ppxscal/embedding_network huggingface dataset:
An Exploratory Study on E-Commerce Strategy in Small and Medium Sized Enterprises: An Ecological Niches View
Authors: Shen Chenglin, Zhang Xinxin
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

Concept of ecological niche is introduced to analyze the relations of e-commerce and traditional business, the latent ecological niche and actual ecological niche, large sized enterprise and small and medium sized enterprise (SME) in this paper. The e-commerce adoptions in SMEs and their attitudes towards the use of strategies were examined. Then four strategies of e-commerce for SMEs based on Niche Theory was put forward, namely dislocation management strategies, value innovation strategies, resources expansion strategies, and utilization of the third-party e-commerce service platform strategies. Finally we suggest that SMEs within the different niches should frame different strategies to develop the e-commerce in future.
Scenario Based Mapping of Dynamic Applications on MPSoC: A 3D Graphics Case Study
Authors: Narasinga Rao Miniskar, Elena Hammari, Satyakiran Munaga, Stylianos Mamagkakis, Per Gunnar Kjeldsberg, Francky Catthoor
Venue: Proceedings of the 9th International Workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation (2009)

Modern multimedia applications are becoming increasingly dynamic. The state-of-the-art scalable 3D graphics algorithms are able to adapt at run-time their hardware resource allocation requests according to input, resource availability and a number of quality metrics. Additionally, the resource management mechanisms are becoming more dynamic themselves and are able to cope efficiently at run-time with these varying resource requests, available hardware resources and competing requests from other applications. In this paper, we study the dynamic resource requests of the Wavelet Subdivision Surfaces (WSS) based scalable 3D graphics application. We also show how to schedule its computational resources at run-time with the use of the Task Concurrency Management (TCM) methodology and the System Scenario based approach on MPSoC platform with very heterogeneous Processing Elements (including RISC, VLIW and FPGA accelerator resources).
The Elliptic Curve Discrete Logarithm Problem and Equivalent Hard Problems for Elliptic Divisibility Sequences
Authors: Kristin E. Lauter, Katherine E. Stange
Venue: Selected Areas in Cryptography: 15th International Workshop, SAC 2008, Sackville, New Brunswick, Canada, August 14-15, Revised Selected Papers (2009)

We define three hard problems in the theory of elliptic divisibility sequences (EDS Association, EDS Residue and EDS Discrete Log), each of which is solvable in sub-exponential time if and only if the elliptic curve discrete logarithm problem is solvable in sub-exponential time. We also relate the problem of EDS Association to the Tate pairing and the MOV, Frey-Rück and Shipsey EDS attacks on the elliptic curve discrete logarithm problem in the cases where these apply.
Security analysis of mCrypton proper to low-cost ubiquitous computing devices and applications
Authors: Jong Hyuk Park
Venue: International Journal of Communication Systems (2009)

mCrypton, which is a mini-version of Crypton, is a 64-bit block cipher with three key size options (64 bits, 96 bits, 128 bits). It was designed for use in low-cost ubiquitous wireless devices and resource-constrained tiny devices such as low-cost Radio-Frequency Identification tags and sensors in Ubiquitous Sensor Network. In this paper we show that 8-round mCrypton with 128-bit key is vulnerable to related-key rectangle attack. We first describe how to construct two related-key truncated differentials on which 7-round related-key rectangle distinguisher is based and then we exploit it to attack 8-round mCrypton. This attack requires 246 dada and 246 time complexities, which is faster than exhaustive search. This is the first known cryptanalytic result on mCrypton. Copyright &copy; 2009 John Wiley & Sons, Ltd. In this paper, we show that 8-round mCrypton with 128-bit key is vulnerable to related-key rectangle attack. We first describe how to construct two related-key truncated differentials on which 7-round related-key rectangle distinguisher is based and then we exploit it to attack 8-round mCrypton. This attack requires 246 dada and 246 time complexities which is faster than exhaustive search. This is the first known cryptanalytic result on mCrypton. Copyright &copy; 2009 John Wiley & Sons, Ltd.
High-Resolution Adaptive PET Imaging
Authors: Jian Zhou, Jinyi Qi
Venue: Proceedings of the 21st International Conference on Information Processing in Medical Imaging (2009)

While the performance of small animal PET systems has been improved impressively in terms of spatial resolution and sensitivity, demands for further improvements remain high with growing number of applications. Here we propose a novel PET system design that integrates a high-resolution detector into an existing PET system to obtain higher-resolution images in a target region. The high-resolution detector will be adaptively positioned based on the detectability or quantitative accuracy of a feature of interest. The proposed system will be particularly effective for studying human cancers using animal models where tumors are often grown near the skin surface and therefore permit close contact with the high resolution detector. It will also be useful for the high-resolution brain imaging in rodents. In this paper, we present the theoretical analysis and Monte Carlo simulation studies of the performance of the proposed system.
Asset negotiation and trade-off support within a multi-agent environment
Authors: Brooke Abrahams, John Zeleznikow
Venue: Proceedings of the 1st International Working Conference on Human Factors and Computational Models in Negotiation (2008)

