ppxscal/embedding_network huggingface dataset:
Online Handwritten Shape Recognition Using Segmental Hidden Markov Models
Authors: Thierry Artieres, Sanparith Marukatat, Patrick Gallinari
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

We investigate a new approach for online handwritten shape recognition. Interesting features of this approach include learning without manual tuning, learning from very few training samples, incremental learning of characters, and adaptation to the user-specific needs. The proposed system can deal with two-dimensional graphical shapes such as Latin and Asian characters, command gestures, symbols, small drawings, and geometric shapes. It can be used as a building block for a series of recognition tasks with many applications.
Differential Effects of Lesions of the Amygdala and Prefrontal Cortex on Recognizing Facial Expressions of Complex Emotions
Authors: P. Shaw, J. Bramham, E. J. Lawrence, R. Morris, S. Baron-cohen, A. S. David
Venue: Journal of Cognitive Neuroscience (2005)

Humans can detect facial expressions of both simple, basic emotions and expressions reflecting more complex states of mind. The latter includes emotional expressions that regulate social interactions ("social expressions" such as looking hostile or friendly) and expressions that reflect the inner thought state of others ("cognitive expressions" such as looking pensive). To explore the neural substrate of this skill, we examined performance on a test of detection of such complex expressions in patients with lesions of the temporal lobe (n = 54) or frontal lobe (n = 31). Of the temporal group, 18 had unilateral focal lesions of the amygdala and of the frontal group, 14 patients had unilateral lesions of the ventromedial prefrontal cortex&mdash;two regions held to be pivotal in mediating social cognitive skills. Damage to either the left or right amygdala was associated with impairment in the recognition of both social and cognitive expressions, despite an intact ability to extract information relating to invariant physical attributes. Lesions to all of the right prefrontal cortex&mdash;not just the ventromedial portions&mdash;led to a specific deficit in recognizing complex social expressions with a negative valence. The deficit in the group with right prefrontal cortical damage may contribute to the disturbances in social behavior associated with such lesions. The results also suggest that the amygdala has a role in processing a wide range of emotional expressions.
Indexing schemes for similarity search: an illustrated paradigm
Authors: Vladimir Pestov, Aleksandar Stojmirović
Venue: Fundamenta Informaticae (2005)

We suggest a variation of the Hellerstein--Koutsoupias--Papadimitriou indexability model for datasets equipped with a similarity measure, with the aim of better understanding the structure of indexing schemes for similarity-based search and the geometry of similarity workloads. This in particular provides a unified approach to a great variety of schemes used to index into metric spaces and facilitates their transfer to more general similarity measures such as quasi-metrics. We discuss links between performance of indexing schemes and high-dimensional geometry. The concepts and results are illustrated on a very large concrete dataset of peptide fragments equipped with a biologically significant similarity measure.
A Novel Metric on Partitions for Image Segmentation
Authors: Vladimir Mashtalir, Elena Mikhnova, Vladislav Shlyakhov, Elena Yegorova
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

The explosion of image content is closely connected with segmentations efficiency. However, there is no agreement as to what a good segmentation is due to hard data and applications dependence. To reduce the gap between low-level features and high-level semantic, collections of image partitions produced by different segmentation algorithms are often considered. We propose, theoretically ground and experimentally explore a new metric on segmented images or on arbitrary partitions of finite sets in general.
Incremental Evaluation of Sliding-Window Queries over Data Streams
Authors: Thanaa M. Ghanem Moustafa A. Hammad, Mohamed F. Mokbel, Walid G. Aref, Ahmed K. Elmagarmid
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

Two research efforts have been conducted to realize sliding-window queries in data stream management systems, namely, query reevaluation and incremental evaluation. In the query reevaluation method, two consecutive windows are processed independently of each other. On the other hand, in the incremental evaluation method, the query answer for a window is obtained incrementally from the answer of the preceding window. In this paper, we focus on the incremental evaluation method. Two approaches have been adopted for the incremental evaluation of sliding-window queries, namely, the input-triggered approach and the negative tuples approach. In the input-triggered approach, only the newly inserted tuples flow in the query pipeline and tuple expiration is based on the timestamps of the newly inserted tuples. On the other hand, in the negative tuples approach, tuple expiration is separated from tuple insertion where a tuple flows in the pipeline for every inserted or expired tuple. The negative tuples approach avoids the unpredictable output delays that result from the input-triggered approach. However, negative tuples double the number of tuples through the query pipeline, thus reducing the pipeline bandwidth. Based on a detailed study of the incremental evaluation pipeline, we classify the incremental query operators into two classes according to whether an operator can avoid the processing of negative tuples or not. Based on this classification, we present several optimization techniques over the negative tuples approach that aim to reduce the overhead of processing negative tuples while avoiding the output delay of the query answer. A detailed experimental study, based on a prototype system implementation, shows the performance gains over the input-triggered approach of the negative tuples approach when accompanied with the proposed optimizations.
A Computer-Games-Based AI Research Environment
Authors: Francisco Gallego, Abel Bernabeu, Juan Reverte, Rosana Satorre, Faraon Llorens
Venue: Proceedings of the Fifth Mexican International Conference on Artificial Intelligence (2006)

