ppxscal/embedding_network huggingface dataset:
Advances in Integrated Design and Manufacturing in Mechanical Engineering II, 1st edition
Authors: Serge Tichkiewitch, Serge Tichkiewitch, M. Tollenaere, Pascal Ray
Venue:  (2007)

The 33 papers presented in this book were selected from amongst the 97 papers presented during the sixth edition of the International Conference on Integrated Design and Manufacturing in Mechanical Engineering during 28 sessions. Two keynote papers, one presented by Professor Stephen Lu, from the IMPACT Research Laboratory, University of Southern California, USA, on Supporting participative joint decisions in integrated design and manufacturing teams , and one written by Professor Stefan Rudolph from Stuttgart University about Know-How Reuse in the conceptual design phase of complex engineering products or: Are you still constructing manually or do you generate already automatically , introduce the subject of the Conference and are followed by the different themes highlighted during the conference: The design/manufacturing interface; Integrated design of manufacturing processes; Life cycle design and manufacturing approaches; Agility in design and manufacture; Knowledge in engineering; and Management in production systems.
Nonlinear media as interactive narrative
Authors: Marcos Novak
Venue:  (2008)

As an interdisciplinary artist and composer I have found that, beyond the common language of new media, the connecting tissue between various art practices and music can be found in narrative. In particular, the kind of narrative that is structured using nonlinear representations of information, time, and space. Nonlinear narrative is an inherent aspect of new media that provides a common baseline whereby media artworks can be evaluated and understood.The discussion of nonlinear narrative as interactive media is an exploration of the question, "what is the form of nonlinear interactive narrative ?" providing the impetus for a theoretical discussion, and a formal approach to the understanding of my past works, while providing a basis for the creation of new works that have a dynamic nonlinear structure and reflect on our modern understanding of knowledge and nature. The domain of this document falls within the field of media art and is motivated by a transmodal aesthetic that developed and matured in tandem with my participation in a series of seminars led by Marcos Novak on the subject of transvergence. The terms and ideas presented in support of the concepts put forth in this document are derived from a variety of sources, including the histories of art, music, and literature; concepts in philosophy (in particular Deleuzeian philosophy); and pattern language as found in the field of software engineering. The result of this discussion is the definition, evaluation, and exploration of a transmodal, generalized description of nonlinear narratives in an abstract formal model called the Universe.It is important to clarify that the term Universe is not intended to describe what can be understood as a "universal model." The Universe is a reference to the concept of worlds borrowed from Virtual Reality terminology in order to describe the qualities of immersive interactive artworks as immersive environments. Thus the Universe Model is a description of the formalized approach taken in the realization of my own work and, although not strictly about music, this document follows a long line of documents in music whereby composers formally define the techniques and theory used in their work.
BotGraph: large scale spamming botnet detection
Authors: Yao Zhao, Yinglian Xie, Fang Yu, Qifa Ke, Yuan Yu, Yan Chen, Eliot Gillum
Venue: Proceedings of the 6th USENIX symposium on Networked systems design and implementation (2009)

Network security applications often require analyzing huge volumes of data to identify abnormal patterns or activities. The emergence of cloud-computing models opens up new opportunities to address this challenge by leveraging the power of parallel computing. In this paper, we design and implement a novel system called BotGraph to detect a new type of botnet spamming attacks targeting major Web email providers. Bot-Graph uncovers the correlations among botnet activities by constructing large user-user graphs and looking for tightly connected subgraph components. This enables us to identify stealthy botnet users that are hard to detect when viewed in isolation. To deal with the huge data volume, we implement BotGraph as a distributed application on a computer cluster, and explore a number of performance optimization techniques. Applying it to two months of Hotmail log containing over 500 million users, BotGraph successfully identified over 26 million botnet-created user accounts with a low false positive rate. The running time of constructing and analyzing a 220GB Hot-mail log is around 1.5 hours with 240 machines. We believe both our graph-based approach and our implementations are generally applicable to a wide class of security applications for analyzing large datasets.
Real-time Robust Mapping for an Autonomous Surface Vehicle using an Omnidirectional Camera
Authors: Xiaojin Gong, Bin Xu, Caleb Reed, Chris Wyatt, Daniel Stilwell
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

Towards the goal of achieving truly autonomous navigation for a surface vehicle in maritime environments, a critical task is to detect surrounding obstacles such as the shore, docks, and other boats. In this paper, we demonstrate a real-time vision-based mapping system which detects and localizes stationary obstacles using a single omnidirectional camera and navigational sensors (GPS and gyro). The main challenge of this work is to make mapping robust to a large number of outliers, which stem from waves and specular reflections on the surface of the water. To address this problem, a two-step robust outlier rejection method is proposed. Experimental results obtained in unstructured large-scale environments are presented and validated using topographic maps.
The Use of Qualitative Reasoning Models of Interactions between Populations to Support Causal Reasoning of Deaf Students
Authors: Paulo Salles, Heloisa Lima-Salles, Bert Bredeweg
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

