ppxscal/embedding_network huggingface dataset:
On minimum Fisher information distributions with restricted support and fixed variance
Authors: J. -F. Bercher, C. Vignat
Venue: Information Sciences: an International Journal (2009)

Fisher information is of key importance in estimation theory. It also serves in inference problems as well as in the interpretation of many physical processes. The mean-squared estimation error for the location parameter of a distribution is bounded by the inverse of the Fisher information associated with this distribution. In this paper we look for minimum Fisher information distributions with a restricted support. More precisely, we study the problem of minimizing the Fisher information in the set of distributions with fixed variance defined on a bounded subset S of R or on the positive real line. We show that the solutions of the underlying differential equation can be expressed in terms of Whittaker functions. Then, in the two considered cases, we derive the explicit expressions of the solutions and investigate their behavior. We also characterize the behavior of the minimum Fisher information as a function of the imposed variance.
Investments and Trade-offs in the Economics of Information Security
Authors: Christos Ioannidis, David Pym, Julian Williams
Venue: Financial Cryptography and Data Security: 13th International Conference, FC 2009, Accra Beach, Barbados, February 23-26, 2009. Revised Selected Papers (2009)

We develop and simulate a dynamic model of investment in information security. The model is based on the recognition that both IT managers and users appreciate the trade-off between two of the fundamental characteristics of information security, namely confidentiality and availability. The model's parameters can be clustered in a manner that allows us to categorize and compare the responses to shocks of various types of organizations. We derive the system's stability conditions and find that they admit a wide choice of parameters. We examine the system's responses to the same shock in confidentiality under different parameter constellations that correspond to various types of organizations. Our analysis illustrates that the response to investments in information security will be uniform in neither size nor time evolution.
A data modeling approach to climate change attribution
Authors: Aurélie Lozano
Venue: Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data (2009)

Climate modeling and analysis of climate change have largely been based on forward simulation with physical models. We propose here a data centric approach to climate study based solely on the actual observed data. This novel approach utilizes a variety of relevant statistical modeling and machine learning techniques such as spatial-temporal causal modeling and extreme value modeling, and suggests multiple future research directions. We will describe preliminary results using data for North America from CRU, NOAA, NASA, NCDC, and CDIAC, as well as certain technical challenges encountered. It is hoped that this alternative perspective will help uncover new insights, improve aspects of simulation models with known uncertainties, and provide a useful complementary approach to climate study.
Abstraction is harmful in language learning
Authors: Walter Daelemans
Venue: Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning (1998)

The usual approach to learning language processing tasks such as tagging, parsing, grapheme-to-phoneme conversion, pp-attachment, etc., is to extract regularities from training data in the form of decision trees, rules, probabilities or other abstractions. These representations of regularities are then used to solve new cases of the task. The individual training examples on which the abstractions were based are discarded (forgotten). While this approach seems to work well for other application areas of Machine Learning, I will show that there is evidence that it is not the best way to learn language processing tasks. I will briefly review empirical work in our groups in Antwerp and Tilburg on lazy language learning. In this approach (also called, instance-based, case-based, memory-based, and example-based learning), generalization happens at processing time by means of extrapolation from the most similar items in memory to the new item being processed. Lazy Learning with a simple similarity metric based on information entropy (IB1-IG, Daelemans & van den Bosch, 1992, 1997) consistently outperforms abstracting (greedy) learning techniques such as C5.0 or backprop learning on a broad selection of natural language processing tasks ranging from phonology to semantics. Our intuitive explanation for this result is that lazy learning techniques keep all training items, whereas greedy approaches lose useful information by forgetting low-frequency or exceptional instances of the task, not covered by the extracted rules or models (Daelemans, 1996). Apart from the empirical work in Tilburg and Antwerp, a number of recent studies on statistical natural language processing (e.g. Dagan & Lee, 1997; Collins & Brooks, 1995) also suggest that, contrary to common wisdom, forgetting specific training items, even when they represent extremely low-frequency events, is harmful to generalization accuracy. After reviewing this empirical work briefly, I will report on new results (work in progress in collaboration with van den Bosch and Zavrel), systematically comparing greedy and lazy learning techniques on a number of benchmark natural language processing tasks: tagging, grapheme-to-phoneme conversion, and pp-attachment. The results show that forgetting individual training items, however 'improbable' they may be, is indeed harmful. Furthermore, they show that combining lazy learning with training set editing techniques (based on typicality and other regularity criteria) also leads to worse generalization results. I will conclude that forgetting, either by abstracting from the training data or by editing exceptional training items in lazy learning is harmful to generalization accuracy, and will attempt to provide an explanation for these unexpected results.
Optimal subset-difference broadcast encryption with free riders
Authors: Murat Ak, Kamer Kaya, Ali Aydın Selçuk
Venue: Information Sciences: an International Journal (2009)

