ppxscal/embedding_network huggingface dataset:
Distributed Coordination Strategies for Wide-Area Patrol
Authors: Brandon J. Moore, Kevin M. Passino
Venue: Journal of Intelligent and Robotic Systems (2009)

This paper addresses the problem of enabling a group of autonomous vehicles to effectively patrol an environment significantly larger than their communication and sensing radii. The environment is divided into smaller areas and special coordinator vehicles are designated to control the transfer of the other vehicles from one area to another. Our past work showed that by organizing the areas and coordinators into a ring topology, we could design a control algorithm that globally balanced the number of vehicles in all areas within a bounded length of time. This paper extends those results to a much broader class of area-coordinator topologies and this added flexibility can be used in implementation to reduce the time it takes to attain the globally balanced state.
SurroundSense: mobile phone localization via ambience fingerprinting
Authors: Martin Azizyan, Ionut Constandache, Romit Roy Choudhury
Venue: Proceedings of the 15th annual international conference on Mobile computing and networking (2009)

A growing number of mobile computing applications are centered around the user's location. The notion of location is broad, ranging from physical coordinates (latitude/longitude) to logical labels (like Starbucks, McDonalds). While extensive research has been performed in physical localization, there have been few attempts in recognizing logical locations. This paper argues that the increasing number of sensors on mobile phones presents new opportunities for logical localization. We postulate that ambient sound, light, and color in a place convey a photo-acoustic signature that can be sensed by the phone's camera and microphone. In-built accelerometers in some phones may also be useful in inferring broad classes of user-motion, often dictated by the nature of the place. By combining these optical, acoustic, and motion attributes, it may be feasible to construct an identifiable fingerprint for logical localization. Hence, users in adjacent stores can be separated logically, even when their physical positions are extremely close. We propose SurroundSense, a mobile phone based system that explores logical localization via ambience fingerprinting. Evaluation results from 51 different stores show that SurroundSense can achieve an average accuracy of 87% when all sensing modalities are employed. We believe this is an encouraging result, opening new possibilities in indoor localization.
Is non-parametric hypothesis testing model robust for statistical fault localization?
Authors: Zhenyu Zhang, W. K. Chan, T. H. Tse, Peifeng Hu, Xinming Wang
Venue: Information and Software Technology (2009)

Fault localization is one of the most difficult activities in software debugging. Many existing statistical fault-localization techniques estimate the fault positions of programs by comparing the program feature spectra between passed runs and failed runs. Some existing approaches develop estimation formulas based on mean values of the underlying program feature spectra and their distributions alike. Our previous work advocates the use of a non-parametric approach in estimation formulas to pinpoint fault-relevant positions. It is worthy of further study to resolve the two schools of thought by examining the fundamental, underlying properties of distributions related to fault localization. In particular, we ask: Can the feature spectra of program elements be safely considered as normal distributions so that parametric techniques can be soundly and powerfully applied? In this paper, we empirically investigate this question from the program predicate perspective. We conduct an experimental study based on the Siemens suite of programs. We examine the degree of normality on the distributions of evaluation biases of the predicates, and obtain three major results from the study. First, almost all examined distributions of evaluation biases are either normal or far from normal, but not in between. Second, the most fault-relevant predicates are less likely to exhibit normal distributions in terms of evaluation biases than other predicates. Our results show that normality is not common as far as evaluation bias can represent. Furthermore, the effectiveness of our non-parametric predicate-based fault-localization technique weakly correlates with the distributions of evaluation biases, making the technique robust to this type of uncertainty in the underlying program spectra.
Comparison of Tag Cloud Layouts: Task-Related Performance and Visual Exploration
Authors: Steffen Lohmann, Jürgen Ziegler, Lena Tetzlaff
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

Tag clouds have become a popular visualization and navigation interface on the Web. Despite their popularity, little is known about tag cloud perception and performance with respect to different user goals. This paper presents results from a comparative study of several tag cloud layouts. The results show differences in task performance, leading to the conclusion that interface designers should carefully select the appropriate tag cloud layout according to the expected user goals. Furthermore, the analysis of eye tracking data provides insights into the visual exploration strategies of tag cloud users.
Display size does not affect egocentric distance perception of naturalistic stimuli
Authors: Bernhard E. Riecke, Pooya Amini Behbahani, Chris D. Shaw
Venue: Proceedings of the 6th Symposium on Applied Perception in Graphics and Visualization (2009)