To develop, test and experiment with new AI algorithms, researchers require an experimentation environment. This is even more necessary when we talk about developing agent and multiagent systems. Moreover, if doing performance comparisons of different algorithms is the goal, it is really important to put all those algorithms to work under the same environment conditions. At present, there is a great variety of environments developed to support AI researchers in their tasks. However, it is usual to find that these environments whether they have too specific aims or they perfom well just with some kind of algoritms. In addition, their tendence to be researcher-oriented prevent us from using them in other fields like education, diffusion or massive testing. In this paper we propose a new kind of multiagent research environment, based on a computer game called Screaming Racers, with which we try to surpass these difficulties. Our computer-games-based research environment is intended to be used simultaneously by researchers, students and general players, powering up research, education, diffusion and massive testing.
Collaborating to learn, learning to collaborate: finding the balance in a cross-disciplinary design course
Authors: Emma Mercier, Shelley Goldman, Angela Booker
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

We report on a four-year study of a cross-disciplinary design course. Using an action research model, we have designed and studied this course. In this paper we report on our study of the students' collaborations. We have found that, although students come to the class believing that they know how to collaborate, there is great variation in their collaborative experiences and outcomes. We outline four dimensions of collaboration that differentiate high and low performing groups, where performances is determined by project quality and student learning. These dimensions, 'teamness', communication, creation of a joint problem space and commitment to learning, have been defined through analysis of the ten groups of students who have taken this course. In this paper we use case studies to illustrate how these dimensions have differentially affected two groups who took the course. Finally, we describe our interventions and the parallels between this study and other research.
On the Completeness of Attack Mutation Algorithms
Authors: Shai Rubin, Somesh Jha, Barton P. Miller
Venue: Proceedings of the 19th IEEE workshop on Computer Security Foundations (2006)

An attack mutation algorithm takes a known instance of an attack and transforms it into many distinct instances by repeatedly applying attack transformations. Such algorithms are widely used for testing intrusion detection systems. We investigate the notion of completeness of a mutation algorithm: its capability to generate all possible attack instances from a given set of attack transformations. We define the notion of a \Phi-complete mutation algorithm. Given a set of transformations \phi, an algorithm is complete with respect to \Phi, if it can generate every instance that the transformations in \Phi derive. We show that if the rules in \Phi are uniform and reversible then a \Phi-complete algorithm exists. Intuitively speaking, uniform and reversible transformations mean that we can first exclusively apply transformations that simplify the attack, then exclusively apply transformations that complicate it, and still get all possible instances that are derived by the rules in \Phi. Although uniformity and reversibility may appear severe restrictions, we show that common attack transformations are indeed uniform and reversible. Therefore, our \Phi- complete algorithm can be incorporated into existing testing tools for intrusion detection systems. Furthermore, we show that a \Phi-complete algorithm is useful, not only for testing purposes, but also for determining whether two packet traces are two different mutations of the same attack. % MathType!MTEF!2!1!+- % feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn % hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr % 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9 % vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x % fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeuOPdyeaaa!3767! \[ \Phi\]
Efficient Data Harvesting for Tracing Phenomena in Sensor Networks
Authors: Adesola Omotayo, Moustafa A. Hammad, Ken Barker
Venue: Proceedings of the 18th International Conference on Scientific and Statistical Database Management (2006)

