OpenRaiser/Intern-Atlas huggingface dataset:
Analysis of Increasing Malwares and Cyber Crimes Using Economic Approach
Venue: arXiv cs.CY 2014
Year: 2014

The economics of an internet crime has newly developed into a field of controlling black money. This economic approach not only provides estimated technique of analyzing internet crimes but also gives details to analyzers of system dependability and divergence. This paper will highlight on the subject of online crime, which has formed its industry since. It all started from amateur hackers who cracked websites and wrote malicious software in pursuit of fun or achieving limited objectives to professional hacking. In the past days, electronic fraud was main objective but now it has been changed into electronic hacking. This study focuses the issue through an economic analysis of available web forum to deals in malware and private information. The findings of this survey research provide considerable in-depth sight into the functions of malware economy spinning around computer impositions and compromise. In this regard, the survey research paper may benefit particularly computer security officials, the law enforcement agencies, and in general prospective anyone involved in better understanding cybercrime from the offender standpoint.
Automation of Prosthetic Upper Limbs for Transhumeral Amputees Using Switch-controlled Motors
Venue: arXiv cs.HC 2014
Year: 2014

The issues of research required in the field of bio medical engineering and externally-powered prostheses are attracting attention of regulatory bodies and the common people in various parts of the globe. Today, 90 percent of prostheses used are conventional body powered cable-controlled ones which are very uncomfortable to the amputees as fairly large amount of forces and excursions have to be generated by the amputee. Additionally, its amount of rotation is limited. Alternatively, prosthetic limbs driven using electrical motors might deliver added functionality and improved control, accompanied by better cosmesis, however,it could be bulky and costly. Presently existing proposals usually require fewer bodily response and need additional upkeep than the cable operated prosthetic limbs. Due to the motives mentioned, proposal for mechanization of body-powered prostheses, with ease of maintenance and cost in mind, is presented in this paper. The prosthetic upper limb which is being automated is for Transhumeral type of amputees that is amputated from above elbow. The study consists of two main portions: one is lifting mechanism of the limb and the other is gripping mechanism for the hand using switch controls, which is the most cost effective and optimized solution, rather than using complex and expensive myoelectric control signals.
Conformance Testing as Falsification for Cyber-Physical Systems
Venue: arXiv cs.SY 2014
Year: 2014

In Model-Based Design of Cyber-Physical Systems (CPS), it is often desirable to develop several models of varying fidelity. Models of different fidelity levels can enable mathematical analysis of the model, control synthesis, faster simulation etc. Furthermore, when (automatically or manually) transitioning from a model to its implementation on an actual computational platform, then again two different versions of the same system are being developed. In all previous cases, it is necessary to define a rigorous notion of conformance between different models and between models and their implementations. This paper argues that conformance should be a measure of distance between systems. Albeit a range of theoretical distance notions exists, a way to compute such distances for industrial size systems and models has not been proposed yet. This paper addresses exactly this problem. A universal notion of conformance as closeness between systems is rigorously defined, and evidence is presented that this implies a number of other application-dependent conformance notions. An algorithm for detecting that two systems are not conformant is then proposed, which uses existing proven tools. A method is also proposed to measure the degree of conformance between two systems. The results are demonstrated on a range of models.
Least Entropy-Like Approach for Reconstructing L-Shaped Surfaces Using a Rotating Array of Ultrasonic Sensors
Venue: arXiv cs.RO 2014
Year: 2014

This paper introduces a new algorithm for accurately reconstructing two smooth orthogonal surfaces by processing ultrasonic data. The proposed technique is based on a preliminary analysis of a waveform energy indicator in order to classify the data as belonging to one of the two flat surfaces. The following minimization of a nonlinear cost function, inspired by the mathematical definition of Gibbs entropy, allows to estimate the plane parameters robustly with respect to the presence of outlying data. These outliers are mainly due to the effect of multiple reflections arising in the surfaces intersection region. The scanning system consists of four inexpensive ultrasonic sensors rotated by means of a precision servo digital motor in order to obtain distance measurements for each orientation. Experimental results are presented and compared with the classic Least Squares Method demonstrating the potentiality of the proposed approach in terms of precision and reliability.
Genetic Algorithms and its use with back-propagation network
Venue: arXiv cs.NE 2014
Year: 2014

Genetic algorithms are considered as one of the most efficient search techniques. Although they do not offer an optimal solution, their ability to reach a suitable solution in considerably short time gives them their respectable role in many AI techniques. This work introduces genetic algorithms and describes their characteristics. Then a novel method using genetic algorithm in best training set generation and selection for a back-propagation network is proposed. This work also offers a new extension to the original genetic algorithms
Navigating MazeMap: indoor human mobility, spatio-logical ties and future potential
Venue: arXiv cs.SY 2014
Year: 2014