Although people are quite accurate in visually perceiving absolute egocentric distances in real environments up to 20m, they usually underestimate distances in virtual environments presented through head-mounted displays (HMDs). Several previous studies examined different potential factors, but none of these factors could convincingly explain the observed distance compressionin HMDs. In this study, we investigated the potential influence of naturalistic stimulus presentation and display size -- a factor largely overlooked in previous studies. To this end, we used an indirect blindfolded walking task to previously-seen targets. Participants viewed photos of targets located at various distances on the ground through different-sized displays (HMD, 24" monitor, and 50" screen) and walked without vision to where they thought the location of the target was. Real-world photographs were used to avoid potential artifacts of computer-graphics stimuli. Displays were positioned to provide identical fields of view (32&deg; x 24&deg;). Distance judgments were unexpectedly highly accurate and showed no signs of distance compression for any of the displays. Moreover, display size did not affect distance perception, and performance was virtually identical to a real world baseline, where real-world targets were viewed through 32&deg; x 24&deg; field of view restrictors. A careful analysis of potential underlying factors suggests that the typically-observed distance compression for HMDs might be overcome by using naturalistic real-world stimuli. This might also explain why display size did not affect distance judgments.
A Novel Watermarking Technology Based on Lorenz Chaotic Attractor
Authors: Yaqin Li, Cao Yuan, Yan Huang
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

The Lorenz chaotic system is creatively used to encrypt digital images in this paper. An initial data is chosen for the Lorenz chaotic system, and then an encrypted matrix is shown. For the unpredictability of the system and the sensitivity of the initial data, as well as the encrypted matrix which is unknown except of the owner of the digital image, the copy rights can be effectively protected. The watermarking can be extracted with a few data, and the attacked experiential results show the algorithm has very excellent robustness against regular cut and irregular cut as well as noise and compression.
PINE-SPARKY
Authors: Woonghee Lee, William M. Westler, Arash Bahrami, Hamid R. Eghbalnia, John L. Markley
Venue: Bioinformatics (2009)

Summary: PINE-SPARKY supports the rapid, user-friendly and efficient visualization of probabilistic assignments of NMR chemical shifts to specific atoms in the covalent structure of a protein in the context of experimental NMR spectra. PINE-SPARKY is based on the very popular SPARKY package for visualizing multidimensional NMR spectra (T. D. Goddard and D. G. Kneller, SPARKY 3, University of California, San Francisco). PINE-SPARKY consists of a converter (PINE2SPARKY), which takes the output from an automated PINE-NMR analysis and transforms it into SPARKY input, plus a number of SPARKY extensions. Assignments and their probabilities obtained in the PINE-NMR step are visualized as labels in SPARKY's spectrum view. Three SPARKY extensions (PINE Assigner, PINE Graph Assigner, and Assign the Best by PINE) serve to manipulate the labels that signify the assignments and their probabilities. PINE Assigner lists all possible assignments for a peak selected in the dialog box and enables the user to choose among these. A window in PINE Graph Assigner shows all atoms in a selected residue along with all atoms in its adjacent residues; in addition, it displays a ranked list of PINE-derived connectivity assignments to any selected atom. Assign the Best-by-PINE allows the user to choose a probability threshold and to automatically accept as “fixed” all assignments above that threshold; following this operation, only the less certain assignments need to be examined visually. Once assignments are fixed, the output files generated by PINE-SPARKY can be used as input to PINE-NMR for further refinements. Availability: The program, in the form of source code and binary code along with tutorials and reference manuals, is available at http://pine.nmrfam.wisc.edu/PINE-SPARKY. Contact:whlee@nmrfam.wisc.edu; markley@nmrfam.wisc.edu
Italic or Roman: Word Style Recognition without A Priori Knowledge for Old Printed Documents
Authors: Loris Eynard, Hubert Emptoz
Venue: Proceedings of the 2009 10th International Conference on Document Analysis and Recognition (2009)

This paper presents an Italic/Roman word type recognition system without a priori knowledge on the characters' font. This method aims at analyzing old documents in which character segmentation is not trivial. Therefore our approach segments the document into words and analyse the text word per word. To define the word style, we combine three criteria which are based on the visual differences between a word and a slanted version of the same word.These criteria are defined thanks to features computed from the vertical projection profile of the word. Because we do not assume a specific slant angle, we compute these measures on a whole range of possible slant angles and then sum the obtained scores. Our results show a ratio of 100 %recognition for Italic words and 97.2 % for Roman words.
Probabilistic approaches for modeling text structure and their application to text-to-text generation
Authors: Regina Barzilay
Venue: Proceedings of the 12th European Workshop on Natural Language Generation (2009)

Text-to-text generation aims to produce a coherent text by extracting, combining and rewriting information given in input texts. Examples of its applications include summarization, answer fusion in question-answering and text simplification. At first glance, text-to-text generation seems a much easier task than the traditional generation set-up where the input consists of a non-linguistic representation. Research in summarization over the last decade proved that the opposite is true --- texts generated by these methods rarely match the quality of those written by humans. One of the key reasons is the lack of coherence in the generated text.
BitCube: A Bottom-Up Cubing Engineering
Authors: Alfredo Ferro, Rosalba Giugno, Piera Laura Puglisi, Alfredo Pulvirenti
Venue: Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery (2009)

