OpenRaiser/Intern-Atlas huggingface dataset:
The Concept of Appropriation as a Heuristic for Conceptualising the Relationship between Technology, People and Organisations
Venue: arXiv cs.CY 2008
Year: 2008

The stated aim of this conference is to debate the continuing evolution of IS in businesses and other organisations. This paper seeks to contribute to this debate by exploring the concept of appropriation from a number of different epistemological, cultural and linguistic viewpoints to allow us to explore 'the black box' of appropriation and to gain a fuller understanding of the term. At the conceptual level, it will examine some of the different ways in which people have attempted to explain the relationship between the objective and concrete features of technology and the subjective and shifting nature of the people and organisation within which that technology is deployed. At the cultural and linguistic level the paper will examine the notion as it is found in the Francophone literature, where the term has a long and rich history, and the Anglophone literature where appropriation is seen as a rather more specialist term. The paper will conclude with some observations on the ongoing nature of the debate, the value of reading beyond the literature with which one is familiar and the rewards that come from exploring different historical (and linguistic) viewpoints.
A New Approach to Automated Epileptic Diagnosis Using EEG and Probabilistic Neural Network
Venue: arXiv cs.AI 2008
Year: 2008

Epilepsy is one of the most common neurological disorders that greatly impair patient' daily lives. Traditional epileptic diagnosis relies on tedious visual screening by neurologists from lengthy EEG recording that requires the presence of seizure (ictal) activities. Nowadays, there are many systems helping the neurologists to quickly find interesting segments of the lengthy signal by automatic seizure detection. However, we notice that it is very difficult, if not impossible, to obtain long-term EEG data with seizure activities for epilepsy patients in areas lack of medical resources and trained neurologists. Therefore, we propose to study automated epileptic diagnosis using interictal EEG data that is much easier to collect than ictal data. The authors are not aware of any report on automated EEG diagnostic system that can accurately distinguish patients' interictal EEG from the EEG of normal people. The research presented in this paper, therefore, aims to develop an automated diagnostic system that can use interictal EEG data to diagnose whether the person is epileptic. Such a system should also detect seizure activities for further investigation by doctors and potential patient monitoring. To develop such a system, we extract four classes of features from the EEG data and build a Probabilistic Neural Network (PNN) fed with these features. Leave-one-out cross-validation (LOO-CV) on a widely used epileptic-normal data set reflects an impressive 99.5% accuracy of our system on distinguishing normal people's EEG from patient's interictal EEG. We also find our system can be used in patient monitoring (seizure detection) and seizure focus localization, with 96.7% and 77.5% accuracy respectively on the data set.
Weighted Sum Rate Optimization for Cognitive Radio MIMO Broadcast Channels
Venue: arXiv cs.IT 2008
Year: 2008

In this paper, we consider a cognitive radio (CR) network in which the unlicensed (secondary) users are allowed to concurrently access the spectrum allocated to the licensed (primary) users provided that their interference to the primary users (PUs) satisfies certain constraints. We study a weighted sum rate maximization problem for the secondary user (SU) multiple input multiple output (MIMO) broadcast channel (BC), in which the SUs have not only the sum power constraint but also interference constraints. We first transform this multi-constraint maximization problem into its equivalent form, which involves a single constraint with multiple auxiliary variables. Fixing these multiple auxiliary variables, we propose a duality result for the equivalent problem. Our duality result can solve the optimization problem for MIMO-BC with multiple linear constraints, and thus can be viewed as an extension of the conventional results, which rely crucially on a single sum power constraint. Furthermore, we develop an efficient sub-gradient based iterative algorithm to solve the equivalent problem and show that the developed algorithm converges to a globally optimal solution. Simulation results are further provided to corroborate the effectiveness of the proposed algorithm.
Natural pseudo-distance and optimal matching between reduced size functions
Venue: arXiv cs.CG 2008
Year: 2008

