ppxscal/embedding_network huggingface dataset:
Security vulnerabilities in IEEE 802.22
Authors: Kaigui Bian, Jung-Min "Jerry" Park
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

Cognitive Radio (CR) is seen as one of the enabling technologies for realizing a new spectrum access paradigm, viz. Opportunistic Spectrum Sharing (OSS). IEEE 802.22 is the world's first wireless standard based on CR technology. It defines the air interface for a wireless regional area network (WRAN) that uses fallow segments of the licensed (incumbent) TV broadcast bands. CR technology enables unlicensed (secondary) users in WRANs to utilize licensed spectrum bands on a non-interference basis to incumbent users. The coexistence between incumbent users and secondary users is referred to as incumbent coexistence. On the other hand, the coexistence between secondary users in different WRAN cells is referred to as self-coexistence. The 802.22 draft standard prescribes several mechanisms for addressing incumbent- and self-coexistence issues. In this paper, we describe how adversaries can exploit or undermine such mechanisms to degrade the performance of 802.22 WRANs and increase the likelihood of those networks interfering with incumbent networks. The standard includes a security sublayer to provide subscribers with privacy, authentication, and confidentiality. Our investigation, however, revealed that the security sublayer falls short of addressing all of the key security threats. We also discuss countermeasures that may be able to address those threats.
Using data correlation to build an intrusion detection system
Authors: L. Romano, V. Vianello, S. D'antonio, S. Giordano
Venue: Proceedings of the 10th WSEAS international conference on Automation & information (2009)

Intrusion Detection Systems (IDSs) are one of the most adopted technologies when facing the issue of computer security. Regrettably, current solutions are far from perfect: i) either they produce a large number of false positives or they detect only known attacks; ii) they do not scale as the monitored infrastructure grows in terms of number of components and of exchanged data. Correlation of attack symptoms from diverse information sources has been proven to be an effective approach. In this paper, we propose an IDS solution which correlates information from diverse sources for improved performance, i.e. achieving high detection while reducing false positives. We discuss the key issues that result from adopting correlation of data coming from multiple sources and present the conceptual architecture that has been drown in the PHDS ("A Middleware Infrastructure for Real-Time Processing of Heterogeneous Data Streams") project to face such issues in a Security and Safety domain. We also present technological choices taken to implement such an architecture.
Plenary lecture II: topological theory of electromagnetic boundary problems
Authors: Guennadi A. Kouzaev
Venue: Proceedings of the 2nd conference on European computing conference (2008)

Spatio-temporal shapes of the electromagnetic field are defined by the boundary and initial conditions, and the most of them are derived by numerical methods due to the complexity of the solutions. In this lecture, the treatment of the boundary problems of the electromagnetism by topological methods is considered. The field is described by topological schemes. They are composed of the equilibrium points and separatrices of the field-force lines and derived qualitatively on the given boundary conditions using semi-analytical techniques. The developed approach is fast and for effective initial solutions of boundary electromagnetic problems. Additionally, the developed approach has been applied for the electromagnetic signal area. The digital information is carried by topologically different schemes of space-time field impulses composed of 3-D vector manifolds, and the signals have increased noise immunity. The prospective digital circuitry distinguishes the topologically modulated 4-D field shapes and compares them according to the Boolean and predicate logic. The developed approach is for advanced signaling and computing.
Algorithms, protocols and systems for remote observation using networked robotic cameras
Authors: Dezhen Song
Venue:  (2008)

Emerging advances in robotic cameras, long-range wireless networking, and distributed sensors make feasible a new class of hybrid teleoperated/autonomous robotic remote "observatories" that can allow groups of peoples, via the Internet, to observe, record, and index detailed activity occurred in remote site. Equipped with robotic pan-tilt actuation mechanisms and a high-zoom lens, the camera can cover a large region with very high spatial resolution and allows for observation at a distance. High resolution motion panorama is the most nature data representation. We develop algorithms and protocols for high resolution motion panorama. We discover and prove the projection invariance and achieve real time image alignment. We propose a minimum variance based incremental frame alignment algorithm to minimize the accumulation of alignment error in incremental image alignment and ensure the quality of the panorama video over the long run. We propose a Frame Graph based panorama documentation algorithm to manage the large scale data involved in the online panorama video documentation. We propose a on-demand high resolution panorama video-streaming system that allows on-demand sharing of a high-resolution motion panorama and efficiently deals with multiple concurrent spatial-temporal user requests. In conclusion, our research work on high resolution motion panorama have significantly improve the efficiency and accuracy of image alignment, panorama video quality, data organization, and data storage and retrieving in remote observation using networked robotic cameras.
Statistical global metabolic control analysis
Authors: Zelimir Kurtanjek
Venue: Proceedings of the 10th WSEAS international conference on Mathematics and computers in biology and chemistry (2009)