Broadcast encryption (BE) deals with secure transmission of a message to a group of receivers such that only an authorized subset of receivers can decrypt the message. The transmission cost of a BE system can be reduced considerably if a limited number of free riders can be tolerated in the system. In this paper, we study the problem of how to optimally place a given number of free riders in a subset-difference (SD)-based BE system, which is currently the most efficient BE scheme in use and has also been incorporated in standards, and we propose a polynomial-time optimal placement algorithm and three more efficient heuristics for this problem. Simulation experiments show that SD-based BE schemes can benefit significantly from the proposed algorithms.
The effect of corpus size on case frame acquisition for discourse analysis
Authors: Ryohei Sasano, Daisuke Kawahara, Sadao Kurohashi
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

This paper reports the effect of corpus size on case frame acquisition for discourse analysis in Japanese. For this study, we collected a Japanese corpus consisting of up to 100 billion words, and constructed case frames from corpora of six different sizes. Then, we applied these case frames to syntactic and case structure analysis, and zero anaphora resolution. We obtained better results by using case frames constructed from larger corpora; the performance was not saturated even with a corpus size of 100 billion words.
Color Recovering Based on Dichromatic Reflection Model and Finite Dimensional Linear Model
Authors: Yonghong Long, Haixia Luo, Aichun Yi
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

This paper proposes a new illumination estimation scheme for color recovering based on dichromatic reflection model and finite-dimensional linear model. According to the dichromatic reflection model, the surface spectral reflectance is described as the sum of interface reflectance and body reflectance. The interface component is used to estimate the spectral power distribution of the illuminant. Firstly, the illumination chromaticity is estimated by the intersection of two color-signal planes from two inhomogeneous surfaces, based on which we can get the illuminant spectral power distribution. Then the original images are able to be recovered to the image with standard illuminant D65 using the finite-dimensional model. From the experimental results, the proposed method performs well in recovering colors of images taken under chromatic illuminant.
The input-interface of Webcam applied in 3D virtual reality systems
Authors: Huey-Min Sun, Wen-Lin Cheng
Venue: Computers Education (2009)

Our research explores a virtual reality application based on Web camera (Webcam) input-interface. The interface can replace with the mouse to control direction intention of a user by the method of frame difference. We divide a frame into nine grids from Webcam and make use of the background registration to compute the moving object. In order to make this technology apply to 3D virtual reality system, we use the Virtools Dev to build virtual scenes and the Microsoft Visual C++ to build this interface. We also use the MySQL database management system to access users' data and the displaying data. We implement a number of Building Blocks (BB) to support Virtools Dev for using the database management system and the Webcam input-interface in this composite system. The results of research are expected to the digital content industries such that users can easy to use the input-interface to control browsing the virtual reality. Our system can supply interactive digital content, photographs, and access the questions from the database management system. In addition, the system provides the browsing mold, the question mold, and the course content describing mold with the input-interface. In order to explore the intention of users for using the system, we design the questionnaire based on the technology acceptance model (TAM). In our empirical study, we find that perceived playfulness is positive association with attitude toward using. Interface style is positive association with perceived ease of use.
The Research of ERP Development Based on Network Era
Authors: Xu Zhaoyong
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Enterprise Resource Planning (ERP) is the system solution to manage the enterprise resource, which takes the modern management thought as the instruction, uses the information technology, reasonably plans the enterprise resources disposition. But under the network condition, ERP must enrich its function; also improve its application and management. The paper proposes the idea and the countermeasure to develop the ERP in six aspects in order to promote the competitiveness of enterprise's China.
An Interval-Based Knowledge Model and Query Language for Temporal Information
Authors: He Huang, Zhongzhi Shi, Xiaoxiao He, Lirong Qiu, Jiewen Luo
Venue: Multi-Agent Systems for Society: 8th Pacific Rim International Workshop on Multi-Agents, PRIMA 2005, Kuala Lumpur, Malaysia, September 26-28, 2005, Revised Selected Papers (2009)

