ppxscal/embedding_network huggingface dataset:
A Security Model for Mobile Processes
Authors: Michael Decker
Venue: Proceedings of the 2008 7th International Conference on Mobile Business (2008)

Technologies like mobile devices (e.g. PDAs, smartphones, notebooks)and wireless data communication (e.g. GPRS, UMTS, WiFi) have a great potential for the improvement of mobile processes, e.g. by enabling access to time-critical information and preventing media disruptions. But the usage of these technologies leads also to specific challenges, particularly with regard to security and usability. One approach to deal with mobile-specific security concerns is to control access to functions provided by mobile information systems depending on the current location of the user, e.g. a travelling salesman should only be allowed to enter a customer's order when he currently resides at the premises of that customer. A formal model to write down such rules is called "security model". There are already some security models which take the user's location into account when deciding which functions of a system a certain user is allowed to use but they are process-agnostic, i.e. location-restrictions at process level cannot be expressed. In literature also security models for process-aware information system can be found but they don't consider location. In our work we therefore propose a security model for mobile processes based on an elicitation of requirements.
Social norm emergence in virtual agent societies
Authors: Bastin Tony Roy Savarimuthu, Maryam Purvis, Martin Purvis
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

The advent of virtual environments such as SecondLife call for a distributed approach for norm emergence and spreading. In open virtual environments, monitoring various interacting agents (avatars), using a centralized authority might be computationally expensive. The number of possible states and actions of an agent could be huge. An approach for sustaining order and smoother functioning of these environments can be facilitated through norms. Agents can generate norms based on interactions. In particular, those social norms that incur certain cost to an individual agent but benefit the whole society are more interesting than those benefit both the agent and the society. The problem is that the selfish agents might not be willing to share the norm adherence cost. In this work, we experiment with notion proposed by Axelrod that social norms are best at preventing small defections where the cost of enforcement is low. We also study how common knowledge can be used to faciliate the overall benefit of the society. We believe our work can be used to facilitate norm emergence in virtual online societies.
Interview with Guido van Rossum
Authors: James Gray
Venue: Linux Journal (2008)

The new Python 3000 is bounding beyond Python 2. Python creator Guido van Rossum explains why you've got to try it.
Implementing Parametric Reinforcement Learning in Robocup Rescue Simulation
Authors: Omid Aghazadeh, Maziar Ahmad Sharbafi, Abolfazl Toroghi Haghighat
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

Decision making in complex, multi agent and dynamic environments such as Rescue Simulation is a challenging problem in Artificial Intelligence. Uncertainty, noisy input data and stochastic behavior which is a common difficulty of real time environment makes decision making more complicated in such environments. Our approach to solve the bottleneck of dynamicity and variety of conditions in such situations is reinforcement learning. Classic reinforcement learning methods usually work with state and action value functions and temporal difference updates. Using function approximation is an alternative method to hold state and action value functions directly. Many Reinforcement learning methods in continuous action and state spaces implement function approximation and TD updates such as TD, LSTD, iLSTD, etc. A new approach to online reinforcement learning in continuous action or state spaces is presented in this paper which doesn't work with TD updates. We have named it Parametric Reinforcement Learning. This method is utilized in Robocup Rescue Simulation / Police Force agent's decision making process and the perfect results of this utilization have been shown in this paper. Our simulation results show that this method increases the speed of learning and simplicity of use. It has also very low memory usage and very low costing computation time.
Composition of Motion Description Languages
Authors: Wenqi Zhang, Herbert G. Tanner
Venue: Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control (2008)

We introduce a new formalism to compose interacting heterogeneous systems described by extended motion description languages (mdles). The novelty lies in producing a composed system whose behavior could be a superset of the union of the behaviors of its generators. In the class of systems modeled using mdles, the composition operator is closed, and language equivalence can be decidable. Our approach consists of representing mdles as normed processes, recursively defined as a guarded system of recursion equations in restricted Greibach Normal Form over a basic process algebra. Basic processes have well defined semantics for composition, which we exploit to establish the properties of our composed mdles.
PhotoSim: Tightly Integrating Image Analysis into a Photo Browsing UI
Authors: Ya-Xi Chen, Andreas Butz
Venue: Proceedings of the 9th international symposium on Smart Graphics (2008)