Argumentation theory is often used in multi agentsystems to facilitate autonomous agent reasoning and multi-agent interaction. The technology can also be used to develop online negotiation and mediation services by providing argument structures that assist parties involved in a dispute to resolve outstanding issues or avoid future disputes. While Alternative Dispute Resolution (ADR) represents a move from a fixed and formal process to a more flexible one, Online Dispute Resolution (ODR) moves ADR from a physical to a virtual place. The research aims to capitalise on the recent trend towards ODR by creating a JADE based multi-agent ODR environment. The utility functions and argument structures of two existing ODR applications are being re-deployed as Web based intelligent agents capable of intuitively coordinating during a negotiation. One agent uses expert knowledge of the Australian Family Law domain to recommend a percentage property split, while another uses heuristics and game theory and combines this split with a significance rating of items provided by each party, to allocate issues and advise upon possible trade-offs. The ultimate aim is to provide disputants with an integrated ODR environment offering a range of services to assist them in achieving fairer outcomes.
Proceedings of the 22nd annual ACM symposium on User interface software and technology
Venue: Symposium on User Interface Software and Technology (2009)

It is our great pleasure to welcome you to Victoria, British Columbia for UIST 2009, the Twenty-Second Annual ACM Symposium on User Interface Software and Technology. UIST is the premier forum for the presentation of research innovations in the software and technology of human-computer interfaces. Sponsored by ACM's special interest groups on computer-human interaction (SIGCHI) and computer graphics (SIGGRAPH), UIST brings together researchers and practitioners from many areas, including web and graphical interfaces, new input and output devices, information visualization, interactive displays, tangible computing and CSCW. The single track schedule, intimate size and comfortable surroundings make UIST an ideal place to exchange results as well as forge future collaborations. The call for papers attracted 183 full paper and tech note submissions from more than 20 countries. The program committee accepted 33 papers (18%) after a thorough review process. Each anonymous submission (a first for UIST 2009) was assigned primary and secondary program committee members. The primary committee member assigned at least two external reviewers for each submission and the secondary at least one. After receiving the reviews, both program committee members wrote a meta-review for every submission. Authors were then given all reviews and the opportunity to write a short rebuttal. The program committee then met in New York on June 5-6, 2009, to examine each submission and select the top papers. Submissions were finally accepted only after the authors provided a final revision addressing the committee's comments. This year's program includes an opening keynote by Stephen Macknik and Susana Martinez-Conde on the neurobiological basis of the perception of magic tricks, and a closing keynote by Eric Paulos on how communities of "expert amateurs" can effect change through the use of novel sensing and computing platforms. New this year is the Student Innovation Contest, which challenges student teams to develop new interactions on unique hardware. In this first year of the event, contestants will be supplied with a prototype pressure-sensitive keyboard designed by Microsoft Hardware. Posters, demos and the seventh annual Doctoral Symposium complete the program. These are described in the UIST program companion distributed at the conference.
A comparison of fraud cues and classification methods for fake escrow website detection
Authors: Ahmed Abbasi, Hsinchun Chen
Venue: Information Technology and Management (2009)

The ability to automatically detect fraudulent escrow websites is important in order to alleviate online auction fraud. Despite research on related topics, such as web spam and spoof site detection, fake escrow website categorization has received little attention. The authentic appearance of fake escrow websites makes it difficult for Internet users to differentiate legitimate sites from phonies; making systems for detecting such websites an important endeavor. In this study we evaluated the effectiveness of various features and techniques for detecting fake escrow websites. Our analysis included a rich set of fraud cues extracted from web page text, image, and link information. We also compared several machine learning algorithms, including support vector machines, neural networks, decision trees, naïve bayes, and principal component analysis. Experiments were conducted to assess the proposed fraud cues and techniques on a test bed encompassing nearly 90,000 web pages derived from 410 legitimate and fake escrow websites. The combination of an extended feature set and a support vector machines ensemble classifier enabled accuracies over 90 and 96% for page and site level classification, respectively, when differentiating fake pages from real ones. Deeper analysis revealed that an extended set of fraud cues is necessary due to the broad spectrum of tactics employed by fraudsters. The study confirms the feasibility of using automated methods for detecting fake escrow websites. The results may also be useful for informing existing online escrow fraud resources and communities of practice about the plethora of fraud cues pervasive in fake websites.
Multispectral Image Recognition Research Based on Biomimetic Pattern Recognition
Authors: Wenming Cao, Hao Feng
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

