OpenRaiser/Intern-Atlas huggingface dataset:
KamiWaAi - Interactive 3D Sketching with Java Based on Cl(4,1) Conformal Model of Euclidean Space
Venue: arXiv cs.CG 2013
Year: 2013

This paper introduces the new interactive Java sketching software KamiWaAi, recently developed at the University of Fukui. Its graphical user interface enables the user without any knowledge of both mathematics or computer science, to do full three dimensional "drawings" on the screen. The resulting constructions can be reshaped interactively by dragging its points over the screen. The programming approach is new. KamiWaAi implements geometric objects like points, lines, circles, spheres, etc. directly as software objects (Java classes) of the same name. These software objects are geometric entities mathematically defined and manipulated in a conformal geometric algebra, combining the five dimensions of origin, three space and infinity. Simple geometric products in this algebra represent geometric unions, intersections, arbitrary rotations and translations, projections, distance, etc. To ease the coordinate free and matrix free implementation of this fundamental geometric product, a new algebraic three level approach is presented. Finally details about the Java classes of the new GeometricAlgebra software package and their associated methods are given. KamiWaAi is available for free internet download. Key Words: Geometric Algebra, Conformal Geometric Algebra, Geometric Calculus Software, GeometricAlgebra, Java Package, Interactive 3D Software, Geometric Objects
ROTUNDE - A Smart Meeting Cinematography Initiative: Tools, Datasets, and Benchmarks for Cognitive Interpretation and Control
Venue: arXiv cs.AI 2013
Year: 2013

We construe smart meeting cinematography with a focus on professional situations such as meetings and seminars, possibly conducted in a distributed manner across socio-spatially separated groups. The basic objective in smart meeting cinematography is to interpret professional interactions involving people, and automatically produce dynamic recordings of discussions, debates, presentations etc in the presence of multiple communication modalities. Typical modalities include gestures (e.g., raising one's hand for a question, applause), voice and interruption, electronic apparatus (e.g., pressing a button), movement (e.g., standing-up, moving around) etc. ROTUNDE, an instance of smart meeting cinematography concept, aims to: (a) develop functionality-driven benchmarks with respect to the interpretation and control capabilities of human-cinematographers, real-time video editors, surveillance personnel, and typical human performance in everyday situations; (b) Develop general tools for the commonsense cognitive interpretation of dynamic scenes from the viewpoint of visuo-spatial cognition centred perceptual narrativisation. Particular emphasis is placed on declarative representations and interfacing mechanisms that seamlessly integrate within large-scale cognitive (interaction) systems and companion technologies consisting of diverse AI sub-components. For instance, the envisaged tools would provide general capabilities for high-level commonsense reasoning about space, events, actions, change, and interaction.
Discriminative Parameter Estimation for Random Walks Segmentation: Technical Report
Venue: arXiv cs.CV 2013
Year: 2013

The Random Walks (RW) algorithm is one of the most e - cient and easy-to-use probabilistic segmentation methods. By combining contrast terms with prior terms, it provides accurate segmentations of medical images in a fully automated manner. However, one of the main drawbacks of using the RW algorithm is that its parameters have to be hand-tuned. we propose a novel discriminative learning framework that estimates the parameters using a training dataset. The main challenge we face is that the training samples are not fully supervised. Speci cally, they provide a hard segmentation of the images, instead of a proba-bilistic segmentation. We overcome this challenge by treating the optimal probabilistic segmentation that is compatible with the given hard segmentation as a latent variable. This allows us to employ the latent support vector machine formulation for parameter estimation. We show that our approach signi cantly outperforms the baseline methods on a challenging dataset consisting of real clinical 3D MRI volumes of skeletal muscles.
Practical Secrecy using Artificial Noise
Venue: arXiv cs.IT 2013
Year: 2013

In this paper, we consider the use of artificial noise for secure communications. We propose the notion of practical secrecy as a new design criterion based on the behavior of the eavesdropper's error probability $P_E$, as the signal-to-noise ratio goes to infinity. We then show that the practical secrecy can be guaranteed by the randomly distributed artificial noise with specified power. We show that it is possible to achieve practical secrecy even when the eavesdropper can afford more antennas than the transmitter.
Can Research be Taught?
Venue: arXiv cs.CY 2013
Year: 2013

The word 'researcher' is loaded and often confusing. It takes years to become one and to master all of its aspects. In this paper, we investigate whether or not this process of 'becoming' can be catalyzed through education. The focus will be on wireless communications, though the same principle could very well be replicated to other disciplines.
An Active Host-Based Intrusion Detection System for ARP-Related Attacks and its Verification
Venue: arXiv cs.NI 2013
Year: 2013