Current photo browsers for personal photo collections mostly use the folder structure or camera-recorded time stamps as the only ordering principle. Some also allow manually provided meta-data (tags) for organizing and retrieving photos, but currently, only professional tools allow a pre-grouping of photos by image similarity. We believe that similarity is indeed a useful criterion both for image retrieval and casual browsing, and that the tight integration of content analysis techniques in media UIs in general can lead to more powerful UIs. In this paper we present a prototype, in which we have tightly integrated image analysis techniques and user feedback into a zoomable user interface for browsing and sorting digital photos. We have discussed our system with domain experts and received encouragement as well as valuable ideas for future research.
Hash algorithm design for a non-uniformly distributed database
Authors: Wei-Ming Lin
Venue:  (2008)

Computer networks have continued to make substantial advances in the past couple of decades, through better technologies and methodologies employed. As the usage of the networks continues to increase exponentially, high throughput of the networks has to be maintained with various performance-efficient network algorithms. IP address lookup is one of the processes, the performance of which dearly affects the overall network performance. Hashing has been widely used for fast IP address lookup due to its simplicity, but hashing has commonly assumed an address set with uniformly distributed key values. Performance from these known hashing techniques is far from optimal due to the high non-uniformity in actual IP address distribution. In this dissertation, we present a new methodology to deal with hashing on non-uniform distributed database. The new methodology is based on determining the "bit-wise" distribution" of database bits. With the knowledge of the bit-wise distribution hashing can be improved by being able to calculate how an XOR operator will alter the randomness of the hashing algorithm. We show how our methodology can be applied to an ad-hoc hashing algorithm or a predefined XOR folding hashing algorithm. Bit-duplication techniques are also proposed to further increase the hash randomness. An extensive analysis on correlation among hash keys is also performed to look for the best hash combinations. Simulation results show a very significant improvement in performance on randomly generated addresses and several sample IP address databases over the standard classical approaches to hashing.
Characterization of Service Times Burstiness of IEEE 802.11 DCF
Authors: Francesco Vacirca, Andrea Baiocchi
Venue: Proceedings of the 5th international conference on Wired/Wireless Internet Communications (2007)

First order metrics (throughput, average delay) of the IEEE 802.11 DCF MAC protocol have been extensively analyzed. The service process of the same protocol has not received the same attention, although it is known that it might be bursty. We develop a simple and accurate Markov model that allows a complete characterization of the service process of an 802.11 BSS. A major result of simulations is that correlation between consecutive service times is negligible, hence the service process can be safely described as a renewal process. The analytic model highlights that service burstiness lies essentially in the doubling of the contention window after a collision up to very large values. The trade-off between average throughput and service burstiness is obtained from the model.
A Self-organizing Neural System for Background and Foreground Modeling
Authors: Lucia Maddalena, Alfredo Petrosino
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

In this paper we propose a system that is able to detect moving objects in digital image sequences taken from stationary cameras and to distinguish wether they have eventually stopped in the scene. Our approach is based on self organization through artificial neural networks to construct a model of the scene background that can handle scenes containing moving backgrounds or gradual illumination variations, and models of stopped foreground layers that help in distinguishing between moving and stopped foreground regions, leading to an initial segmentation of scene objects. Experimental results are presented for color video sequences that represent typical situations critical for video surveillance systems.
The Application of Cell-Based Clustering Algorithm Dealing with Radar Data Fusion
Authors: Hongping Shu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

Cell-based clustering method using cell data structure, so all operations are clustering on the cell. Based on the processing of the observation data clustering, algorithms about data fusion and objective tracking are discussed. Matrixes of filter formula, such as the observation transfer-matrix, observation noise covariance matrix, the initial value of estimation covariance matrix, and observation matrix have been confirmed. The simulation result indicated that, the filter track trace is good after the cell clustering, the cell clustering have the good function in the processing observed value noise aspect.
A self-tuning disk striping system for parallel input/output
Authors: Daniel A. Reed
Venue:  (2007)