Studies on learning problems from geometry perspective have attracted an ever increasing attention in machine learning, leaded by Biomimetic Pattern Recognition on information geometry. Biomimetic Pattern Recognition is a new model of Pattern Recognition based on “matter cognition” instead of “matter classification”. This new model is much closer to the function of human being, than traditional statistical Pattern Recognition using “optimal separating” as its main principle.This paper proposes a high-dimensional descriptive way about multispectral image. Geometrical properties of high-dimensional structures underlying a set of samples are learned via successive projections from the higher dimension to the lower dimension until Clifford space, under guidance of the established properties and theorems in high-dimensional descriptive way. Specifically, we introduce a principle of homology continuity based on Clifford Algebra and provides a geometrical learning algorithm for specifying Clifford Algebra shapes, which is then applied to biomimetic pattern recognition. Experimental results are presented to show the efficiency of our theory.
The geometry of informational extensions
Authors: M. A. Gorelov
Venue: Automation and Remote Control (2009)

The paper studies strategy spaces in all possible informational extensions of a game with the natural metric. We show that all these extensions can be considered subspaces of a single space corresponding to a special quasi-informational extension that has a clear meaningful interpretation. We obtain an upper bound on the entropy of informational extensions.
Efficiency of techniques for mixed-space collaborative navigation
Authors: Aaron Stafford, Bruce H. Thomas, Wayne Piekarski
Venue: Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality (2008)

This paper describes the results of a study conducted to determine the efficiency of visual cues for a collaborative navigation task in a mixed-space environment. The task required a user with an exocentric view of a virtual room to navigate a fully immersed user with an egocentric view to an exit. The study compares natural hand-based gestures, a mouse-based interface and an audio only technique to determine their relative efficiency on task completion times. The results show that visual cue-based collaborative navigation techniques are significantly more efficient than an audio-only technique.
Energy-Efficient Communication in Multi-interface Wireless Networks
Authors: Stavros Athanassopoulos, Ioannis Caragiannis, Christos Kaklamanis, Evi Papaioannou
Venue: Proceedings of the 34th International Symposium on Mathematical Foundations of Computer Science 2009 (2009)

We study communication problems in wireless networks supporting multiple interfaces. In such networks, two nodes can communicate if they are close and share a common interface. The activation of each interface has a cost reflecting the energy consumed when a node uses this interface. We distinguish between the symmetric and non-symmetric case, depending on whether all nodes have the same activation cost for each interface or not. For the symmetric case, we present a (3/2 + ¿)---approximation algorithm for the problem of achieving connectivity with minimum activation cost, improving a previous bound of 2. For the non-symmetric case, we show that the connectivity problem is not approximable within a sublogarithmic factor in the number of nodes and present a logarithmic approximation algorithm for a more general problem that models group communication.
Volume Anomaly Detection in Data Networks: An Optimal Detection Algorithm vs. the PCA Approach
Authors: Pedro Casas, Lionel Fillatre, Sandrine Vaton, Igor Nikiforov
Venue: Traffic Management and Traffic Engineering for the Future Internet: First Euro-NF Workshop, FITraMEn 2008, Porto, Portugal, December 11-12, Revised Selected Papers (2009)

The crucial future role of Internet in society makes of network monitoring a critical issue for network operators in future network scenarios. The Future Internet will have to cope with new and different anomalies, motivating the development of accurate detection algorithms. This paper presents a novel approach to detect unexpected and large traffic variations in data networks. We introduce an optimal volume anomaly detection algorithm in which the anomaly-free traffic is treated as a nuisance parameter. The algorithm relies on an original parsimonious model for traffic demands which allows detecting anomalies from link traffic measurements, reducing the overhead of data collection. The performance of the method is compared to that obtained with the Principal Components Analysis (PCA) approach. We choose this method as benchmark given its relevance in the anomaly detection literature. Our proposal is validated using data from an operational network, showing how the method outperforms the PCA approach.
Parallel Object Motion Prediction in a Robotic Navigational Environment
Authors: Vijay S. Rajpurohit, M. M. Manohara Pai
Venue: Proceedings of the 10th International Conference on Parallel Computing Technologies (2009)

In a dynamic Robot navigation system , the Robot has to deal with multiple number of moving objects in the environment simultaneously. The control loop of Robot motion planning comprising of sense-plan-act cycle has very short duration . Predicting the next instance position (Short Term Prediction) and the trajectory (Long Term Prediction) of moving objects in a dynamic navigation system is a part of sense-plan-act cycle. With increase in the number of moving objects under observation, the performance of the prediction techniques reduce gradually. To overcome this drawback, in this paper we propose a parallel motion prediction algorithm to keep track of multiple number of moving objects within the Robotic navigational environment. The implementation of parallel algorithm is done on a cluster computing setup. Performance of the algorithm is tested for different test case scenarios with detailed analysis on efficiency and speedup.
Wavelet-based semblance filtering
Authors: G. R. J. Cooper
Venue: Computers Geosciences (2009)