Making inferences is crucial for understanding the world. The school may develop such skills but there are few formal opportunities for that. This paper describes an experiment designed to investigate the use of qualitative reasoning models to support deaf students in making inferences about the behaviour of populations in interactions such as commensalism, amensalism, and predation. The experiment was done in two sessions. In both, the teacher presented the concepts, which were translated to the signed language, and at the end the students answer to a test, consisting of objective questions and a written essay. In the second session qualitative models about the same types of interactions were used to show the structure of the two populations system and the dynamics of the system over time. Statistical analysis showed that the use of qualitative models had a significant positive effect on the performance of the students. They gave more correct answers to objective questions and produced less trivial conclusions in their essays. We are confident that qualitative models have an important role to play in their scientific education and in the acquisition of Portuguese as a second language.
Categorical semantics for arrows
Authors: Bart Jacobs, Chris Heunen, Ichiro Hasuo
Venue: Journal of Functional Programming (2009)

Arrows are an extension of the well-established notion of a monad in functional-programming languages. This paper presents several examples and constructions and develops denotational semantics of arrows as monoids in categories of bifunctors Cop × C → C. Observing similarities to monads – which are monoids in categories of endofunctors C → C – it then considers Eilenberg–Moore and Kleisli constructions for arrows. The latter yields Freyd categories, mathematically formulating the folklore claim ‘Arrows are Freyd categories.’
A selective-phrase-based preprocessor for improved spam filtering
Authors: Sumitra Mukherjee
Venue:  (2008)

A selective-phrase-based preprocessor for use in generating the feature set of an e-mail message prior to its classification as spam or non-spam is presented. The proposed preprocessor subsumes the phrase-based preprocessor used by Yerazunis and the word-based preprocessor employed by Graham. In Yerazunis' phrased-based approach, a sliding window of W contiguous words is used to generate phrases, and all sub-phrases of each W-word phrase are used as features. In Graham's word-based method, just the individual words in an e-mail message are used as features. The primary goal of this investigation was to determine whether the classification accuracy attained by Yerazunis' preprocessor can be achieved at a lower computational cost by selecting a much smaller but promising set of phrases from which to generate the sub-phrases that constitute the features. The proposed preprocessor first identifies a small number f of words from the input text (namely, those that are most likely to appear in spam messages). For each such word, it then selects B distinct phrases of W contiguous words that contain that word and uses all sub-phrases of each such phrase as features. A secondary goal of the research was to investigate the sensitivity of the classification accuracy on f, B, and W. The methods used by the proposed preprocessor and the preprocessors devised by Yerazunis and Graham were tested on a benchmark corpus of e-mail messages. The classification accuracy and other metrics were measured and reported. The results indicated that the classification accuracy of the proposed preprocessor was comparable to that of Yerazunis' preprocessor while utilizing a much smaller set of features. In addition, the research indicated optimum values for f, B, and W: The best accuracies were achieved at (f, B, W) = (2, 1, 2) and (f, B, W) = (2, 2, 2).
New high fill-factor triangular microlens array fabrication method using UV proximity printing
Authors: Tsung-Hung Lin, Hsiharng Yang, Ching-Kong Chao, Shih-Yu Hung
Venue: Microsystem Technologies (2009)

A simple and effective method for fabricating a high fill-factor triangular microlens array using the proximity printing in lithography process is reported. The technology utilizes the UV proximity printing by controlling the printing gap between the mask and substrate. The designed approximate triangle microlens array pattern can be fabricated in photoresist. This is because to the UV light diffraction deflects away from the aperture edges and produces a certain exposure in photoresist material outside the aperture edges. This method can precisely control the geometric profile of a high fill-factor triangular microlens array. The experimental results showed that the triangular photoresist microlens array could be formed automatically when the printing gap ranged from 240 to 840&#x00a0;&#x03bc;m. The gapless triangular microlens array will be used to increase the luminance for the backlight module of liquid crystal displays.
Proceedings of the KDD-09 Workshop on Statistical and Relational Learning in Bioinformatics
Venue: International Conference on Knowledge Discovery and Data Mining (2009)