In this thesis, we propose a self-tuning approach for automatically selecting and refining the file system's striping parameters based on application access patterns. The technique presented here relies on the monitoring of application I/O requests and the application of an analytic model to determine file striping parameters that improve overall file system performance. The application I/O requests are characterized by their size, type, duration and inter-arrival times, and clustered into representative groups to determine typical request sizes. Then, an analytical striping model is used to determine potential performance improvements. Input parameters to this model include the disk and network system characteristics, and knowledge of application I/O access pattern behavior. The output of the model is the estimated response time as a function of the request size, request rate and stripe depth. An optimum stripe depth that minimizes the average response time can be calculated from this output. Two file restriping methods are studied, and a 3-competitive online algorithm for determining when to restripe is presented. Finally, we present results gathered from executing three high-performance scientific applications, WaveToy, sPPM and Montage, on three different computer clusters. Our results show that I/O performance for the WaveToy and sPPM applications can be improved significantly by striping their output files across several disks using a stripe depth derived from applying the restriping model to the application's I/O access patterns.
Optimal trajectory planning for mobile robots
Authors: David A. Castanon
Venue:  (2008)

Given growing emphasis on robot autonomy, the problem of planning a trajectory for these autonomous systems in a complex environment has become increasingly important. The objective of this research is to solve trajectory generation and optimization problems for mobile robot systems with both single and multiple goals. Considering the complexity of general trajectory planning problems, we concentrate mainly on two dynamic models: a holonomic system where velocity is a control variable and a nonholonomic system proposed by Dubins with constant velocity and constrained turning radius. For the simple holonomic model, we focus on computation of optimal trajectories with complex objective functions. We use a stochastic control framework to obtain characterizations of optimal trajectories as solutions of Hamilton-Jacobi-Bellman equations. Based on either upwind schemes or value iteration methods, we develop and evaluate alternative numerical methods for both isotropic (velocity-independent) and anisotropic (velocity-dependent) cost models. For the Dubins' vehicle model, we extend the results of Dubins and others to solve for minimum-time trajectories with diverse path and terminal constraints, characterizing solutions using Pontryagin's Maximum Principle. A direct application of these local shortest-path solutions is the Dubins' Traveling Salesman problem (DTSP), where the goal is to find the shortest trajectory for a Dubins' vehicle given a number of locations. We extend our analytic solutions to two-point and three-point Dubins' shortest path problems to obtain a receding horizon algorithm that outperforms alternative algorithms proposed in the literature when the visiting order is known. We also combine these algorithms with existing TSP heuristics to obtain improved algorithms when the order is not known. We also studied trajectory planning for Dubins' vehicles in the presence of moving obstacles. For stationary obstacles and holonomic vehicles, probabilistic algorithms such as rapidly-exploring random trees (RRTs) can provide guarantees of finding a path to a goal. We developed a variation of RRTs for time-varying obstacles and Dubins' dynamics. We prove probabilistic completeness for this algorithm, establishing that a path will be found if one exists. We also compared our approach with an alternative, the probabilistic roadmap algorithm, and established that our algorithm yields improvements for these problems.
The Effects of Agent Nonverbal Communication on Procedural and Attitudinal Learning Outcomes
Authors: Amy L. Baylor, Soyoung Kim
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

This experimental study investigated the differential effects of pedagogical agent nonverbal communication on attitudinal and procedural learning. A 2x2x2 factorial design was employed with 237 participants to investigate the effect of type of instruction (procedural, attitudinal), deictic gesture (presence, absence), and facial expression (presence, absence) on learner attitudes, agent perception (agent persona, gesture, facial expression), and learning. Results indicated that facial expressions were particularly valuable for attitudinal learning, and were actually detrimental for procedural learning. Similarly, gestures were perceived as more valuable for students in the procedural module, even though they did not directly enhance recall.
Pro Spring 2.5
Authors: Jan Machacek, Jessica Ditt, Aleksa Vukotic, Anirvan Chakraborty
Venue: Books For Professionals By Professionals (2008)

