ppxscal/embedding_network huggingface dataset:
Model-Based Development of Medical Devices
Authors: Uwe Becker
Venue: Proceedings of the 28th International Conference on Computer Safety, Reliability, and Security (2009)

Model-based development can offer many advantages compared to other techniques. This paper will demonstrate how models are used to develop safe systems in a medical devices company. The approach described uses a combination of model-driven analysis, model-driven design, model-driven test and model-driven safety analysis. Different approaches have been developed and followed in the past. The approach presented has been developed in an evolutionary manner and by combining approaches described in literature. It turned out to be well suited for the medical device domain and is considered to be a best practice approach. As such it is part of the development process that must be followed when developing new medical devices. The development process has to be defined in a written way and is checked by TÜV and FDA auditors on a yearly base. It is considered to be well above-average and thus may be adopted by other companies developing safety-relevant devices. During the audit process it is verified that the documentation of the process is as expected and that the actual development process is performed according to the defined process. This assures for companies adopting the approach that it is authenticated by daily practice and its use requires only modest overhead.
Multimodal people detection and tracking in crowded scenes
Authors: Luciano Spinello, Rudolph Triebel, Roland Siegwart
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

This paper presents a novel people detection and tracking method based on a multi-modal sensor fusion approach that utilizes 2D laser range and camera data. The data points in the laser scans are clustered using a novel graph-based method and an SVM based version of the cascaded AdaBoost classifier is trained with a set of geometrical features of these clusters. In the detection phase, the classified laser data is projected into the camera image to define a region of interest for the vision-based people detector. This detector is a fast version of the Implicit Shape Model (ISM) that learns an appearance codebook of local SIFT descriptors from a set of hand-labeled images of pedestrians and uses them in a voting scheme to vote for centers of detected people. The extension consists in a fast and detailed analysis of the spatial distribution of voters per detected person. Each detected person is tracked using a greedy data association method and multiple Extended Kalman Filters that use different motion models. This way, the filter can cope with a variety of different motion patterns. The tracker is asynchronously updated by the detections from the laser and the camera data. Experiments conducted in real-world outdoor scenarios with crowds of pedestrians demonstrate the usefulness of our approach.
Controlled Query Evaluation and Inference-Free View Updates
Authors: Joachim Biskup, Jens Seiler, Torben Weibert
Venue: Proceedings of the 23rd Annual IFIP WG 11.3 Working Conference on Data and Applications Security XXIII (2009)

We extend Controlled Query Evaluation (CQE), an inference control method to enforce confidentiality in static information systems under queries, to updatable databases. Within the framework of the lying approach to CQE, we study user update requests that have to be translated into a new database state. In order to avoid dangerous inferences, some such updates have to be denied even though the new database instance would be compatible with a set of integrity constraints. In contrast, some other updates leading to an incompatible instance should not be denied. We design a control method to resolve this seemingly paradoxical situation and then prove that the general security definitions of CQE and other properties linked to user updates hold.
Computer Organization and Architecture: Designing for Performance, 8th edition
Authors: William Stallings
Venue:  (2009)

KEY BENEFIT: Learn the fundamentals of processor and computer design from the newest edition of this award winning text. KEY TOPICS: Introduction; Computer Evolution and Performance; A Top-Level View of Computer Function and Interconnection; Cache Memory; Internal Memory Technology; External Memory; I/O; Operating System Support; Computer Arithmetic; Instruction Sets: Characteristics and Functions; Instruction Sets: Addressing Modes and Formats; CPU Structure and Function; RISCs; Instruction-Level Parallelism and Superscalar Processors; Control Unit Operation; Microprogrammed Control; Parallel Processing; Multicore Architecture. Online Chapters: Number Systems; Digital Logic; Assembly Language, Assemblers, and Compilers; The IA-64 Architecture. MARKET: Ideal for professionals in computer science, computer engineering, and electrical engineering. 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
Decoupling congestion control from TCP for multi-hop wireless networks: semi-TCP
Authors: Shengming Jiang, Qin Zuo, Gang Wei
Venue: Proceedings of the 4th ACM workshop on Challenged networks (2009)