This work introduces the concept of global sensitivity based on simultaneous variation of a complete set of enzymes, metabolite concentrations, and cofactors in finite ranges of concentrations. Perturbations are defined by finite ranges of concentrations and corresponding probability density distributions. Effects of perturbations of the homeostatic state variables including input and output products of a considered flux, and cofactors on the flux analysis are evaluated. The flux sensitivities are determined as first and second order relative multidimensional variances. The first order effects are reflection of random perturbation of each individual enzyme, metabolite and cofactor. The dispersions of fluxes due to each perturbation are evaluated by numerical simulation and the Fourier Amplitude Sensitivity Test algorithm. The implications of the proposed theory are demonstrated by computer simulation of theoretical problem on regulation of branched metabolism pathway at steady state, and also unsteady control flux analysis based on experimental data of E. coli central metabolism upon perturbation by glucose impulse.
A Study on Improved Fuzzy Neural Network Controller for Air-Condition with Frequency Change
Authors: Shuqing Wang, Zipeng Zhang, Zhihuai Xiao, Xiaohui Yuan
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

The environment of room temperature is complicated and it is difficult to get precise mathematics model for the control of air-condition with frequency change. It is difficult using conventional fuzzy control way to control air-condition to get better control performance. Fuzzy neural network has strong fuzzy reasoning ability and learning ability, which can control air-condition with frequency change to get better control effect. In this paper, an improved fuzzy neural network controller is designed to control air-condition. In order to overcome the weakness of slow learning speed for fuzzy neural network, GAs is employed to optimize parameters of fuzzy neural network. In order to improve training speed and overcome the shortcoming of local optimization, the designed genetic algorithm is improved based on the control system. Simulating experiment shows that the designed controller has better controlling effect than other conventional fuzzy controller.
Discovering options from example trajectories
Authors: Peng Zang, Peng Zhou, David Minnen, Charles Isbell
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We present a novel technique for automated problem decomposition to address the problem of scalability in reinforcement learning. Our technique makes use of a set of near-optimal trajectories to discover options and incorporates them into the learning process, dramatically reducing the time it takes to solve the underlying problem. We run a series of experiments in two different domains and show that our method offers up to 30 fold speedup over the baseline.
k-ary search on modern processors
Authors: Benjamin Schlegel, Rainer Gemulla, Wolfgang Lehner
Venue: Proceedings of the Fifth International Workshop on Data Management on New Hardware (2009)

This paper presents novel tree-based search algorithms that exploit the SIMD instructions found in virtually all modern processors. The algorithms are a natural extension of binary search: While binary search performs one comparison at each iteration, thereby cutting the search space in two halves, our algorithms perform k comparisons at a time and thus cut the search space into k pieces. On traditional processors, this so-called k-ary search procedure is not beneficial because the cost increase per iteration offsets the cost reduction due to the reduced number of iterations. On modern processors, however, multiple scalar operations can be executed simultaneously, which makes k-ary search attractive. In this paper, we provide two different search algorithms that differ in terms of efficiency and memory access patterns. Both algorithms are first described in a platform independent way and then evaluated on various state-of-the-art processors. Our experiments suggest that k-ary search provides significant performance improvements (factor two and more) on most platforms.
The community is where the rapport is -- on sense and structure in the youtube community
Authors: Dana Rotman, Jennifer Golbeck, Jennifer Preece
Venue: Proceedings of the fourth international conference on Communities and technologies (2009)