The Spring Framework 2.5 release reflects the state of the art in both the Spring Framework and enterprise Java frameworks as a whole. A guidebook to this critical tool is necessary reading for any conscientious Java developer. Rob Harrop, author of Pro Spring The move from socalled heavyweight architectures, such as Enterprise JavaBeans, toward lightweight frameworks, like Spring, has not stopped since Pro Spring was published by Rob Harrop and Jan Machacek in 2005; in fact, its picked up pace. The Spring Framework remains the leader in this move and provides a platform on which you can build your own applications and services. Pro Spring 2.5 covers the new features of Spring 2.5, but moreover, it is focused on the best practices and core standards of contemporary Spring development. As members of the Spring development team at Cake Solutions, the author team brings extensive practical experience gained from working with Spring since version 1.0 and delivering successful systems on top of it. Learn the approaches that really matter in a professional, enterpriselevel environment, so you can apply them to your projects today, safe in the knowledge that they just work. What Youll Learn Discover how to use Springs Inversion of Control (IoC). Explore Springs excellent aspectoriented programming (AOP) support, including Spring 2.5s new @AspectJ feature. Find out how to use Springs dynamic scripting language features, Spring design patterns, and performance tuning in Spring applications. Learn what really works in realworld Spring development. Understand Springs support for the JDBC framework, Hibernate, the Quartz enterprise scheduler, declarative transaction management, and much more. Master Springs welldesigned MVC framework and add AJAX to your Spring web applications to create flexible, efficient, and manageable applications using the best techniques available. Who is this book for? Enterprise Java, J2EE/Java EE developers looking to learn and use the Spring metaframework, the now growing, leading alternative to J2EE/Java EE About the Apress Pro Series The Apress Pro series books are practical, professional tutorials to keep you on and moving up the professional ladder. You have gotten the job, now you need to hone your skills in these tough competitive times. The Apress Pro series expands your skills and expertise in exactly the areas you need. Master the content of a Pro book, and you will always be able to get the job done in a professional development project. Written by experts in their field, Pro series books from Apress give you the hard-won solutions to problems you will face in your professional programming career.
P2P Reputation Systems Credibility Analysis: Tradeoffs and Design Decisions
Authors: Eleni Koutrouli, Aphrodite Tsalgatidou
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

Peer-to-Peer (P2P) systems are distributed self-organized systems without a controlling entity where peers need to make trust decisions regarding who they will transact with. P2P reputation systems exploit past transactional information to provide members of P2P networks with measures which will help them make such trust decisions. However, these systems are vulnerable themselves to various types of attacks which can distort their functionality and credibility. A number of defense mechanisms have been proposed to counteract specific attacks, but research lacks an exploration of how these mechanisms can be used together so as to provide the highest degree of credibility. In this paper, after presenting the basic attacks and defense mechanisms concerning P2P reputation systems, we analyze the tradeoffs between different credibility enhancing mechanisms and ways to achieve the right balances. Our aim is to help reputation systems designers to incorporate in their systems the right mechanisms or the right combinations of mechanisms against the threats of the specific reputation systems.
Exploratory Spatial Analysis of Illegal Oil Discharges Detected off Canada's Pacific Coast
Authors: Norma Serra-Sogas, Patrick O'Hara, Rosaline Canessa, Stefania Bertazzon, Marina Gavrilova
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

In order to identify a model that best predicts spatial patterns it is necessary to first explore the spatial properties of the data that will be included in a predictive model. Exploratory analyses help determine whether or not important statistical assumptions are met, and potentially lead to the definition of spatial patterns that might exist in the data. Here, we present results from exploratory analyses based on detected illegal oil spills by the National Aerial Surveillance Program (NASP) in Canada's Pacific Region, and marine vessel traffic, the possible source of these oil discharges. We identify and describe spatial properties of the oil spills, surveillance flights and marine traffic, to ultimately identify to most suitable predictive model to map areas where these events are more likely to occur.
Real Time Eyes Tracking and Classification for Driver Fatigue Detection
Authors: M. Imran Khan, A. Bin Mansoor
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

In this paper, we propose a vision-based real time algorithm for driver fatigue detection. Face and eyes of the driver are first localized and then marked in every frame obtained from the video source. The eyes are tracked in real time using correlation function with an automatically generated online template. The proposed algorithm can detect eyelids movement and can classify whether the eyes are open or closed by using normalized cross correlation function based classifier. If the eyes are closed for more than a specified time an alarm is generated. The accuracy of algorithm is demonstrated using real data under varying conditions for people with different gender, skin colors, eye shapes and facial hairs.
Information Fusion in Multimedia Information Retrieval
Authors: Jana Kludas, Eric Bruno, Stéphane Marchand-Maillet
Venue: Adaptive Multimedial Retrieval: Retrieval, User, and Semantics: 5th International Workshop, AMR 2007, Paris, France, July 5-6, 2007 Revised Selected Papers (2007)

In retrieval, indexing and classification of multimedia data an efficient information fusion of the different modalities is essential for the system's overall performance. Since information fusion, its influence factors and performance improvement boundaries have been lively discussed in the last years in different research communities, we will review their latest findings. They most importantly point out that exploiting the feature's and modality's dependencies will yield to maximal performance. In data analysis and fusion tests with annotated image collections this is undermined.