This paper studies the properties of a new lower bound for the natural pseudo-distance. The natural pseudo-distance is a dissimilarity measure between shapes, where a shape is viewed as a topological space endowed with a real-valued continuous function. Measuring dissimilarity amounts to minimizing the change in the functions due to the application of homeomorphisms between topological spaces, with respect to the $L_\infty$-norm. In order to obtain the lower bound, a suitable metric between size functions, called matching distance, is introduced. It compares size functions by solving an optimal matching problem between countable point sets. The matching distance is shown to be resistant to perturbations, implying that it is always smaller than the natural pseudo-distance. We also prove that the lower bound so obtained is sharp and cannot be improved by any other distance between size functions.
Matching Interdiction
Venue: arXiv cs.DM 2008
Year: 2008

In the matching interdiction problem, we are given an undirected graph with weights and interdiction costs on the edges and seek to remove a subset of the edges constrained to some budget, such that the weight of a maximum weight matching in the remaining graph is minimized. In this work we introduce the matching interdiction problem and show that it is strongly NP-complete even when the input is restricted to simple, bipartite graphs with unit edge weights and unit interdiction costs. Furthermore, we present a pseudo-polynomial algorithm for solving the matching interdiction problem on graphs with bounded treewidth. The proposed algorithm extends the approach that is typically used for the creation of efficient algorithms on graphs with bounded treewidth to interdiction problems.
Respect My Authority! HITS Without Hyperlinks, Utilizing Cluster-Based Language Models
Venue: arXiv cs.IR 2008
Year: 2008

We present an approach to improving the precision of an initial document ranking wherein we utilize cluster information within a graph-based framework. The main idea is to perform re-ranking based on centrality within bipartite graphs of documents (on one side) and clusters (on the other side), on the premise that these are mutually reinforcing entities. Links between entities are created via consideration of language models induced from them. We find that our cluster-document graphs give rise to much better retrieval performance than previously proposed document-only graphs do. For example, authority-based re-ranking of documents via a HITS-style cluster-based approach outperforms a previously-proposed PageRank-inspired algorithm applied to solely-document graphs. Moreover, we also show that computing authority scores for clusters constitutes an effective method for identifying clusters containing a large percentage of relevant documents.
The privacy implications of Bluetooth
Venue: arXiv cs.CR 2008
Year: 2008

A substantial amount of research, as well as media hype, has surrounded RFID technology and its privacy implications. Currently, researchers and the media focus on the privacy threats posed by RFID, while consumer groups choose to boycott products bearing RFID tags. At the same, however, a very similar technology has quietly become part of our everyday lives: Bluetooth. In this paper we highlight the fact that Bluetooth is a widespread technology that has real privacy implications. Furthermore, we explore the applicability of RFID-based solutions to address these privacy implications.
Image Processing in Optical Guidance for Autonomous Landing of Lunar Probe
Venue: arXiv cs.RO 2008
Year: 2008

Because of the communication delay between earth and moon, the GNC technology of lunar probe is becoming more important than ever. Current navigation technology is not able to provide precise motion estimation for probe landing control system Computer vision offers a new approach to solve this problem. In this paper, author introduces an image process algorithm of computer vision navigation for autonomous landing of lunar probe. The purpose of the algorithm is to detect and track feature points which are factors of navigation. Firstly, fixation areas are detected as sub-images and matched. Secondly, feature points are extracted from sub-images and tracked. Computer simulation demonstrates the result of algorithm takes less computation and fulfils requests of navigation algorithm.
Automated Flight Test and System Identification for Rotary Wing Small Aerial Platform using Frequency Responses Analysis
Venue: arXiv cs.RO 2008
Year: 2008