Time plays a crucial role in describing dynamic domain and resources on the Web. Most of current ontology languages, without notion of time or change, can only describe domain knowledge in a static sense. In order to bring structure to time-varying information, we propose an interval-based knowledge model (IKM), which is composed of a temporal knowledge schema, temporal integrity constraints and an interpretation structure. In the IKM, a group of expressive temporal constructs are provided to capture the temporal features of concepts, attributes and relationships; a group of rules are defined to enrich expressivity of the model; formal meaning is given to the model via an interpretation with model-theoretical semantics. A high-level query language is defined on the model, too.
Multilingual collocation extraction: issues and solutions
Authors: Violeta Seretan, Eric Wehrli
Venue: Proceedings of the Workshop on Multilingual Language Resources and Interoperability (2006)

Although traditionally seen as a language-independent task, collocation extraction relies nowadays more and more on the linguistic preprocessing of texts (e.g., lemmatization, POS tagging, chunking or parsing) prior to the application of statistical measures. This paper provides a language-oriented review of the existing extraction work. It points out several language-specific issues related to extraction and proposes a strategy for coping with them. It then describes a hybrid extraction system based on a multilingual parser. Finally, it presents a case-study on the performance of an association measure across a number of languages.
Development of a Novel Platform for Greater Situational Awareness in the Urban Military Terrain
Authors: Stephen D. Prior, Siu-Tsen Shen, Anthony S. White, Siddharth Odedra, Mehmet Karamanoglu, Mehmet Ali Erbil, Tom Foran
Venue: Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009 (2009)

The conflicts in Afghanistan and Iraq and the more recent war in the Gaza Strip have emphasized the need for novel platforms which provide for greater situational awareness in the urban terrain. Without intelligent systems, which can accurately provide real-time information, collateral damage to property will result, together with unnecessary civilian deaths. This situation is exacerbated by the fact that within the next decade 75% of the world's population will be living in urban areas. This paper outlines the current state of unmanned aerial vehicles throughout the world and presents a novel design of a multiple rotary wing platform which has great potential for both military and civilian application areas.
Mining Frequent Gradual Itemsets from Large Databases
Authors: Lisa Di-Jorio, Anne Laurent, Maguelonne Teisseire
Venue: Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII (2009)

Mining gradual rules plays a crucial role in many real world applications where huge volumes of complex numerical data must be handled, e.g., biological databases, survey databases, data streams or sensor readings. Gradual rules highlight complex order correlations of the form "The more/less X, then the more/less Y". Such rules have been studied since the early 70's, mostly in the fuzzy logic domain, where the main efforts have been focused on how to model and use such rules. However, mining gradual rules remains challenging because of the exponential combination space to explore. In this paper, we tackle the particular problem of handling huge volumes by proposing scalable methods. First, we formally define gradual association rules and we propose an original lattice-based approach. The GRITE algorithm is proposed for extracting gradual itemsets in an efficient manner. An experimental study on large-scale synthetic and real datasets is performed, showing the efficiency and interest of our approach.
A Framework to Support Interoperability among Web Service Registries
Authors: Cheng Zeng, Keqing He, Bing Li
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

This paper presents the framework to support the interoperability among different Web Service Registries (WSRs). The current degree of interoperability, which is now at the syntax level, cannot ensure the cooperation among WSRs. Therefore, it is important to enhance the degree of interoperability for improving the flexibility among WSRs. As a solution to the problem of interoperability, we rely on ISO/IEC 19763-3: MFI4OR (Metamodel framework for interoperability: Metamodel for Ontology Registration) to create the Web service registry model based on Double-ontology pattern. One of them is WSRO (Web Service Reference Ontology) which is viewed as a registry model of web service in the WSR and provides the theoretical foundation of the interoperability among different WSRs; another is Domain Ontology (DO), which is used to annotate web service for enhancing the semantic query. Based on Double-ontology pattern, the semantic interoperation among WSRs is clearly improved.
Matchmaker: Interpersonal Touch in Gaming
Authors: Cody Watts, Ehud Sharlin, Peter Woytiuk
Venue: Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development (2009)

