transform a formal RTPA specification into executable and effective programs for real-time systems.
Area and Power Reduction of Embedded DSP Systems using Instruction Compression and Re-configurable Encoding
Authors: Subash Chandar, Mahesh Mehendale, R. Govindarajan
Venue: Journal of VLSI Signal Processing Systems (2006)

In embedded control applications, system cost and power/energy consumption are key considerations. In such applications, program memory forms a significant part of the chip area. Hence reducing code size reduces the system cost significantly. A significant part of the total power is consumed in fetching instructions from the program memory. Hence reducing instruction fetch power has been a key target for reducing power consumption. To reduce the cost and power consumption, embedded systems in these applications use application specific processors that are fine tuned to provide better solutions in terms of code density, and power consumption. Further fine tuning to suit each particular application in the targeted class can be achieved through reconfigurable architectures. In this paper, we propose a reconfiguration mechanism, called Instruction Re-map Table, to re-map the instructions to shorter length code words. Using this mechanism, frequently used set of instructions can be compressed. This reduces code size and hence the cost. Secondly, we use the same mechanism to target power reduction by encoding frequently used instruction sequences to Gray codes. Such encodings, along with instruction compression, reduce the instruction fetch power. We enhance Texas Instruments DSP core TMS320C27x to incorporate this mechanism and evaluate the improvements on code size and instruction fetch energy using real life embedded control application programs as benchmarks. Our scheme reduces the code size by over 10% and the energy consumed by over 40%.
Dynamic threshold method for scene change detection
Authors: S. Wee
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

In general, the scene change for video indexing could be detected by using an appropriate threshold. However, the single fixed threshold value used in previous researches cannot perform well for all videos equally. In this paper, we propose a dynamic threshold method (DTM) in order to improve the performance of the scene change detection. The proposed method utilizes variable parameters obtained from detected cuts and the distribution of cut intervals in order to change the threshold dynamically. In short, the threshold in DTM is lowered in the area where the chance of cut occurrence is high and raised in the area where the chance of cut occurrence is low. Experimental results indicate that the proposed DTM is both computationally low and robust to false alarm. 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
Towards mapping library and information science
Authors: Frizo Janssens, Jacqueline Leta, Wolfgang Glänzel, Bart De Moor
Venue: Information Processing and Management: an International Journal (2006)

In an earlier study by the authors, full-text analysis and traditional bibliometric methods were combined to map research papers published in the journal Scientometrics. The main objective was to develop appropriate techniques of full-text analysis and to improve the efficiency of the individual methods in the mapping of science. The number of papers was, however, rather limited. In the present study, we extend the quantitative linguistic part of the previous studies to a set of five journals representing the field of Library and Information Science (LIS). Almost 1000 articles and notes published in the period 2002-2004 have been selected for this exercise. The optimum solution for clustering LIS is found for six clusters. The combination of different mapping techniques, applied to the full text of scientific publications, results in a characteristic tripod pattern. Besides two clusters in bibliometrics, one cluster in information retrieval and one containing general issues, webometrics and patent studies are identified as small but emerging clusters within LIS. The study is concluded with the analysis of cluster representations by the selected journals.
The ability to articulate strategy as a predictor of programming skill
Authors: Simon, Quintin Cutts, Sally Fincher, Patricia Haden, Anthony Robins, Ken Sutton, Bob Baker, Ilona Box, Michael de Raadt, John Hamer, Margaret Hamilton, Raymond Lister, Marian Petre, Denise Tolhurst, Jodi Tutty
Venue: Proceedings of the 8th Austalian conference on Computing education - Volume 52 (2006)