This paper proposes an autopilot system that can be used to control the small scale rotorcraft during the flight test for linear-frequency-domain system identification. The input frequency swept is generated automatically as part of the autopilot control command. Therefore the bandwidth coverage and consistency of the frequency swept is guaranteed to produce high quality data for system identification. Beside that we can set the safety parameter during the flight test (maximum roll or pitch value, minimum altitude, etc) so the safety of the whole flight test is guaranteed. This autopilot for automated flight test will be tested using hardware in the loop simulator for hover flight condition.
Energy and Time Efficient Scheduling of Tasks with Dependencies on Asymmetric Multiprocessors
Venue: arXiv cs.DC 2008
Year: 2008

In this work we study the problem of scheduling tasks with dependencies in multiprocessor architectures where processors have different speeds. We present the preemptive algorithm "Save-Energy" that given a schedule of tasks it post processes it to improve the energy efficiency without any deterioration of the makespan. In terms of time efficiency, we show that preemptive scheduling in an asymmetric system can achieve the same or better optimal makespan than in a symmetric system. Motivited by real multiprocessor systems, we investigate architectures that exhibit limited asymmetry: there are two essentially different speeds. Interestingly, this special case has not been studied in the field of parallel computing and scheduling theory; only the general case was studied where processors have $K$ essentially different speeds. We present the non-preemptive algorithm ``Remnants'' that achieves almost optimal makespan. We provide a refined analysis of a recent scheduling method. Based on this analysis, we specialize the scheduling policy and provide an algorithm of $(3 + o(1))$ expected approximation factor. Note that this improves the previous best factor (6 for two speeds). We believe that our work will convince researchers to revisit this well studied scheduling problem for these simple, yet realistic, asymmetric multiprocessor architectures.
Logic Learning in Hopfield Networks
Venue: arXiv cs.LO 2008
Year: 2008

Synaptic weights for neurons in logic programming can be calculated either by using Hebbian learning or by Wan Abdullah's method. In other words, Hebbian learning for governing events corresponding to some respective program clauses is equivalent with learning using Wan Abdullah's method for the same respective program clauses. In this paper we will evaluate experimentally the equivalence between these two types of learning through computer simulations.
Asymptotic Bound on Binary Self-Orthogonal Codes
Venue: arXiv cs.IT 2008
Year: 2008

We present two constructions for binary self-orthogonal codes. It turns out that our constructions yield a constructive bound on binary self-orthogonal codes. In particular, when the information rate R=1/2, by our constructive lower bound, the relative minimum distance δ\approx 0.0595 (for GV bound, δ\approx 0.110). Moreover, we have proved that the binary self-orthogonal codes asymptotically achieve the Gilbert-Varshamov bound.
Multi-Antenna Gaussian Broadcast Channels with Confidential Messages
Venue: arXiv cs.IT 2008
Year: 2008

In wireless data networks, communication is particularly susceptible to eavesdropping due to its broadcast nature. Security and privacy systems have become critical for wireless providers and enterprise networks. This paper considers the problem of secret communication over a Gaussian broadcast channel, where a multi-antenna transmitter sends independent confidential messages to two users with \emph{information-theoretic secrecy}. That is, each user would like to obtain its own confidential message in a reliable and safe manner. This communication model is referred to as the multi-antenna Gaussian broadcast channel with confidential messages (MGBC-CM). Under this communication scenario, a secret dirty-paper coding scheme and the corresponding achievable secrecy rate region are first developed based on Gaussian codebooks. Next, a computable Sato-type outer bound on the secrecy capacity region is provided for the MGBC-CM. Furthermore, the Sato-type outer bound proves to be consistent with the boundary of the secret dirty-paper coding achievable rate region, and hence, the secrecy capacity region of the MGBC-CM is established. Finally, a numerical example demonstrates that both users can achieve positive rates simultaneously under the information-theoretic secrecy requirement.
Wireless Erasure Networks with Feedback
Venue: arXiv cs.IT 2008
Year: 2008