Acts of interpersonal touch --- a touch shared between two people --- are used by couples to communicate in a simple and emotionally intimate way. In this paper, we argue that the intimacy afforded by acts of interpersonal touch can be used in computer entertainment to support enjoyable and engaging activities for couples. To support this notion, we have developed Matchmaker; a two-player, cooperative tabletop video game based on themes of love and romance. Matchmaker's gameplay is directly controlled by a set of collaborative tabletop interaction techniques, as well as by acts of interpersonal touch between its players. In this paper we present a detailed description of Matchmaker's design and the results of an exploratory user suggesting that Matchmaker is enjoyable to play and that its use of interpersonal touch contributes to players' enjoyment.
Research on Salinity Detecting Based on Embedded CAN-Ethernet Gateway
Authors: Xingqiao Liu, Xiaoxia Gong, Yang Liu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

According to the principle of salinity measurement by conductance method, a kind of salinity detecting instrument using the processor SOC MCU C8051F040 was conducted in this paper, and this instrument worked as a intelligent detecting node on CAN bus. A kind of CAN-Ethernet gateway was designed based on ARM7 microprocessor LPC2292. The real-time operating system µC/OS-II was used as the software platform. The Web Server was built based on TCP/IP protocol stack which was transplanted on the embedded system. A method of software compensation was proposed basing on the fact that temperature influences the conductivity of water. In addition, instantaneous temperature was measured and its influence on salinity was removed off. Therefore, PT100 thermoelectric resistance was used in temperature measuring circuit. The experiment shows that field detecting instrument has high measuring accuracy, strong anti-interference ability and stable operation.
Designing Laser Gesture Interface for Robot Control
Authors: Kentaro Ishii, Shengdong Zhao, Masahiko Inami, Takeo Igarashi, Michita Imai
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

A laser pointer can be a powerful tool for robot control. However, in the past, their use in the field of robotics has been limited to simple target designation, without exploring their potential as versatile input devices. This paper proposes to create a laser pointer-based user interface for giving various instructions to a robot by applying stroke gesture recognition to the laser's trajectory. Through this interface, the user can draw stroke gestures using a laser pointer to specify target objects and commands for the robot to execute accordingly. This system, which includes lasso and dwelling gestures for object selection, stroke gestures for robot operation, and push-button commands for movement cancellation, has been refined from its prototype form through several user-study evaluations. Our results suggest that laser pointers can be effective not only for target designation but also for specifying command and target location for a robot to perform.
Parallelized Architecture of Multiple Classifiers for Face Detection
Authors: Junguk Cho, Bridget Benson, Shahnam Mirzaei, Ryan Kastner
Venue: Proceedings of the 2009 20th IEEE International Conference on Application-specific Systems, Architectures and Processors (2009)

This paper presents a parallelized architecture of multiple classifiers for face detection based on the Viola and Jones object detection method. This method makes use of the AdaBoost algorithm which identifies a sequence of Haar classifiers that indicate the presence of a face. We describe the hardware design techniques including image scaling, integral image generation, pipelined processing of classifiers, and parallel processing of multiple classifiers to accelerate the processing speed of the face detection system. Also we discuss the parallelized architecture which can be scalable for configurable device with variable resources. We implement the proposed architecture in Verilog HDL on a Xilinx Virtex-5 FPGA and show the parallelized architecture of multiple classifiers can have 3.3× performance gain over the architecture of a single classifier and an 84× performance gain over an equivalent software solution.
An intelligent system for Chinese calligraphy
Authors: Songhua Xu, Hao Jiang, Francis C. M. Lau, Yunhe Pan
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

Our work links Chinese calligraphy to computer science through an integrated intelligence approach. We first extract strokes of existent calligraphy using a semi-automatic, two-phase mechanism: the first phase tries to do the best possible extraction using a combination of algorithmic techniques; the second phase presents an intelligent user interface to allow the user to provide input to the extraction process for the difficult cases such as those in highly random, cursive, or distorted styles. Having derived a parametric representation of calligraphy, we employ a supervised learning based method to explore the space of visually pleasing calligraphy. A numeric grading method for judging the beauty of calligraphy is then applied to the space. We integrate such a grading unit into an existent constraint-based reasoning system for calligraphy generation, which results in a significant enhancement in terms of visual quality in the automatically generated calligraphic characters. Finally, we construct an intelligent calligraphy tutoring system making use of the above. This work represents our first step towards understanding the human process of appreciating beauty through modeling the process with an integration of available AI techniques. More results and supplementary materials are provided at http://www.cs.hku.hk/~songhua/calligraphy.