The KDD-09 Workshop on Statistical and Relational Learning in Bioinformatics (StReBio) will be held at the University of Antwerp, Paris, France, on Sunday June, 28th, 2009. This second edition of the workshop is intended to bring together researchers from both the fields of statistical and relational learning and the field of bioinformatics. Hopefully this will contribute to communication between these communities and will stimulate the development of new relational techniques for application in the biological domain. Bioinformatics is a domain where information is naturally represented in terms of relations between heterogeneous objects. Modern experimentation and data acquisition techniques make the study of complex interactions in biological systems possible, yielding huge amounts of data. This raises challenges for the machine learning and data mining communities, where interest in relational and statistical learning has been growing in the last few years. Apart from the amount of (relational) data, the information is often incomplete, and measurements may be noisy, creating additional challenges. We have tried to choose a workshop format which promotes as much as possible the exchange of ideas. Aspects which can help to achieve our goal are the problem statement presentations, the time allocated in the program for questions and discussion, the informal proceedings and the workshop website (http://www.cs.kuleuven.be/~dtai/events/StReBio09/) where the abstracts, papers and some presentations will be available. We selected eight papers for full presentation. All these contributions, in varying degrees, fit the format of the workshop: they apply statistical or relational techniques to problems from the biological domain. Furthermore, we accepted one problem statement to be presented at the workshop. The idea of the problem statement track is to stimulate the interaction between biologists and computer scientists by presenting biological problems in a more mathematical form, making the structure and the source of uncertainty of the data more explicit. We hope that the problem statements will lead to lively discussions and the exchange of ideas. Finally, a tentative solution to a problem statement from last year's edition is presented. We feel honoured to have David Balding and as invited speaker, who is an authority in the field of statistical genetics.
How Knowledge Validation Processes Affect Knowledge Contribution
Authors: Alexandra Durcikova, Peter Gray
Venue: Journal of Management Information Systems (2009)

To ensure that knowledge repositories contain high-quality knowledge, knowledge management research recommends that contributions to a repository undergo stringent validation processes. To date, however, no research has studied the impact of such processes on contributors' repository-related perceptions or behaviors. To address this gap, we develop a model based on signaling theory and reinforcement theory to explain how individuals' perceptions of three primary validation process characteristics (duration, transparency, and restrictiveness) impact their perceptions of repository knowledge quality and their contribution behaviors. Our empirical results confirm the importance of implementing review processes that are transparent and developmentally oriented as a way of encouraging knowledge contribution. More broadly, this study underscores the need to develop integrated theoretical models that draw from a variety of reference theories when attempting to explain knowledge-related behaviors.
An energy bounding approach for directional transparency in multiple degree-of-freedom haptic interaction
Authors: Jaeha Kim, Jong-Phil Kim, Changhoon Seo, Jeha Ryu
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

This paper presents an energy bounding approach (EBA) to enhance directional transparency while guaranteeing stability for multiple degree-of-freedom (DOF) haptic interaction. It was observed that the passivity condition for multiple ports may lead to some oscillations in some coordinate directions even though total energy is positive. The passivity condition, therefore, needs to be applied to each orthogonal coordinate. For guaranteeing stability in each orthogonal coordinate, the EBA is applied. For multiple-dof haptic interaction, however, the EBA in each coordinate may cause a problem that the direction of the rendered force vector is distorted. This problem can easily be solved by projecting the direction of the rendered force vector on its original direction. The validity of the proposed algorithm is shown by some experiments.
Use of random time-intervals (RTIs) generation for biometric verification
Authors: Nikolaos A. Laskaris, Stefanos P. Zafeiriou, Lambrini Garefa
Venue: Pattern Recognition (2009)

We explore the possibility of using human-generated time-series as biometric signature. Adopting a simple psychometric procedure, in which a button is pressed in entirely random manner, successive elapsed times are registered and gathered in a signal reflecting user's internal cognitive processes. By reconstructing and comparing the dynamics across repetitions from the same subject a noticeable consistency was observed. Moreover, the dynamics showed a prominent idiosyncratic character when realizations from different subjects were contrasted. We established an appropriate similarity measure to systematize such comparisons and experimentally verified that it is feasible to restore someone's identity from RTI (random time-interval) signals. By incorporating it in an SVM-based verification system, which was trained and tested using a medium sized dataset (from 40 persons), a considerably low equal error rate (EER) of ~5% was achieved. RTI signals can be collected effortlessly and this makes our approach appealing, especially in transactions mediated by standard pc terminal keyboards or even telephone keypads.
Towards Structured Approaches to Arbitrary Data Selection and Performance Prediction for Speaker Recognition
Authors: Howard Lei
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