A multi-national, multi-institutional study investigating introductory programming courses drew on student participants from eleven institutions, mainly in Australasia, during the academic year of 2004. A number of diagnostic tasks were used to explore cognitive, behavioural, and attitudinal factors such as spatial visualisation and reasoning, the ability to articulate strategies for commonplace search and design tasks, and attitudes to studying. This paper reports in detail on the task that required participants to articulate a commonplace search strategy. The results indicate that increasing measures of richness of articulation of a search strategy are associated with higher marks in the course.
Sojourn times in (discrete) time shared systems and their continuous time limits
Authors: Arzad A. Kherani
Venue: Proceedings of the 1st international conference on Performance evaluation methodolgies and tools (2006)

We consider two classes of preemptive processor sharing scheduling policies in which the instantaneous weight given to a customer depends on a) the amount of service already imparted to the customer (Age-based scheduling), or b) the amount of service yet to be imparted to the customer (Residual Processing Time, RPT, based scheduling). We analyze the system for the mean sojourn time of a tagged customer conditioned on its service requirement. The main contribution of this article are:i) We decompose the sojourn time of a customer into two parts: a) the contribution of the descendants of the customer, and b) the contribution of the jobs (and their descendants) which the customer sees on arrival. For the preemptive system under consideration, it is shown that the behavior of the mean sojourn time for large values of service requirement is determined only by the first term above. We provide a closed form expression for this component of the sojourn time for general Age-based and RPT-based scheduling disciplines.iii) If the weight assigned to a customer with an age x units is x&alpha; for some &alpha;, we show that the behavior of mean sojourn time conditioned on service requirement is asymptotically linear for all 0 &le; &alpha; &le; 1. Moreover, this asymptotic slope is same for 0 &le; &alpha; < 1 and shows a discontinuity at &alpha; = 1.
Global Epidemiological Outbreak Surveillance System Architecture
Authors: Ricardo Jorge Santos, Jorge Bernardino
Venue: Proceedings of the 10th International Database Engineering and Applications Symposium (2006)

Diseases such as avian influenza, severe acute respiratory syndrome (SARS) and Creutzfeldt-Jacob syndrome represent a new era of biological threats. Nowadays, these hazards breed, mutate and evolve at tremendous speed. Furthermore, they may spread out at the same speed as which we travel. This reveals an urgent need for an agent capable of dealing with such threats. Data warehouses are databases which provide decision support by on-line analytical processing (OLAP) techniques. We present the architecture for an effective information system infrastructure enabling the prediction and near real-time detection of disease outbreaks, using knowledge extraction algorithms to explore a symptoms/diseases data warehouse in a continuous and active form. To collect such data, we take advantage of the Internet and features existing in today's common communication devices such as personal computers, portable digital assistants and cellular phones. We present a case-simulation based on a small country, showing the system can detect an outbreak within hours or even minutes after its physical occurrence, alerting health decision makers and providing quick interaction and feedback between all users. The architecture is also functionally independent from its geographical dimension.
Method Matters: An Empirical Study of Impact in Cognitive Neuroscience
Authors: Lesley K. Fellows, Andrea S. Heberlein, Dawn A. Morales, Geeta Shivde, Sara Waller, Denise H. Wu
Venue: Journal of Cognitive Neuroscience (2005)

A major thrust of cognitive neuroscience is the elucidation of structure&ndash;function relationships in the human brain. Over the last several years, functional neuroimaging has risen in prominence relative to the lesion studies that formed the historical core of work in this field. These two methods have different strengths and weaknesses. Among these is a crucial difference in the nature of evidence each can provide. Lesion studies can provide evidence for necessity claims, whereas functional neuroimaging studies do not. We hypothesized that lesion studies will continue to have greater scientific impact even as the relative proportion of such studies in the cognitive neuroscience literature declines. Using methods drawn from systematic literature review, we identified a set of original cognitive neuroscience articles that employed either functional imaging or lesion techniques, published at one of two time points in the 1990s, and assessed the effect of the method used on each article's impact across the decade. Functional neuroimaging studies were cited three times more often than lesion studies throughout the time span we examined. This effect was in large part due to differences in the influence of the journals publishing the two methods; functional neuroimaging studies appeared disproportionately more often in higher impact journals. There were also differences in the degree to which articles using one method cited articles using the other method. Functional neuroimaging articles were less likely to include such cross-method citations.
'Hybrid modeling': advanced scientific investigations linking computer models and real-world sensing (an interactive poster)
Authors: Paulo Blikstein, Uri Wilensky
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