Consider a lossy packet network of queues, communicating over a wireless medium. This paper presents a throughput-optimal transmission strategy for a unicast network when feedback is available, which has the following advantages: It requires a very limited form of acknowledgment feedback. It is completely distributed, and independent of the network topology. Finally, communication at the information theoretic cut-set rate requires no network coding and no rateless coding on the packets. This simple strategy consists of each node randomly choosing a packet from its buffer to transmit at each opportunity. However, the packet is only deleted from a node's buffer once it has been successfully received by the final destination
Practical Automated Partial Verification of Multi-Paradigm Real-Time Models
Venue: arXiv cs.LO 2008
Year: 2008

This article introduces a fully automated verification technique that permits to analyze real-time systems described using a continuous notion of time and a mixture of operational (i.e., automata-based) and descriptive (i.e., logic-based) formalisms. The technique relies on the reduction, under reasonable assumptions, of the continuous-time verification problem to its discrete-time counterpart. This reconciles in a viable and effective way the dense/discrete and operational/descriptive dichotomies that are often encountered in practice when it comes to specifying and analyzing complex critical systems. The article investigates the applicability of the technique through a significant example centered on a communication protocol. More precisely, concurrent runs of the protocol are formalized by parallel instances of a Timed Automaton, while the synchronization rules between these instances are specified through Metric Temporal Logic formulas, thus creating a multi-paradigm model. Verification tests run on this model using a bounded validity checker implementing the technique show consistent results and interesting performances.
Strategy Improvement for Concurrent Safety Games
Venue: arXiv cs.GT 2008
Year: 2008

We consider concurrent games played on graphs. At every round of the game, each player simultaneously and independently selects a move; the moves jointly determine the transition to a successor state. Two basic objectives are the safety objective: ``stay forever in a set F of states'', and its dual, the reachability objective, ``reach a set R of states''. We present in this paper a strategy improvement algorithm for computing the value of a concurrent safety game, that is, the maximal probability with which player 1 can enforce the safety objective. The algorithm yields a sequence of player-1 strategies which ensure probabilities of winning that converge monotonically to the value of the safety game. The significance of the result is twofold. First, while strategy improvement algorithms were known for Markov decision processes and turn-based games, as well as for concurrent reachability games, this is the first strategy improvement algorithm for concurrent safety games. Second, and most importantly, the improvement algorithm provides a way to approximate the value of a concurrent safety game from below (the known value-iteration algorithms approximate the value from above). Thus, when used together with value-iteration algorithms, or with strategy improvement algorithms for reachability games, our algorithm leads to the first practical algorithm for computing converging upper and lower bounds for the value of reachability and safety games.
Comment - Practical Data Protection
Venue: arXiv cs.CR 2008
Year: 2008

Recently, Rawat and Saxena proposed a method for protecting data using ``Disclaimer Statement''. This paper presents some issues and several flaws in their proposal.
Introduction to Relational Networks for Classification
Venue: arXiv cs.LG 2008
Year: 2008

The use of computational intelligence techniques for classification has been used in numerous applications. This paper compares the use of a Multi Layer Perceptron Neural Network and a new Relational Network on classifying the HIV status of women at ante-natal clinics. The paper discusses the architecture of the relational network and its merits compared to a neural network and most other computational intelligence classifiers. Results gathered from the study indicate comparable classification accuracies as well as revealed relationships between data features in the classification data. Much higher classification accuracies are recommended for future research in the area of HIV classification as well as missing data estimation.
Superposition-Coded Concurrent Decode-and-Forward Relaying
Venue: arXiv cs.IT 2008
Year: 2008

In this paper, a superposition-coded concurrent decode-and-forward (DF) relaying protocol is presented. A specific scenario, where the inter-relay channel is sufficiently strong, is considered. Assuming perfect source-relay transmissions, the proposed scheme further improves the diversity performance of previously proposed repetition-coded concurrent DF relaying, in which the advantage of the inter-relay interference is not fully extracted.
Lattice Problems, Gauge Functions and Parameterized Algorithms
Venue: arXiv cs.CC 2008
Year: 2008