Enhancing on line analytical processing through efficient cube computation plays a key role in Data Warehouse management. Hashing, grouping and mining techniques are commonly used to improve cube pre-computation. BitCube, a fast cubing method which uses bitmaps as inverted indexes for grouping, is presented. It horizontally partitions data according to the values of one dimension and for each resulting fragment it performs grouping following bottom-up criteria. BitCube allows also partial materialization based on iceberg conditions to treat large datasets for which a full cube pre-computation is too expensive. Space requirement of bitmaps is optimized by applying an adaption of the WAH compression technique. Experimental analysis, on both synthetic and real datasets, shows that BitCube outperforms previous algorithms for full cube computation and results comparable on iceberg cubing.
Proceedings of the NAACL HLT 2009 Workshop on Semi-Supervised Learning for Natural Language Processing
Venue: ACL Workshops (2009)

Welcome to the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing! Will semi-supervised learning (SSL) become the next de-facto standard for building natural language processing (NLP) systems, just as supervised learning has transformed the field in the last decade? Or will it remain as a nice idea that doesn't always work in practice? Semi-supervised learning has become an important topic due to the promise that high-quality labeled data and abundant unlabeled data, if leveraged appropriately, can achieve superior performance at lower cost. As researchers in semi-supervised learning reach critical mass, we believe it is time to take a step back and think broadly about whether we can discover general insights from the various techniques developed for different NLP tasks. The goal of this workshop is to help build a community of SSL-NLP researchers and foster discussions about insights, speculations, and results (both positive and negative) that may otherwise not appear in a technical paper at a major conference. In our call-for-paper, we posed some open questions: 1. Problem Structure: What are the different classes of NLP problem structures (e.g. sequences, trees, N-best lists) and what algorithms are best suited for each class? For instance, can graph-based algorithms be successfully applied to sequence-to-sequence problems like machine translation, or are self-training and feature-based methods the only reasonable choices for these problems? 2. Background Knowledge: What kinds of NLP-specific background knowledge can we exploit to aid semi-supervised learning? Recent learning paradigms such as constraint-driven learning and prototype learning take advantage of our domain knowledge about particular NLP tasks; they represent a move away from purely data-agnostic methods and are good examples of how linguistic intuition can drive algorithm development. 3. Scalability: NLP data-sets are often large. What are the scalability challenges and solutions for applying existing semi-supervised learning algorithms to NLP data? 4. Evaluation and Negative Results: What can we learn from negative results? Can we make an educated guess as to when semi-supervised learning might outperform supervised or unsupervised learning based on what we know about the NLP problem? 5. To Use or Not To Use: Should semi-supervised learning only be employed in low-resource languages/tasks (i.e. little labeled data, much unlabeled data), or should we expect gains even in high-resource scenarios (i.e. expecting semi-supervised learning to improve on a supervised system that is already more than 95% accurate)? We received 17 submissions and selected 10 papers after a rigorous review process. These papers cover a variety of tasks, ranging from information extraction to speech recognition. Some introduce new techniques, while others compared existing methods under a variety of situations. We are pleased to present these papers in this volume.
The Research of Immobilized Atrazine Degrading Bacteria Degrading Characteristics
Authors: Yao Ma, Yuexuan Ma, Zhao Jiang, Rongjuan Wang, Ying Zhang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

The immobilization technology could improve the degradation efficiency and adaptability of bacteria. It is a simple, accurate and safety processing method. The research use alginate sodium embedding method to fix the high efficient atrazine degrading bacteria, research the best immobilized condition of alginate sodium to the atrazine degrading bacteria, provide the theoretical basis for next research and practical application. The concentration of the alginate sodium is 3%, the concentration of calcium chloride and bacterial liquid is 5% respectively. Use the different dosing quantity of alginate sodium which from 1-8mL, in different temperature 4℃,10℃，20℃，30℃，40℃ and different pH from 3-10 to determine the best immobilized condition. The result show that the both strains in 30℃ and pH 4-7 condition degradation rate is the highest, after culturing 72 hours atrazine is degraded totally the degradation rate is nearly 100%. The best suitable dosing quantity of the strain which in the adding carbon source condition is 6mL, the best suitable dosing quantity of the strain which use atrazine as the only carbon and nitrogen sources is 3mL.
Assessing mobility support in mesh networks
Authors: Stefano Annese, Claudio Casetti, Carla F. Chiasserini, Paolo Cipollone, Andrea Ghittino, Massimo Reineri
Venue: Proceedings of the 4th ACM international workshop on Experimental evaluation and characterization (2009)