YouTube is a video sharing repository, enabling users to post, share and discuss videos. Its stated mission is to create "an online video community"; however, YouTube is not commonly thought of as a community. Our aim in this study is to answer the question whether users have a "sense of community" towards YouTube, and if such feelings exist are they reflected in the explicit ties among members. To accomplish this, YouTube was examined using two different and complementing methods. Using Grounded Theory, we performed a detailed analysis of more than 30 videos and their corresponding textual comments, which discussed two topics: users' feelings about the YouTube community, and users' accounts of interaction within the community. We then performed a structural analysis on the ties these users display on their YouTube channels. This analysis showed that although users perceive YouTube to be a cohesive community, the explicit relationships in the friendship and subscription network are almost random. We suggest that users' sense of community is not necessarily related to the structure of the YouTube network, and may result from subjective affinity towards other users. This study also points out the importance of triangulating qualitative and quantitative data to get a deeper understanding of the nature of an online community.
A logit model for predicting wetland location using ASTER and GIS
Authors: E. Pantaleoni, R. H. Wynne, J. M. Galbraith, J. B. Campbell
Venue: International Journal of Remote Sensing (2009)

Data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to develop a logistic regression model to predict the location of wetlands in the Coastal Plain of Virginia. We used the first five bands from two ASTER scenes (spanning 0.52-2.18 µm) covering the same area, acquired 6 March 2005 and 16 October 2005. March Band 3 contributed the most in discriminating wetlands over the other ASTER bands (marginal effect = 7.277), and it predicted the location of 60% of the total wetlands. We used a canonical discriminant analysis to test the significance of GIS variables in separating wetlands from uplands. Soil Survey Geographic Database soil data had the highest correlation with the first canonical component (0.876), followed by March Band 3 (-0.803), and the National Hydrography Dataset water (0.725). We included GIS data layers into the logit model. The resulting model predicted the location of over 78% of total wetlands, highlighting the potential of models incorporating ASTER data for speeding the wetland mapping process, lowering costs of map production, and improving wetland mapping accuracy.
Chip Multiprocessor Architecture: Techniques to Improve Throughput and Latency, 1st edition
Authors: Kunle Olukotun
Venue:  (2007)

Chip multiprocessors - also called multi-core microprocessors or CMPs for short - are now the only way to build high-performance microprocessors, for a variety of reasons. Large uniprocessors are no longer scaling in performance, because it is only possible to extract a limited amount of parallelism from a typical instruction stream using conventional superscalar instruction issue techniques. In addition, one cannot simply ratchet up the clock speed on today's processors, or the power dissipation will become prohibitive in all but water-cooled systems. Compounding these problems is the simple fact that with the immense numbers of transistors available on today's microprocessor chips, it is too costly to design and debug ever-larger processors every year or two. CMPs avoid these problems by filling up a processor die with multiple, relatively simpler processor cores instead of just one huge core. The exact size of a CMPs cores can vary from very simple pipelines to moderately complex superscalar processors, but once a core has been selected the CMPs performance can easily scale across silicon process generations simply by stamping down more copies of the hard-to-design, high-speed processor core in each successive chip generation. In addition, parallel code execution, obtained by spreading multiple threads of execution across the various cores, can achieve significantly higher performance than would be possible using only a single core. While parallel threads are already common in many useful workloads, there are still important workloads that are hard to divide into parallel threads. The low inter-processor communication latency between the cores in a CMP helps make a much wider range of applications viable candidates for parallel execution than was possible with conventional, multi-chip multiprocessors; nevertheless, limited parallelism in key applications is the main factor limiting acceptance of CMPs in some types of systems.
Implementation considerations for improving data integrity in normalized relational databases
Authors: Tennyson X. Chen, Martin D. Meyer, Nanthini Ganapathi
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

Using vertical decomposition method to normalize relational database has been well illustrated and understood. The purpose of relational decomposition is to remove data redundancy and prevent data anomalies. Up to the Boyce-Codd normal from (BCNF), decompositions are performed based on functional dependency at a relation's attribute level. However, since data redundancies can also appear between attributes that are interrelated in forms other than functional dependency, decomposition method fails to remove some very basic data anomalies. Consequently, we can still observe data anomalies in high level normal forms such as BCNF, 4NF and 5NF. After introducing the data anomalies that may occur in high level normal forms, this paper discusses some practical approaches on how to eliminate or reduce such anomalies in order to improve data integrity.
A Mathematical Modeling Module with System Engineering Approach for Teaching Undergraduate Students to Conquer Complexity
Authors: Hong Liu, Jayathi Raghavan
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