Spoofing with falsified IP-MAC pair is the first step in most of the LAN based-attacks. Address Resolution Protocol (ARP) is stateless, which is the main cause that makes spoofing possible. Several network level and host level mechanisms have been proposed to detect and mitigate ARP spoofing but each of them has their own drawback. In this paper we propose a Host-based Intrusion Detection system for LAN attacks, which works without any extra constraint like static IP-MAC, modifying ARP etc. The proposed scheme is verified under all possible attack scenarios. The scheme is successfully validated in a test bed with various attack scenarios and the results show the effectiveness of the proposed technique.
Tuple Value Based Multiplicative Data Perturbation Approach To Preserve Privacy In Data Stream Mining
Venue: arXiv cs.DB 2013
Year: 2013

Huge volume of data from domain specific applications such as medical, financial, library, telephone, shopping records and individual are regularly generated. Sharing of these data is proved to be beneficial for data mining application. On one hand such data is an important asset to business decision making by analyzing it. On the other hand data privacy concerns may prevent data owners from sharing information for data analysis. In order to share data while preserving privacy, data owner must come up with a solution which achieves the dual goal of privacy preservation as well as an accuracy of data mining task - clustering and classification. An efficient and effective approach has been proposed that aims to protect privacy of sensitive information and obtaining data clustering with minimum information loss.
A Compact Dual Band Dielectric Resonator Antenna For Wireless Applications
Venue: arXiv cs.OH 2013
Year: 2013

This paper presents the design of a dual band rectangular Dielectric Resonator Antenna (DRA) coupled to narrow slot aperture that is fed by microstrip line. The fundamental TE111 mode and higher-order TE113 mode are excited with their resonant frequencies respectively. These frequencies can be controlled by changing the DRA dimensions. A dielectric resonator with high permittivity is used to miniaturize the global structure. The proposed antenna is designed to have dual band operation suitable for both DCS (1710 - 1880 MHz) and WLAN (2400 - 2484 MHz) applications. The return loss, radiation pattern and gain of the proposed antenna are evaluated. Reasonable agreement between simulation and experimental results is obtained.
I am 4 vho: new approach to improve seamless vertical hanover in heterogeneous wireless networks
Venue: arXiv cs.NI 2013
Year: 2013

Two mechanisms have been proposed independently by IEEE and 3GPP; namely, Media Independent Handover (MIH) and Access Network Discovery and Selection Function (ANDSF), respectively. These mechanisms enable a seamless Vertical Handover (VHO) between the different types of technologies (3GPP and non-3GPP), such as GSM (Global System for Mobile Communication), Wireless Fidelity (Wi- Fi), Worldwide Interoperability for Microwave Access (WiMAX), Universal Mobile Telecommunications System (UMTS) and Long Term Evolution (LTE). In this paper, we overview these mechanisms and show their components, benefits and drawbacks. Then we present our Imperative Alternative MIH for Vertical Handover (I AM 4 VHO) approach based on the approaches that have been studied in the literature with better performance (packet loss and latency), less connection failure (probability of reject sessions), less complexity and more exhaustive for enhancing VHO heterogeneous wireless networks environment.
A model driven engineering approach to develop a cooperative information system
Venue: arXiv cs.SE 2013
Year: 2013

To reuse one or several existing systems in order to develop a complex system is a common practice in software engineering. This approach can be justified by the fact that it is often difficult for a single Information System (IS) to accomplish all the requested tasks. So, one solution is to combine many different ISs and make them collaborate in order to realize these tasks. We proposed an approach named AspeCiS (An Aspect-oriented Approach to Develop a Cooperative Information System) to develop a Cooperative Information System from existing ISs by using their artifacts such as existing requirements, and design. AspeCiS covers the three following phases: (i) discovery and analysis of Cooperative Requirements, (ii) design of Cooperative Requirements models, and (iii) preparation of the implementation phase. The main issue of AspeCiS is the definition of Cooperative Requirements using the Existing Requirements and Additional Requirements, which should be composed with Aspectual Requirements. We earlier studied how to elicit the Cooperative Requirements in AspeCiS (phase of discovery and analysis of Cooperative Requirements in AspeCiS) . We study here the second phase of AspeCiS (design of Cooperative Requirements models), by the way of a model weaving process. This process uses so-called AspeCiS Weaving Metamodel, and it weaves Existing and Additional Requirements models to realize Cooperative Requirements models.
Extending Universal Intelligence Models with Formal Notion of Representation
Venue: arXiv cs.AI 2013
Year: 2013

Solomonoff induction is known to be universal, but incomputable. Its approximations, namely, the Minimum Description (or Message) Length (MDL) principles, are adopted in practice in the efficient, but non-universal form. Recent attempts to bridge this gap leaded to development of the Representational MDL principle that originates from formal decomposition of the task of induction. In this paper, possible extension of the RMDL principle in the context of universal intelligence agents is considered, for which introduction of representations is shown to be an unavoidable meta-heuristic and a step toward efficient general intelligence. Hierarchical representations and model optimization with the use of information-theoretic interpretation of the adaptive resonance are also discussed.
Infrared face recognition: a literature review
Venue: arXiv cs.CV 2013
Year: 2013