Many publish/subscribe systems have been built using wireless sensor networks, WSNs, deployed for real-world environmental data collection, security monitoring, and object tracking. However; research efforts on WSN-basedpub- 1ish/subscribe systems have largely focused on routing algorithms leaving data management issues mostly untouched. This paper considers a publish/subscribe system built on top of a sensor network that monitors the occurrences of phenomena. In quest for explanations to the occurrence of a phenomenon, a subscriber poses one-time queries to the sensor network for sensor readings taken seconds or minutes before the reported phenomenon occurred. These types of queries cannot be satisfied by subscriptions since subscriptions are only effective in delivering streams of new phenomena. To efficiently answer such queries, it is imperative that a Data Farm of sensor readings be cultivated within WSNs. This paper proposes a new algorithm for archiving sensor readings on Data Farm that leverages the non-volatile memory of sensor nodes in the network. The proposed algorithm takes advantage of the memory space on nodes that have low probabilities of detecting phenomena. By running an extensive set of simulation experiments, the performance results show that the proposed algorithm can provide 32.9% memory gain and 81.8% low communication overhead when compared to an approach in which nodes use only their own physical memory.
The role of exogenous factors in technology acceptance: the case of object-oriented technology
Authors: Sang M. Lee, Injai Kim, Shanggeun Rhee, Silvana Trimi
Venue: Information and Management (2006)

In spite of many theoretical models, the role of exogenous factors in accepting object-oriented technology has not been satisfactorily demonstrated. By comparing two competing models, our study examined the role and location of exogenous variables in explaining user acceptance of object-oriented technology. Based on the results, we developed a new model that combined the key ideas of both TAM and TPB and showed that both models are necessary in understanding the unique role of each exogenous variable.
The Relevance of Software Modeling to the Software Industry
Venue: Proceedings of the 17th International Symposium on Software Reliability Engineering (2006)

A good percentage of papers submitted to software development related conferences are related to the subject of modeling. To many researchers, model-driven development is the answer to most software reliability/development problems. They argue that models help the architects to reason about the problem and solution domains, and can potentially be used to formally prove that any solution meets its specification (again another area of considerable research interest). But in the midst of this massive interest in modeling from the research fraternity, industry appears to take a more ambivalent attitude, often viewing modeling as a useful methodology but having limitations. Additionally some in industry are moving away from formal methodologies, in applying techniques such as XP or agile methods.
Guest Editor's Introduction: On the Evolution of Applying Agent Technology to Healthcare
Authors: Antonio Moreno
Venue: IEEE Intelligent Systems (2006)

This article is part of a special issue on Intelligent Agents in Healthcare. Agent technology is currently being applied to solve different kinds of problems in the healthcare domain. This special issue presents six articles that discuss different applications, in areas as diverse as automatic e-health service discovery, use of argumentation techniques in organ transplants, and the implementation of agent-based mechanisms that ensure the confidentiality and privacy of sensitive medical data.
Bayesian methods for discrete event simulation
Authors: Stephen E. Chick
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Bayesian methods are now used in a variety of ways in discrete-event simulation. Applications include input modeling, response surface modeling, uncertainty analysis, and experimental designs for field data collection, selection procedures, and response surface estimation. This paper reviews some fundamental concepts of subjective probability and Bayesian statistics that have led to results in simulation applications.
Topics over time: a non-Markov continuous-time model of topical trends
Authors: Xuerui Wang, Andrew McCallum
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

This paper presents an LDA-style topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. Unlike other recent work that relies on Markov assumptions or discretization of time, here each topic is associated with a continuous distribution over timestamps, and for each generated document, the mixture distribution over topics is influenced by both word co-occurrences and the document's timestamp. Thus, the meaning of a particular topic can be relied upon as constant, but the topics' occurrence and correlations change significantly over time. We present results on nine months of personal email, 17 years of NIPS research papers and over 200 years of presidential state-of-the-union addresses, showing improved topics, better timestamp prediction, and interpretable trends.
Testing the Correctness of MPI Implementations
Authors: Rainer Keller, Michael Resch
Venue: Proceedings of the Proceedings of The Fifth International Symposium on Parallel and Distributed Computing (2006)

This paper introduces an MPI test suite to thoroughly test the correctness of an MPI-implementation. Scientific applications require stable tools and libraries for portable and efficient programming, e. g. when depending on the singlesided communication on multiple platforms. This test suite was originally used to check the correct transmission of data in the PACX-MPI implementation, but has been mainly used and extended to test the development of the new Open MPI implementation. The tool has been designed to be easily extendible in order to integrate new tests using the underlying functionality.
An Image Processing Tool to Support Gestational Age Determination
Authors: Luciano Silva, Olga R. P. Bellon, Rubisley de P. Lemes, Jorge A. Meira, Monica N. L. Cat
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