'Hybrid modeling' is an innovative technological platform that enables students to link multi-agent models ("in" the computer) and electronic sensors ("outside") in real time. The platform is designed for learners to validate, refine, and debug their computer models using real-world data. Also, the technology broadens the types of scientific explorations possible in classrooms. Pilot studies suggest a real-to-virtual reciprocity that catalyzes further inquiry toward deeper understanding.
Fostering creativity through cross-disciplinary collaboration in an online dance course
Authors: Iris Garland, Lucio Teles, Xinchun Wang
Venue: Proceedings of the 1999 conference on Computer support for collaborative learning (1999)

This paper examines cross-disciplinary collaboration in an online dance course in the School for the Contemporary Arts, Simon Fraser University. The course was delivered entirely online through the Lohn Lab, Centre for Distance Education at SFU. Students were from both the Faculty of Arts and the Faculty of Applied Sciences, which allowed for cross-disciplinary collaborative work. Most course tasks required the students to create unique human figure animations using Life Forms 3-D human figure animation software and give aesthetic critiques on the work of others. To investigate how online collaborative tasks may foster creativity, we analyzed conference transcripts, interviews, and questionnaires. Transcript analysis showed that students actively collaborated. The message exchange also revealed that the environment functioned well as a means of promoting student-centered collaboration. The insight and creativity in using Life Forms that the non-dance students contributed helped dance students free themselves from their established conceptions of dance pedagogy and aesthetics. Issues that hindered collaboration were mostly related to students' particular preferences and software problems (downloading/uploading time). The majority of students interviewed supported the online collaborative Life Forms assignment tasks, but some were negative about collaborative assignments.
Employees' privacy vs. employers' security: can they be balanced?
Authors: Lilian Mitrou, Maria Karyda
Venue: Telematics and Informatics (2006)

This paper addresses the controversy between employees' right to privacy and employers' need to safeguard organizational resources by employing monitoring tools. It shows how organizations can formulate use policies, by applying basic principles for fair and lawful monitoring. A list of key points is presented, which organizations should take into account, for developing such policies. Finally, the paper explores how, widely accepted information security standards, such as the ISO 17799, can aid the attempt to address this controversy.
A Comparison between Scatter Search and the RAND Method for Solving the Joint Replenishment Problem
Authors: Miguel A. Gutierrez A., S. de-los-Cobos, J. Goddard
Venue: Proceedings of the Fifth Mexican International Conference on Artificial Intelligence (2006)

The purpose of the present paper is to compare the performance of scatter search (SS) against one of the best heuristics, known as the RAND algorithm (Kaspi and Rosenblatt [7]), in order to solve a popular and useful multi-product inventory problem referred to in the literature as the joint replenishment problem (JRP). The JRP is a classical problem of great utility for many real problems. This paper applies the SS method to a set of randomly generated examples, and shows that the solutions obtained, when compared to RAND, are, when not better, at least identical in the majority of cases for up to 50 items. An important observation is that the average number of iterations employed by SS to find the best solutions on the set of examples, had a linear behavior with respect to the number of items.
Reverse testing: an efficient framework to select amongst classifiers under sample selection bias
Authors: Wei Fan, Ian Davidson
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