Given a k-dimensional subspace M\subseteq \R^n and a full rank integer lattice L\subseteq \R^n, the \emph{subspace avoiding problem} SAP is to find a shortest vector in L\setminus M. Treating k as a parameter, we obtain new parameterized approximation and exact algorithms for SAP based on the AKS sieving technique. More precisely, we give a randomized $(1+ε)$-approximation algorithm for parameterized SAP that runs in time 2^{O(n)}.(1/ε)^k, where the parameter k is the dimension of the subspace M. Thus, we obtain a 2^{O(n)} time algorithm for ε=2^{-O(n/k)}. We also give a 2^{O(n+k\log k)} exact algorithm for the parameterized SAP for any \ell_p norm. Several of our algorithms work for all gauge functions as metric with some natural restrictions, in particular for all \ell_p norms. We also prove an Ω(2^n) lower bound on the query complexity of AKS sieving based exact algorithms for SVP that accesses the gauge function as oracle.
Simulation of Dynamic Yaw Stability Derivatives of a Bird Using CFD
Venue: arXiv cs.RO 2008
Year: 2008

Simulation results on dynamic yaw stability derivatives of a gull bird by means of computational fluid dynamics are presented. Two different kinds of motions are used for determining the dynamic yaw stability derivatives CNr and CNbeta . Concerning the first one, simple lateral translation and yaw rotary motions in yaw are considered. The second one consists of combined motions. To determine dynamic yaw stability derivatives of the bird, the simulation of an unsteady flow with a bird model showing a harmonic motion is performed. The unsteady flow solution for each time step is obtained by solving unsteady Euler equations based on a finite volume approach for a smaller reduced frequency. Then, an evaluation of unsteady forces and moments for one cycle is conducted using harmonic Fourier analysis. The results on the dynamic yaw stability derivatives for both simulations of the model motion show a good agreement.
Design and control of dynamical quantum processes in ortho para H2 conversion on surfaces
Venue: arXiv cs.RO 2008
Year: 2008

We present here a novel, cost-effective method for increasing and controlling the ortho para H2 (o p H2) conversion yield. First, we invoke two processes derived from fundamental, surface science insights, based on the effect of molecular orientation on the hydrogen solid surface reaction, i.e., dynamical quantum filtering and steering, and apply them to enhance the o p H2 conversion yield. Second, we find an important factor that can significantly influence the yield i.e., inhomogeneity of spin density distribution. This factor gives us a promising possibility to increase the yield and to find the best catalyst e.g., design of materials that can function as catalysts for the o p H2 conversion.
A Few More Quadratic APN Functions
Venue: arXiv cs.IT 2008
Year: 2008

We present two infinite families of APN functions where the degree of the field is divisible by 3 but not 9. Our families contain two already known families as special cases. We also discuss the inequivalence proof (by computation) which shows that these functions are new.
Tight local approximation results for max-min linear programs
Venue: arXiv cs.DC 2008
Year: 2008

In a bipartite max-min LP, we are given a bipartite graph $\myG = (V \cup I \cup K, E)$, where each agent $v \in V$ is adjacent to exactly one constraint $i \in I$ and exactly one objective $k \in K$. Each agent $v$ controls a variable $x_v$. For each $i \in I$ we have a nonnegative linear constraint on the variables of adjacent agents. For each $k \in K$ we have a nonnegative linear objective function of the variables of adjacent agents. The task is to maximise the minimum of the objective functions. We study local algorithms where each agent $v$ must choose $x_v$ based on input within its constant-radius neighbourhood in $\myG$. We show that for every $ε>0$ there exists a local algorithm achieving the approximation ratio ${Δ_I (1 - 1/Δ_K)} + ε$. We also show that this result is the best possible -- no local algorithm can achieve the approximation ratio ${Δ_I (1 - 1/Δ_K)}$. Here $Δ_I$ is the maximum degree of a vertex $i \in I$, and $Δ_K$ is the maximum degree of a vertex $k \in K$. As a methodological contribution, we introduce the technique of graph unfolding for the design of local approximation algorithms.