This paper presents a mathematical modeling module for ODE courses. The module uses light-weight systems engineering approach to promote the competency of undergraduates to overcome the complexity in applied mathematics problems. The mathematics training of undergraduates in most colleges is limited to solving applications with a couple of variables in few steps of computations. Once faced with problems beyond that level of complexity, they are not only challenged to plan a scheme for finding solutions, but also to provide justification for their answers. This module combines an iterative modeling process with the compartmental analysis methodology to leverage these challenges. Verification and validation techniques are introduced for assuring the soundness of answers. The query-based process forces the students to trace critical mathematics equations to the corresponding phenomena of the problem under consideration. Examples within the module are arranged with incremental complexity. Stella is used as a modeling and simulation tool.
Integrating individual and social intelligence into module-based agents without central coordinator
Authors: Bianca Innocenti, Beatriz López, Joaquim Salvi
Venue: Proceeding of the 2008 conference on STAIRS 2008: Proceedings of the Fourth Starting AI Researchers' Symposium (2008)

Robots are complex entities that can be modeled as multi-agent systems. The multi-agent paradigm provides an integrated intelligence framework such as a path planning agent that uses search techniques interacts with a fuzzy-based agent that moves the robot to a given location. Agent coordination is required to achieve the appropriate global behavior. When there is no central agent that coordinates the overall architecture, the intelligence required for social interaction should therefore be deployed at the agent level. In such a situation, individual intelligence (how to reach a goal) and social intelligence (how to collaborate or compete for resource with other agents) should be integrated at the agent level. In this paper we propose the use of module-based agents to achieve this integration. The whole multi-agent robot architecture, ARMADiCo, has been implemented with several module-based agents and tested on a Pioneer 2DX of ActivMedia. Some preliminary results are shown and discussed.
CRA Survey Counts New PhDs
Authors: Bob Ward
Venue: Computer (2009)

The Computing Research Association's annual Taulbee Survey of PhD-granting departments of computer science and computer engineering in North America reveals that doctorate degree production is close to peaking and the number of doctorates granted will begin to decrease.
Dielectric elastomer actuators for tactile displays
Authors: Marc Matysek, Peter Lotz, Thomas Winterstein, Helmut F. Schlaak
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

In this paper we discuss dielectric elastomer actuators (DEA) as one of the most promising technologies in electroactive polymers (EAP). For tactile display applications a large number of actuator elements is essential. The multilayer technology presented here offers the possibility to build up independent actuators and arrays at a high density within one substrate. The functional principle of these electromechanical transducers provides a simple way to measure the actual deformation. The paper concludes with a concept to determine the active deformation as well as user applied forces.
Stability Conditions of Delayed Recurrent Neural Networks with Positive Linear Activation Functions
Authors: Dongyun Wang, Yan Wang
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

By using the positive linearity of the activation functions of neurons in recurrent neural networks, and by adopting the method of decomposing the state space to sub-regions, the mathematical equations of delayed recurrent neural networks are rewritten to be the form of linear differential difference equations in the neighbourhood of each equilibrium, which is an interior point of some sub-region. Based on this linear form and by using the stability theory of linear differential difference equations and the tool of M-matrix, delay-dependent and delay-independent stability algebraic criteria are obtained. All results obtained in this paper need only to compute the eigenvalues of some matrices or to examine the matrices to be M-matrix or to verify some inequalities to be holden.
Non destructive techniques of automatic shape classification of vegetal products
Authors: Marius Buzera, Valentina E. Balas, Gabriela Prostean, Nikos E. Mastorakis
Venue: Proceedings of the 10th WSEAS international conference on Neural networks (2009)

Over the last few years, there has been more and more interest upon carrying out some automatic machines meant to classify both industrial and vegetal products. Shape color and size represent the most important parameters for vegetal products to be assessed via machines vision techniques as a part of automatic processes. Taking into account the large amount of parameters for vegetal products to be reached as a goal of automatic classification, as well as the high degree of fluency of certain parameters, the usual algorithms can easily turn ineffective. Thus, a prototype of an automatic machine hinting to classify vegetal products was projected and brought to life so as to develop and test a series of decision algorithms belonging to artificial intelligence. To classify the shape and size has been developed a back-propagation feed-forward artificial neural network. Part of the result and conclusions are presented through this paper.