Automatic face recognition (AFR) is an area with immense practical potential which includes a wide range of commercial and law enforcement applications, and it continues to be one of the most active research areas of computer vision. Even after over three decades of intense research, the state-of-the-art in AFR continues to improve, benefiting from advances in a range of different fields including image processing, pattern recognition, computer graphics and physiology. However, systems based on visible spectrum images continue to face challenges in the presence of illumination, pose and expression changes, as well as facial disguises, all of which can significantly decrease their accuracy. Amongst various approaches which have been proposed in an attempt to overcome these limitations, the use of infrared (IR) imaging has emerged as a particularly promising research direction. This paper presents a comprehensive and timely review of the literature on this subject.
Design Based Teaching for Science and Engineering Students
Venue: arXiv cs.CY 2013
Year: 2013

In this paper, we will explain a successfully proven lecturing method based entirely on system design. Wireless communications will be used as an example to explain this new teaching philosophy.
Algebraic foundations of split hypercomplex nonlinear adaptive filtering
Venue: arXiv cs.CV 2013
Year: 2013

A split hypercomplex learning algorithm for the training of nonlinear finite impulse response adaptive filters for the processing of hypercomplex signals of any dimension is proposed. The derivation strictly takes into account the laws of hypercomplex algebra and hypercomplex calculus, some of which have been neglected in existing learning approaches (e.g. for quaternions). Already in the case of quaternions we can predict improvements in performance of hypercomplex processes. The convergence of the proposed algorithms is rigorously analyzed. Keywords: Quaternionic adaptive filtering, Hypercomplex adaptive filtering, Nonlinear adaptive filtering, Hypercomplex Multilayer Perceptron, Clifford geometric algebra
Measuring the Impact of Adversarial Errors on Packet Scheduling Strategies
Venue: arXiv cs.NI 2013
Year: 2013

In this paper we explore the problem of achieving efficient packet transmission over unreliable links with worst case occurrence of errors. In such a setup, even an omniscient offline scheduling strategy cannot achieve stability of the packet queue, nor is it able to use up all the available bandwidth. Hence, an important first step is to identify an appropriate metric for measuring the efficiency of scheduling strategies in such a setting. To this end, we propose a relative throughput metric which corresponds to the long term competitive ratio of the algorithm with respect to the optimal. We then explore the impact of the error detection mechanism and feedback delay on our measure. We compare instantaneous error feedback with deferred error feedback, that requires a faulty packet to be fully received in order to detect the error. We propose algorithms for worst-case adversarial and stochastic packet arrival models, and formally analyze their performance. The relative throughput achieved by these algorithms is shown to be close to optimal by deriving lower bounds on the relative throughput of the algorithms and almost matching upper bounds for any algorithm in the considered settings. Our collection of results demonstrate the potential of using instantaneous feedback to improve the performance of communication systems in adverse environments.
Online Parallel Scheduling of Non-uniform Tasks: Trading Failures for Energy
Venue: arXiv cs.DC 2013
Year: 2013

Consider a system in which tasks of different execution times arrive continuously and have to be executed by a set of processors that are prone to crashes and restarts. In this paper we model and study the impact of parallelism and failures on the competitiveness of such an online system. In a fault-free environment, a simple Longest-in-System scheduling policy, enhanced by a redundancy-avoidance mechanism, guarantees optimality in a long-term execution. In the presence of failures though, scheduling becomes a much more challenging task. In particular, no parallel deterministic algorithm can be competitive against an offline optimal solution, even with one single processor and tasks of only two different execution times. We find that when additional energy is provided to the system in the form of processor speedup, the situation changes. Specifically, we identify thresholds on the speedup under which such competitiveness cannot be achieved by any deterministic algorithm, and above which competitive algorithms exist. Finally, we propose algorithms that achieve small bounded competitive ratios when the speedup is over the threshold.
Discriminative k-means clustering
Venue: arXiv cs.CV 2013
Year: 2013

The k-means algorithm is a partitional clustering method. Over 60 years old, it has been successfully used for a variety of problems. The popularity of k-means is in large part a consequence of its simplicity and efficiency. In this paper we are inspired by these appealing properties of k-means in the development of a clustering algorithm which accepts the notion of "positively" and "negatively" labelled data. The goal is to discover the cluster structure of both positive and negative data in a manner which allows for the discrimination between the two sets. The usefulness of this idea is demonstrated practically on the problem of face recognition, where the task of learning the scope of a person's appearance should be done in a manner which allows this face to be differentiated from others.
Distributed Decision-Making over Adaptive Networks
Venue: arXiv cs.IT 2013
Year: 2013