TCP performs poorly in multihop wireless networks and even worse if end-to-end connectivity is often broken such as in challenged networks. Lots of research has been carried out but this problem has not been solved completely. Recently, hop-by-hop congestion control originally proposed for wired networks has been applied for multihop wireless networks to significantly improve performances. We think that (i) moving congestion control down to lower layers is essential to overcome TCP problems in multihop wireless networks and (ii) in this case, it is necessary to further decouple congestion control from TCP. Such TCP only retains reliability control and is called semi-TCP henceforth. Due to using hop-by-hop congestion control, the congestion control efficiency of semi-TCP will not rely on the availability of end-to-end connectivity, which makes semi-TCP more suitable than TCP for challenged networks. Besides performance improvement, semi-TCP may further reduce overall system complexity by removing redundant congestion control and using simple congestion control rather than TCP congestion window. This paper discusses such a semi-TCP using a hop-by-hop congestion control that only slightly modifies the RTS/CTS protocol used in the IEEE 802.11 DCF. Furthermore, a solution to a deadlock problem in the RTS/CTS-based hop-by-hop congestion control is also studied. The performance of this semi-TCP is investigated in comparison with TCP-NewReno via simulation in NS2.
Video Sequences Association for People Re-identification across Multiple Non-overlapping Cameras
Authors: Dung Nghi Truong Cong, Catherine Achard, Louahdi Khoudour, Lounis Douadi
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

This paper presents a solution of the appearance-based people re-identification problem in a surveillance system including multiple cameras with different fields of vision. We first utilize different color-based features, combined with several illuminant invariant normalizations in order to characterize the silhouettes in static frames. A graph-based approach which is capable of learning the global structure of the manifold and preserving the properties of the original data in a lower dimensional representation is then introduced to reduce the effective working space and to realize the comparison of the video sequences. The global system was tested on a real data set collected by two cameras installed on board a train. The experimental results show that the combination of color-based features, invariant normalization procedures and the graph-based approach leads to very satisfactory results.
Model-Based Specification and Validation of User Interface Requirements
Authors: Birgit Bomsdorf, Daniel Sinnig
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

Core functional requirements as captured in use case models are too high-level to be meaningful to user interface developers. In this paper we present how use case models can be systematically refined into detailed user interface requirements specifications, captured as task models. We argue that the transition from functional to UI specific requirements is a semi-formal step which necessitates experience, skills and domain knowledge of the requirements engineer. In order to facilitate the transition we sketch out an integrated development methodology for use case and task models. Since the engineer is also responsible for establishing conformity between use cases and task models we also show, how this validation can be supported by means of the WTM task model simulator.
A Policy-Based Sensor Selection System with Goal Oriented Singular Value Decomposition Technique
Authors: Hoi Chan, Thomas Kwok
Venue: Proceedings of the 2009 IEEE International Symposium on Policies for Distributed Systems and Networks (2009)

Modern data center relies on the use of numerous sensors to collect system and environment data to guide the optimal operations of the data centers to meet the desired business goals. The amount of sensors and monitored systems in the data center could be huge, and it includes many types of sensors generating seemingly unrelated data. This presents a challenge to the efficient utilization of these data to determine problems and how well the data center will deliver to the business. In this demo,we present an automatic policy selection management approach with goal guided singular value decomposition technique integrated into IBM Tivoli Monitoring System (ITM) to efficiently utilize the sensor data.
Cheap and fast---but is it good?: evaluating non-expert annotations for natural language tasks
Authors: Rion Snow, Brendan O'Connor, Daniel Jurafsky, Andrew Y. Ng
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

Human linguistic annotation is crucial for many natural language processing tasks but can be expensive and time-consuming. We explore the use of Amazon's Mechanical Turk system, a significantly cheaper and faster method for collecting annotations from a broad base of paid non-expert contributors over the Web. We investigate five tasks: affect recognition, word similarity, recognizing textual entailment, event temporal ordering, and word sense disambiguation. For all five, we show high agreement between Mechanical Turk non-expert annotations and existing gold standard labels provided by expert labelers. For the task of affect recognition, we also show that using non-expert labels for training machine learning algorithms can be as effective as using gold standard annotations from experts. We propose a technique for bias correction that significantly improves annotation quality on two tasks. We conclude that many large labeling tasks can be effectively designed and carried out in this method at a fraction of the usual expense.
A Bayesian Approach to Model Checking Biological Systems
Authors: Sumit K. Jha, Edmund M. Clarke, Christopher J. Langmead, Axel Legay, André Platzer, Paolo Zuliani
Venue: Proceedings of the 7th International Conference on Computational Methods in Systems Biology (2009)

Recently, there has been considerable interest in the use of Model Checking for Systems Biology. Unfortunately, the state space of stochastic biological models is often too large for classical Model Checking techniques. For these models, a statistical approach to Model Checking has been shown to be an effective alternative. Extending our earlier work, we present the first algorithm for performing statistical Model Checking using Bayesian Sequential Hypothesis Testing. We show that our Bayesian approach outperforms current statistical Model Checking techniques, which rely on tests from Classical (aka Frequentist) statistics, by requiring fewer system simulations. Another advantage of our approach is the ability to incorporate prior Biological knowledge about the model being verified. We demonstrate our algorithm on a variety of models from the Systems Biology literature and show that it enables faster verification than state-of-the-art techniques, even when no prior knowledge is available.
Planning and execution with phase transitions
Authors: Håkan L. S. Younes
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