We address the joint problem of traffic routing and mobility support in wireless mesh networks that are built by many fixed nodes and few mobile nodes. We focus on a vehicular setting, where buses or streetcars connect to different fixed mesh nodes as they move in a urban environment. First, through simulation we identify the best candidate for routing traffic in such a scenario and we find that our improved version of the BATMAN protocol, named smart window BATMAN, outperforms other reactive and proactive approaches. Then, we develop a testbed which includes both roadside mesh nodes and vehicular mesh nodes. There, we implement the selected routing solution, along with a handover scheme that allows vehicles to connect to the different mesh nodes in a seamless manner. Our testbed and performance assessment show that mobility can be efficiently supported in mesh networks, and that our modified version of the BATMAN protocol is a good candidate for sustaining the handover of UDP streams in a seamless manner.
Combining Fast-Paced Usability and Scientific Testing to Improve the Lunar Quest Physics Game
Authors: Holly Blasko-Drabik, James Bohnsack, Clint Bowers
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

This study focuses on conducting fast-paced in-house testing in combination with user comments and scores on the Questionnaire for User Interface Satisfaction (QUIS) to provide a better educational game. The standard QUIS was shortened and focused to be more sensitive to aspects of our educational game. The game, Lunar Quest, was created at the University of Central Florida as a supplemental instruction tool that would provide students with examples of several different Physics concepts while being an enjoyable and fun game. Overall the modified version of the QUIS was not successful in determining which categories of the game should be targeted, although the open ended questions did help our researchers focus the game redesign and showed improvement throughout the testing period.
Algorithmic Information Theory and Foundations of Probability
Authors: Alexander Shen
Venue: Proceedings of the 3rd International Workshop on Reachability Problems (2009)

The question how and why mathematical probability theory can be applied to the "real world" has been debated for centuries. We try to survey the role of algorithmic information theory (Kolmogorov complexity) in this debate.
Position: the user is the enemy
Authors: S. Vidyaraman, M. Chandrasekaran, S. Upadhyaya
Venue: Proceedings of the 2007 Workshop on New Security Paradigms (2008)

The Human Factor has long been recognized as the weakest link in computer systems security, yet, nothing technically significant has been done to address this problem in an attack agnostic manner. In this paper, we introduce the mantra of "The User is the Enemy" for security designers and developers alike as an underlying current towards addressing the weak human factor. We present different notions of the user and the system and argue from parallel tracks that user actions, both ignorant and non-compliant, are detrimental to the organization. We further show how the paradigm has been applied in a rather unconscious manner and contend that security mechanisms borne out of a conscious application will be more effective towards addressing this systemic problem. Our position is not meant to be a cynical attitude towards users; rather, it is meant to be the focal point of security design attitude, similar to the mantra "All user input is evil" for addressing buffer overflow attacks.
The Design and Analysis of a Real-Time, Continuous Arousal Monitor
Authors: Bernard Grundlehner, Lindsay Brown, Julien Penders, Bert Gyselinckx
Venue: Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks (2009)

The recent development of miniaturized, low-power components for body sensor networks pave the way towards intelligent and ambulatory monitoring devices with a plurality of applications. Here, the design and development of a real-time arousal monitor, based on Human++ Body Area Network components is described. A new set of biomarkers is proposed based on psychophysiological observations and principles. A strong relation between the estimated arousal level and the expected arousal level is reported for responses triggered by movie clips, in a controlled environment. This relation is shown to extend to stimuli of a different nature, such as sounds and mental stress tests. The system will enable new applications in the field of stress management, safety, e-learning and gaming.
Conceptual and Spatial Footprints for Complex Systems Analysis: Application to the Semantic Web
Authors: Bénédicte Grand, Michel Soto, Marie-Aude Aufaure
Venue: Proceedings of the 20th International Conference on Database and Expert Systems Applications (2009)

This paper advocates the use of Formal Concept Analysis and Galois lattices for complex systems analysis. This method provides an overview of a system by indicating its main areas of interest as well as its level of specificity/generality. Moreover, it proposes possible entry points for navigation by identifying the most significant elements of the system. Automatic filtering of outliers is also provided.This methodology is generic and may be used for any type of complex systems. In this paper, it is applied to theTopic Map formalism which can be used in the context of the Semantic Web to describe any kind of data as well as ontologies. The proposed Conceptual and Spatial Footprints allow the comparison of Topic Maps both in terms of content and structure. Significant concepts and relationships can be identified, as well as outliers; this method can be used to compare the underlying ontologies or datasets as illustrated in an experiment.