In distributed processing, agents generally collect data generated by the same underlying unknown model (represented by a vector of parameters) and then solve an estimation or inference task cooperatively. In this paper, we consider the situation in which the data observed by the agents may have risen from two different models. Agents do not know beforehand which model accounts for their data and the data of their neighbors. The objective for the network is for all agents to reach agreement on which model to track and to estimate this model cooperatively. In these situations, where agents are subject to data from unknown different sources, conventional distributed estimation strategies would lead to biased estimates relative to any of the underlying models. We first show how to modify existing strategies to guarantee unbiasedness. We then develop a classification scheme for the agents to identify the models that generated the data, and propose a procedure by which the entire network can be made to converge towards the same model through a collaborative decision-making process. The resulting algorithm is applied to model fish foraging behavior in the presence of two food sources.
"Not not bad" is not "bad": A distributional account of negation
Venue: arXiv cs.CL 2013
Year: 2013

With the increasing empirical success of distributional models of compositional semantics, it is timely to consider the types of textual logic that such models are capable of capturing. In this paper, we address shortcomings in the ability of current models to capture logical operations such as negation. As a solution we propose a tripartite formulation for a continuous vector space representation of semantics and subsequently use this representation to develop a formal compositional notion of negation within such models.
A simple case of rationality of escalation
Venue: arXiv cs.GT 2013
Year: 2013

Escalation is the fact that in a game (for instance an auction), the agents play forever. It is not necessary to consider complex examples to establish its rationality. In particular, the $0,1$-game is an extremely simple infinite game in which escalation arises naturally and rationally. In some sense, it can be considered as the paradigm of escalation. Through an example of economic games, we show the benefit economics can take of coinduction.
A Fast Fault Tolerant Partitioning Algorithm for Wireless Sensor Networks
Venue: arXiv cs.DC 2013
Year: 2013

In this paper, given a random uniform distribution of sensor nodes on a 2-D plane, a fast self-organized distributed algorithm is proposed to find the maximum number of partitions of the nodes such that each partition is connected and covers the area to be monitored. Each connected partition remains active in a round robin fashion to cover the query region individually. In case of a node failure, the proposed distributed fault recovery algorithm reconstructs the affected partition locally utilizing the available free nodes. Simulation studies show significant improvement in performance compared to the earlier works in terms of computation time, the diameter of each partition, message overhead and network lifetime.
Preserving differential privacy under finite-precision semantics
Venue: arXiv cs.DB 2013
Year: 2013

The approximation introduced by finite-precision representation of continuous data can induce arbitrarily large information leaks even when the computation using exact semantics is secure. Such leakage can thus undermine design efforts aimed at protecting sensitive information. We focus here on differential privacy, an approach to privacy that emerged from the area of statistical databases and is now widely applied also in other domains. In this approach, privacy is protected by the addition of noise to a true (private) value. To date, this approach to privacy has been proved correct only in the ideal case in which computations are made using an idealized, infinite-precision semantics. In this paper, we analyze the situation at the implementation level, where the semantics is necessarily finite-precision, i.e. the representation of real numbers and the operations on them, are rounded according to some level of precision. We show that in general there are violations of the differential privacy property, and we study the conditions under which we can still guarantee a limited (but, arguably, totally acceptable) variant of the property, under only a minor degradation of the privacy level. Finally, we illustrate our results on two cases of noise-generating distributions: the standard Laplacian mechanism commonly used in differential privacy, and a bivariate version of the Laplacian recently introduced in the setting of privacy-aware geolocation.
Enhancing Unsatisfiable Cores for LTL with Information on Temporal Relevance
Venue: arXiv cs.LO 2013
Year: 2013

LTL is frequently used to express specifications in many domains such as embedded systems or business processes. Witnesses can help to understand why an LTL specification is satisfiable, and a number of approaches exist to make understanding a witness easier. In the case of unsatisfiable specifications unsatisfiable cores (UCs), i.e., parts of an unsatisfiable formula that are themselves unsatisfiable, are a well established means for debugging. However, little work has been done to help understanding a UC of an unsatisfiable LTL formula. In this paper we suggest to enhance a UC of an unsatisfiable LTL formula with additional information about the time points at which the subformulas of the UC are relevant for unsatisfiability. For example, in "(G p) and (X not p)" the first occurrence of "p" is really only "relevant" for unsatisfiability at time point 1 (time starts at time point 0). We present a method to extract such information from the resolution graph of a temporal resolution proof of unsatisfiability of an LTL formula. We implement our method in TRP++, and we experimentally evaluate it. Source code of our tool is available.