We consider a special type of continuous-time Markov decision processes (MDPs) that arise when phase-type distributions are used to model the timing of non-Markovian events and actions. We focus, primarily, on the execution of phase-dependent policies. Phases are introduced into a model to represent relevant execution history, but there is no physical manifestation of phases in the real world. We treat phases as partially observable state features and show how a belief distribution over phase configurations can be derived from observable state features through the use of transient analysis for Markov chains. This results in an efficient method for phase tracking during execution that can be combined with the QMDP value method for POMDPs to make action choices. We also discuss, briefly, how the structure of MDPs with phase transitions can be exploited in structured value iteration with symbolic representation of vectors and matrices.
Intra-Object versus Inter-Object: Concurrency and Reasoning in Creol
Authors: Einar Broch Johnsen, Jasmin Christian Blanchette, Marcel Kyas, Olaf Owe
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

In thread-based object-oriented languages, synchronous method calls usually provide the mechanism to transfer control from caller to callee, blocking the caller until the call is completed. This model of control flow is well-suited for sequential and tightly coupled systems but may be criticized in the concurrent and distributed setting, not only for unnecessary delays but also for the reasoning complexity of multithreaded programs. Concurrent objects propose an alternative to multithread concurrency for object-oriented languages, in which each object encapsulates a thread of control and communication between objects is asynchronous. Creol is a formally defined modeling language for concurrent objects which clearly separates intra-object scheduling from inter-object communication by means of interface encapsulation, asynchronous method calls, and internal processor release points. This separation of concerns provides a very clean model of concurrency which significantly simplifies reasoning for highly parallel and distributed object-oriented systems. This paper gives an example-driven introduction to these basic features of Creol and discusses how this separation of concerns influences analysis of Creol models.
Customer Situations as a Clue to Information Needs
Authors: Susanne Robra-Bissantz
Venue: Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing (2009)

The approach of describing situations of persons in their surroundings is well known in Mobile Business. This approach is extended to a concept of human situations that holds for a wide range of Information Systems. Based on former empirical findings this contribution shows different cases where customer situations lead to information needs in virtual and real shopping processes.
Incremental Ontology-Based Extraction and Alignment in Semi-structured Documents
Authors: Mouhamadou Thiam, Nacéra Bennacer, Nathalie Pernelle, Moussa Lô
Venue: Proceedings of the 20th International Conference on Database and Expert Systems Applications (2009)

SHIRIis an ontology-based system for integration of semi-structured documents related to a specific domain. The system's purpose is to allow users to access to relevant parts of documents as answers to their queries. SHIRI uses RDF/OWL for representation of resources and SPARQL for their querying. It relies on an automatic, unsupervised and ontology-driven approach for extraction, alignment and semantic annotation of tagged elements of documents. In this paper, we focus on the Extract-Align algorithm which exploits a set of named entity and term patterns to extract term candidates to be aligned with the ontology. It proceeds in an incremental manner in order to populate the ontology with terms describing instances of the domain and to reduce the access to extern resources such as Web. We experiment it on a HTML corpus related to call for papers in computer science and the results that we obtain are very promising. These results show how the incremental behaviour of Extract-Align algorithm enriches the ontology and the number of terms (or named entities) aligned directly with the ontology increases.
Context-Dependent Force-Feedback Steering Wheel to Enhance Drivers' On-Road Performances
Authors: Luca Minin, Stefano Marzani, Francesco Tesauri, Roberto Montanari, Caterina Calefato
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

In this paper the topic of the augmented cognition applied to the driving task, and specifically to the steering maneuver, is discussed. We analyze how the presence of haptic feedback on the steering wheel could help drivers to perform a visually-guided task by providing relevant information like vehicle speed and trajectory. Starting from these considerations, a Context-Dependant Steering Wheel force feedback (CDSW) had been developed, able to provide to the driver the most suitable feeling of the vehicle dynamics according to the driven context. With a driving simulator the CSWD software had been tested twice and then compared with a traditional steering wheel.
A Self-Adaptable Improved Arithmetic Based on Wavelet Transform in the Image Edge Detection
Authors: Jingchao Zhang, Songyan Liu, Guangpu Hao, Lingyun Sun, Jin Yang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