One of the most important assumptions made by many classification algorithms is that the training and test sets are drawn from the same distribution, i.e., the so-called "stationary distribution assumption" that the future and the past data sets are identical from a probabilistic standpoint. In many domains of real-world applications, such as marketing solicitation, fraud detection, drug testing, loan approval, sub-population surveys, school enrollment among others, this is rarely the case. This is because the only labeled sample available for training is biased in different ways due to a variety of practical reasons and limitations. In these circumstances, traditional methods to evaluate the expected generalization error of classification algorithms, such as structural risk minimization, ten-fold cross-validation, and leave-one-out validation, usually return poor estimates of which classification algorithm, when trained on biased dataset, will be the most accurate for future unbiased dataset, among a number of competing candidates. Sometimes, the estimated order of the learning algorithms' accuracy could be so poor that it is not even better than random guessing. Therefore,a method to determine the most accurate learner is needed for data mining under sample selection bias for many real-world applications. We present such an approach that can determine which learner will perform the best on an unbiased test set, given a possibly biased training set, in a fraction of the computational cost to use cross-validation based approaches.
Analysis and Application Scenarios of Enterprise Architecture: An Exploratory Study
Authors: Tobias Bucher, Ronny Fischer, Stephan Kurpjuweit, Robert Winter
Venue: Proceedings of the 10th IEEE on International Enterprise Distributed Object Computing Conference Workshops (2006)

Enterprise architecture (EA) gained growing importance as a key issue of information management in recent years. This paper is aimed at contributing to EA methodology by a systemization of EA analysis techniques and EA application scenarios. These findings are compared with current EA practice collected by means of an exploratory study.
Implementing Knowledge Base for HS Matchmaking
Authors: Xie Wei, Li Yinsheng, Xu Yingxiao, Ma Zhanxin
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2006)

Harmonized System (HS) is a systematic directory to identify the product codes based on their categories for entry and exit inspection. The identified HS codes are used, by entry and exit authorities, to determine the applicable policies for product to be inspected. We have proposed a HS codes Web service to intelligently generate the HS codes for the product names. Besides, the service can enable the computer systems to automatically process the quarantine and custom inspection. In this paper, we provide technical details to implement a knowledge base for the service. A semantic reasoning algorithm of the service is used to generate codes on the knowledge base for the input products. The technical solution, system design, experiment results, and applications of the knowledge base are provided.
Quarantine Region Scheme to Mitigate Spam Attacks in Wireless Sensor Networks
Authors: Vedat Coskun, Erdal Cayirci, Albert Levi
Venue: IEEE Transactions on Mobile Computing (2006)

The Quarantine Region Scheme (QRS) is introduced to defend against spam attacks in wireless sensor networks where malicious antinodes frequently generate dummy spam messages to be relayed toward the sink. The aim of the attacker is the exhaustion of the sensor node batteries and the extra delay caused by processing the spam messages. Network-wide message authentication may solve this problem with a cost of cryptographic operations to be performed over all messages. QRS is designed to reduce this cost by applying authentication only whenever and wherever necessary. In QRS, the nodes that detect a nearby spam attack assume themselves to be in a quarantine region. This detection is performed by intermittent authentication checks. Once quarantined, a node continuously applies authentication measures until the spam attack ceases. In the QRS scheme, there is a trade-off between the resilience against spam attacks and the number of authentications. Our experiments show that, in the worst-case scenario that we considered, a not quarantined node catches 80 percent of the spam messages by authenticating only 50 percent of all messages that it processes.
Discovering interesting patterns through user's interactive feedback
Authors: Dong Xin, Xuehua Shen, Qiaozhu Mei, Jiawei Han
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (ie, frequent patterns) has already been mined. Our goal is to help a particular user effectively discover interesting patterns according to his specific interest. Without requiring a user to explicitly construct a prior knowledge to measure the interestingness of patterns, we learn the user's prior knowledge from his interactive feedback. We propose two models to represent a user's prior: the log linear model and biased belief model. The former is designed for item-set patterns, whereas the latter is also applicable to sequential and structural patterns. To learn these models, we present a two-stage approach, progressive shrinking and clustering, to select sample patterns for feedback. The experimental results on real and synthetic data sets demonstrate the effectiveness of our approach.