The FootScanAge is a non-invasive, more accurate novel approach to automatically estimate the gestational age of newborns. This task is performed by the computational analysis of the features from the newborn plantar surface. The FootScanAge system is composed by two main tools: (1) image processing and (2) data mining. In this paper, we present the image processing tool that extract features of the plantar surface by applying image processing techniques developed to work on the footprint of the newborns, which present some singular characteristics. We included the results that support the determination of an adequate gestational age score by using the data mining tool.
A hierarchical mobile agent framework and its application to multimedia contents
Authors: Fuyuki Ishikawa, Nobukaza Yoshioka, Yasuyuki Tahara, Shinichi Honiden
Venue: Systems and Computers in Japan (2007)

A hierarchical mobile agent is a model that extends the standard mobile agent. In this model it is possible for an agent to migrate inside another agent and parent&ndash;child relations can be constructed (the host agent being the parent). By means of such agent synthesis, it is possible to integrate different functionality and have agents interact with one another with no need for remote communications. Even when an agent migrates, it is possible to maintain the relations between parent and child stably over a long period of time. In this paper we focus on the task of controlling these parent&ndash;child relations and propose the MAFEH framework designed to simplify related tasks. This framework has two special characteristics. One consists of the parent&ndash;child agreement specification that expresses the agreement regarding the behavior between parent and child. The other consists of the interaction behavior description specification that facilitates the description of the processes by which individual interactive partners can be searched for, enter into combinations, and disassociate themselves from each other. In this paper we also present an application of the MAFEH framework demonstrating how an agent that encapsulates mobile contents can combine with other agents that provide different contents and services. &copy; 2006 Wiley Periodicals, Inc. Syst Comp Jpn, 38(1): 1&ndash;17, 2007; Published online in Wiley InterScience (). DOI 10.1002&sol;scj.20624
Survey and Review
Authors: Fadil Santosa
Venue: SIAM Review (2006)

Consider the fact that you can put your entire music collection on your portable mp3 player and you begin to realize what a tremendous amount of data is being stored in its tiny disk drive. How is it possible that data can be so efficiently stored in a magnetic storage device? The answer is ferromagnetism. Progress in storage technology follows Kryder&apos;s law, which is akin to the more familiar Moore&apos;s law, governing the performance of CPUs. The storage capacity of disk drives, measured by areal density, has increased exponentially in the past 20 or so years. At the time of this writing, areal density of 110 Gbits/square inch is common. A new storage format, called perpendicular format, is capable of areal density of 245 Gbits/square inch. Ferromagnetism, the subject of the article by Martin Kruzík and Andreas Prohl, is modeled by a continuum theory called micromagnetics. The mathematics of micromagnetics is complex and beautiful, exhibiting rich and surprising behavior. The article introduces the reader to the models of micromagnetics, their mathematical analyses, and simulation methods for them. The authors show that despite great progress in this field, much still needs to be understood. Perhaps the key to quantifying the theoretical limit of magnetic storage capacity lies in the mathematics of micromagnetics. Mathematics might also provide guidance on how one can achieve this limit in practical devices.
Demonstrating the stability of support vector machines for classification
Authors: I. Buciu, C. Kotropoulos, I. Pitas
Venue: Signal Processing (2006)

In this paper, we deal with the stability of support vector machines (SVMs) in classification tasks. We decompose the average prediction error of SVMs into the bias and the variance terms, and we define the aggregation effect. By estimating the aforementioned terms with bootstrap smoothing techniques, we demonstrate that support vector machines are stable classifiers. To investigate the stability of the SVM several experiments were conducted. The first experiment deals with face detection. The second experiment conducted is related to the binary classification of three artificially generated data sets stemming from known distributions and an additional synthetic data set known as "Waveform". Finally, in order to support our claim on the stability of SVMs, two more binary classification experiments were carried out on the "Pime Indian Diabetes" and the "Wisconsin Breast Cancer" data sets. In general, bagging is not expected to improve the classification accuracy of SVMs.
Learning to Use a Learned Model: A Two-Stage Approach to Classification
Authors: Maria-Luiza Antonie, Osmar R. Zaiane, Robert C. Holte
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Association rule-based classifiers have recently emerged as competitive classification systems. However, there are still deficiencies that hinder their performance. One defi- ciency is the use of rules in the classification stage. Current systems assign classes to new objects based on the best rule applied or on some predefined scoring of multiple rules. In this paper we propose a new technique where the system automatically learns how to use the rules. We achieve this by developing a two-stage classification model. First, we use association rule mining to discover classification rules. Second, we employ another learning algorithm to learn how to use these rules in the prediction process. Our two-stage approach outperforms C4.5 and RIPPER on the UCI datasets in our study, and outperforms other rule-learning methods on more than half the datasets. The versatility of our method is also demonstrated by applying it to text classification, where it equals the performance of the best known systems for this task, SVMs.