Fourier transform-based semblance analysis compares two time series on the basis of their phase as a function of frequency. This approach can be extended using wavelets to allow the phase comparison of two datasets to be performed as a function of both time and wavelength. This paper further extends the previous work in two directions; firstly it demonstrates how to display the correlation between multiple (not just two) datasets, and secondly it introduces wavelet-based semblance filtering which allows a pair of datasets to be processed to extract components with any degree of correlation. Matlab source code is available from the IAMG server at www.iamg.org.
On the 7 Total Colorability of Planar Graphs with Maximum Degree 6 and without 4-cycles
Authors: Lan Shen, Yingqian Wang
Venue: Graphs and Combinatorics (2009)

Vizing and Behzad independently conjectured that every graph is (&#x0394;&#x00a0;+&#x00a0;2)-totally-colorable, where &#x0394; denotes the maximum degree of G. This conjecture has not been settled yet even for planar graphs. The only open case is &#x0394;&#x00a0;=&#x00a0;6. It is known that planar graphs with &#x0394;&#x00a0;&#x2265;&#x00a0;9 are (&#x0394;&#x00a0;+&#x00a0;1)-totally-colorable. We conjecture that planar graphs with 4&#x00a0;&#x2264;&#x00a0;&#x0394;&#x00a0;&#x2264;&#x00a0;8 are also (&#x0394;&#x00a0;+&#x00a0;1)-totally-colorable. In addition to some known results supporting this conjecture, we prove that planar graphs with &#x0394;&#x00a0;=&#x00a0;6 and without 4-cycles are 7-totally-colorable.
Poster abstract: Distributed fault detection using a recurrent neural network
Authors: Oliver Obst
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

In long-term deployments of sensor networks, monitoring the quality of gathered data is a critical issue. Over the time of deployment, sensors are exposed to harsh conditions, causing some of them to fail or to deliver less accurate data. If such a degradation remains undetected, the usefulness of a sensor network can be greatly reduced. We present an approach that learns spatio-temporal correlations between different sensors, and makes use of the learned model to detect misbehaving sensors by using distributed computation and only local communication between nodes. We introduce SODESN, a distributed recurrent neural network architecture, and a learning method to train SODESN for fault detection in a distributed scenario. Our approach is evaluated using data from different types of sensors and is able to work well even with less-than-perfect link qualities and more than 50% of failed nodes.
Indoor Position and Orientation for the Blind
Authors: Mauricio Sáenz, Jaime Sánchez
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services (2009)

This work proposes the study and design of mobile interfaces to identify the position and orientation of blind people in closed environments. Through this development we seek to reach a consensus on the use of a certain technology that would allow for the identification of the position and orientation of people within a closed space (such as a school or home) with the necessary infrastructure. A focus group was held in order to identify the users' problems with the navigation. In addition we made initial and final usability tests. The results of the usability evaluation showed that the interface designed was highly usable for blind users and that the technology designed worked to improve the indoor navigation of blind people.
An Improvement on the Model of Ontology-Based Semantic Similarity Computation
Authors: Xiaoyun Wang, Jianfeng Zhou
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

Semantic retrieval is one of keys to achieve knowledge retrieval, and it is based on the computation of semantic similarity. This paper improves the general model of conceptual semantic similarity computation by adding new elements to the model such as instances, the relationship between concepts and instances, and that between instances itself. It also presents the method of computing semantic similarity based on the new model. In the experiment, the method gets the excellent results, which fits our judgment.
AEGIS--attribute experimentation guiding improvement searches
Authors: Michael Racer, Robin Lovgren
Venue: Journal of Heuristics (2009)

The development of a quality heuristic is a challenging undertaking. While some work has been done to link solution quality and problem inputs, relatively little has been done to methodically address that linkage. This research, a meta-heuristic framework called AEGIS, is an initial attempt to integrate problem characteristics into the solution process itself. As the name implies, the goal is to provide guidance to the solution process, through a well-defined learning process. By utilizing statistical techniques and concepts, this study will demonstrate how such knowledge may be used to drive the function of the algorithm.
Robust Adaptive Control for Manipulator System
Authors: Xiaobo Sun
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

A robust adaptive controller is proposed in this paper, aiming at nonlinearity, time variance and multi-parameter couple of manipulator driven by motors. In this paper, the manipulator model is changed to be linear uncertain system and a filter with an integrator is designed. The updated laws of ideal current and unknown quantities are derived by the filter, and then the controller of motor is designed with the ideal current to be final control law. Based on the Lyapunov stability theory, this paper analyzes stability of robust adaptive controller and obtains the sufficient conditions of stability. The simulation results show that the system with proper controller parameters has good dynamic characteristic, tracking characteristic and robustness.