Compared with traditional edge detection methods, the method based on wavelet transform is a high precision way. The scale, however, impacts the effect of output imagine. The high frequency could be controlled when the scale is large, and the SNR of the image is relatively great. But the precision of location is lower. On the other hand, the location could be realized precisely when the scale is small, and the detail of the image could be extracted. But the ability of denoising is weak. A self-adaptable scale selection method is given in this paper. The edge detection of an image can be realized well by different properties of wavelet transform on different scales. Accordingly, the gauss filter is adopted to pre-treat the figure, and the self-adaptable multi-scale wavelet transform is introduced to process the after-pretreat figure. Result of experiment shows that a highly quality edge figure by smooth disposal of different scales is received.
Identifying the topology of protein complexes from affinity purification assays
Authors: Caroline C. Friedel, Ralf Zimmer
Venue: Bioinformatics (2009)

Motivation: Recent advances in high-throughput technologies have made it possible to investigate not only individual protein interactions, but also the association of these proteins in complexes. So far the focus has been on the prediction of complexes as sets of proteins from the experimental results. The modular substructure and the physical interactions within the protein complexes have been mostly ignored. Results: We present an approach for identifying the direct physical interactions and the subcomponent structure of protein complexes predicted from affinity purification assays. Our algorithm calculates the union of all maximum spanning trees from scoring networks for each protein complex to extract relevant interactions. In a subsequent step this network is extended to interactions which are not accounted for by alternative indirect paths. We show that the interactions identified with this approach are more accurate in predicting experimentally derived physical interactions than baseline approaches. Based on these networks, the subcomponent structure of the complexes can be resolved more satisfactorily and subcomplexes can be identified. The usefulness of our method is illustrated on the RNA polymerases for which the modular substructure can be successfully reconstructed. Availability: A Java implementation of the prediction methods and supplementary material are available at http://www.bio.ifi.lmu.de/Complexes/Substructures/. Contact: caroline.friedel@bio.ifi.lmu.de Supplementary information:Supplementary data are available at Bioinformatics online.
Modified fast double sieve bootstraps for ADF tests
Authors: Patrick Richard
Venue: Computational Statistics Data Analysis (2009)

This paper studies the finite sample performance of the sieve bootstrap augmented Dickey-Fuller (ADF) unit root test. It is well known that this test's accuracy in terms of rejection probability under the null depends greatly on the underlying DGP. Through extensive simulations, we find that it also depends on the number of lags employed in the bootstrap DGP and in the bootstrap ADF regression. Based on this finding and using some well established theoretical results, we propose a simple modification that significantly improves the test's accuracy. We also introduce different versions of the fast double bootstrap, each modified according to the same theoretical basis. According to our simulations, these new testing procedures have lower error in rejection probability under the null while retaining good power.
Classification of image objects in Epo doping control using fuzzy decision tree
Authors: Ivan Bajla, Igor Holl&#x00e4;nder, Dorothea Czedik-Heiss, Reinhard Granec
Venue: Pattern Analysis Applications (2009)

Erythropoietin (Epo) is a hormone which can be misused as a doping substance. Its detection involves analysis of images containing specific objects (bands), whose position and intensity are critical for doping positivity. Within a research project of the World Anti-Doping Agency (WADA) we are implementing the GASepo software that serves for Epo testing in doping control laboratories worldwide. For identification of the bands we have developed a segmentation procedure based on a sequence of filters. Whereas all true bands are properly segmented, the procedure generates a number of false positives (artefacts). To separate these artefacts we suggested a post-segmentation supervised classification using real-valued geometrical measures of objects. The method is based on a fuzzy modification of Ross Quinlan&#x2019;s ID3 method, included in the mlf&#x2122; software (Machine Learning Framework). It provides a framework that generates fuzzy decision trees, as well as fuzzy sets for input data. Initially used training set of segmented objects has been replaced by a new one prepared by more accurate expertise using the latest release of the GASepo software. The new fuzzy decision trees (FDT) have been generated for a set of five and nine fuzzy sets. The comparison of the results on testing set of segmented objects shows that the classification based on the new FDTs outperforms other classification methods.
UI on the Fly: generating a multimodal user interface
Authors: David Reitter, Erin Marie Panttaja, Fred Cummins
Venue: Proceedings of HLT-NAACL 2004: Short Papers on XX (2004)

UI on the Fly is a system that dynamically presents coordinated multimodal content through natural language and a small-screen graphical user interface. It adapts to the user's preferences and situation. Multimodal Functional Unification Grammar (MUG) is a unification-based formalism that uses rules to generate content that is coordinated across several communication modes. Faithful variants are scored with a heuristic function.