We developed measures relating feature vector distributions to speaker recognition (SR) performances for performance prediction and potential arbitrary data selection for SR. We examined the measures of mutual information, kurtosis, correlation, and measures pertaining to intra- and inter-speaker variability. We applied the measures on feature vectors of phones to determine which measures gave good SR performance prediction of phones standalone and in combination. We found that mutual information had an -83.5% correlation with the Equal Error Rates (EERs) of each phone. Also, Pearson's correlation between the feature vectors of two phones had a -48.6% correlation with the relative EER improvement of the score-level combination of the phones. When implemented in our new data-selection scheme (which does not require a SR system to be run), the measures allowed us to select data with 2.13% overall EER improvement (on SRE08) over data selected via a brute-force approach, at a fifth of the computational costs.
VHDL implementation of neuro-fuzzy based adaptive bandwidth controller for ATM networks
Authors: M. Sundarambal, D. Chandrakala, P. Anbalagan
Venue: International Journal of Communication Networks and Distributed Systems (2009)

The modern intelligent asynchronous transfer mode (ATM) networks need a scheme to maintain quality of service (QoS) towards different traffic constraints in real time environment for effective control and optimal system utilisation. This paper proposes the VHDL implementation of neuro-fuzzy based adaptive bandwidth controller. The intelligent control is used to manage the adaptive bandwidth prediction, congestion control and call admission control (CAC) of ATM networks simultaneously. This integrated hybrid mechanism reduces the decision errors of conventional CAC policies and operating errors occurred on fuzzy based CAC in ATM networks. The individual blocks needed to implement adaptive bandwidth controller for ATM networks are modelled using VHDL. The timing analysis for the validation, functionality and performance of the model is analysed using Altera Quartus II (5.1 version) HDL software and the logic synthesis is performed. The required codes are downloaded into FPGA Cyclone device.
Finite Element Model Updating Based on Least Squares Support Vector Machines
Authors: Yue Zhu, Lingmi Zhang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

Finite element model updating based on the design parameter is a kind of inverse problem in structural dynamics, whose theoretical foundation is using the features of the structure to be a function of design parameters. According to the first-order derivative of the features with respect to design parameters, iterative solution is made. This paper presents a new method which treats the model updating as a positive problem. Features are independent variables and design parameters are dependent variables. The least squares support vector machines (LS-SVM) is utilized as a map function. The objective value of the design parameters can be directly estimated due to the generalization character of the LS-SVM. The method avoids solving the complicated nonlinear optimization problem which is difficult in the reported methods. Finite element model updating based on LS-SVM about the GARTEUR aircraft model is studied. Simulation results show the errors of design parameters and modal frequencies are less than 2% and 1%, respectively.
A methodology and model to develop complex systems from requirement networks
Authors: David W. Matula, Jerrell Stracener
Venue:  (2008)

This dissertation presents a new method for validating system interface requirements. The requirements are validated by modeling and simulation as requirements develop. Any of the models of computation presented in Chapter 5 can be considered expressions of requirements. System interface requirements are validated and then decomposed into interface subsystems. In addition to its emphasis on interfaces between components and its partitioning ability, the method presented has the following advantages over other design and analysis techniques: (1) It lays the foundation of interfaces as the primary emphasis of requirements; thus, categorizing the objects to be developed for any design. (2). The method validates the system interface requirements by modeling and simulating them, providing feedback at the architectural and requirements levels. (3) It permits the partitioning of a system into subsystem components utilizing: (a) the Minimum Capacity Utilization Problem algorithm with unit flows on the edges; and (b) knowledge about the subsystems.
Functional-Structural Plant Modelling in Crop Production, 1st edition
Authors: J. Vos, L. F. M. Marcelis, P. H. B. de Visser, P. C. Struik, J. B. Evers
Venue: Wageningen Ur Frontis Series (2007)

Functional-structural plant models (FSPMs) describe in quantitative terms the development over time of the three-dimensional (3D) structure of plants as governed by physiological processes and affected by environmental factors. FSPMs are particularly suited to analyse problems in which the spatial structure of the plant or its canopy is an essential factor to explain, e.g., plant competition (intra-plant, inter-plant, inter-species) and the effects of plant configuration and plant manipulation (e.g., pruning and harvesting) on yield and produce quality. This book describes the philosophy of functional-structural plant modelling and several tools for making FSPMs; it outlines methods for measuring essential parameters, including those pertaining to plant structure. As FSPMs offer new opportunities to model sinksource interactions, the physiological theory and modelling approaches regarding partitioning of carbon are given specific attention. Examples of application of FSPMs include wheat modelling in the context of remote sensing and the analysis of predatorprey insect interactions on glasshouse plants. The book will be useful for scientists and advanced students interested in innovative approaches in plant and crop modelling.
Creating Sustainable Designs
Authors: Rebecca J. Wirfs-Brock
Venue: IEEE Software (2009)

Christopher Alexander's concept of centers and properties of living structures can help developers create pleasing, sustainable software designs.