Global navigation systems and location-based services have found their way into our daily lives. Recently, indoor positioning techniques have also been proposed, and there are several live or trial systems already operating. In this paper, we present insights from MazeMap, the first live indoor/outdoor positioning and navigation system deployed at a large university campus in Norway. Our main contribution is a measurement case study; we show the spatial and temporal distribution of MazeMap geo-location and wayfinding requests, construct the aggregated human mobility map of the campus and find strong logical ties between different locations. On one hand, our findings are specific to the venue; on the other hand, the nature of available data and insights coupled with our discussion on potential usage scenarios for indoor positioning and location-based services predict a successful future for these systems and applications.
A Distributed Minimum Cut Approximation Scheme
Venue: arXiv cs.DS 2014
Year: 2014

In this paper, we study the problem of approximating the minimum cut in a distributed message-passing model, the CONGEST model. The minimum cut problem has been well-studied in the context of centralized algorithms. However, there were no known non-trivial algorithms in the distributed model until the recent work of Ghaffari and Kuhn. They gave algorithms for finding cuts of size $O(ε^{-1}λ)$ and $(2+ε)λ$ in $O(D)+\tilde{O}(n^{1/2+ε})$ rounds and $\tilde{O}(D+\sqrt{n})$ rounds respectively, where $λ$ is the size of the minimum cut. This matches the lower bound they provided up to a polylogarithmic factor. Yet, no scheme that achieves $(1+ε)$-approximation ratio is known. We give a distributed algorithm that finds a cut of size $(1+ε)λ$ in $\tilde{O}(D+\sqrt{n})$ time, which is optimal up to polylogarithmic factors.
Domain Views for Constraint Programming
Venue: arXiv cs.AI 2014
Year: 2014

Views are a standard abstraction in constraint programming: They make it possible to implement a single version of each constraint, while avoiding to create new variables and constraints that would slow down propagation. Traditional constraint-programming systems provide the concept of {\em variable views} which implement a view of the type $y = f(x)$ by delegating all (domain and constraint) operations on variable $y$ to variable $x$. This paper proposes the alternative concept of {\em domain views} which only delegate domain operations. Domain views preserve the benefits of variable views but simplify the implementation of value-based propagation. Domain views also support non-injective views compositionally, expanding the scope of views significantly. Experimental results demonstrate the practical benefits of domain views.
The semantic marriage of monads and effects
Venue: arXiv cs.PL 2014
Year: 2014

Wadler and Thiemann unified type-and-effect systems with monadic semantics via a syntactic correspondence and soundness results with respect to an operational semantics. They conjecture that a general, "coherent" denotational semantics can be given to unify effect systems with a monadic-style semantics. We provide such a semantics based on the novel structure of an indexed monad, which we introduce. We redefine the semantics of Moggi's computational lambda-calculus in terms of (strong) indexed monads which gives a one-to-one correspondence between indices of the denotations and the effect annotations of traditional effect systems. Dually, this approach yields indexed comonads which gives a unified semantics and effect system to contextual notions of effect (called coeffects), which we have previously described.
Patterns of Ship-borne Species Spread: A Clustering Approach for Risk Assessment and Management of Non-indigenous Species Spread
Venue: arXiv cs.SI 2014
Year: 2014

The spread of non-indigenous species (NIS) through the global shipping network (GSN) has enormous ecological and economic cost throughout the world. Previous attempts at quantifying NIS invasions have mostly taken "bottom-up" approaches that eventually require the use of multiple simplifying assumptions due to insufficiency and/or uncertainty of available data. By modeling implicit species exchanges via a graph abstraction that we refer to as the Species Flow Network (SFN), a different approach that exploits the power of network science methods in extracting knowledge from largely incomplete data is presented. Here, coarse-grained species flow dynamics are studied via a graph clustering approach that decomposes the SFN to clusters of ports and inter-cluster connections. With this decomposition of ports in place, NIS flow among clusters can be very efficiently reduced by enforcing NIS management on a few chosen inter-cluster connections. Furthermore, efficient NIS management strategy for species exchanges within a cluster (often difficult due higher rate of travel and pathways) are then derived in conjunction with ecological and environmental aspects that govern the species establishment. The benefits of the presented approach include robustness to data uncertainties, implicit incorporation of "stepping-stone" spread of invasive species, and decoupling of species spread and establishment risk estimation. Our analysis of a multi-year (1997--2006) GSN dataset using the presented approach shows the existence of a few large clusters of ports with higher intra-cluster species flow that are fairly stable over time. Furthermore, detailed investigations were carried out on vessel types, ports, and inter-cluster connections. Finally, our observations are discussed in the context of known NIS invasions and future research directions are also presented.
Real Time Strategy Language
Venue: arXiv cs.AI 2014
Year: 2014

Real Time Strategy (RTS) games provide complex domain to test the latest artificial intelligence (AI) research. In much of the literature, AI systems have been limited to playing one game. Although, this specialization has resulted in stronger AI gaming systems it does not address the key concerns of AI researcher. AI researchers seek the development of AI agents that can autonomously interpret learn, and apply new knowledge. To achieve human level performance, current AI systems rely on game specific knowledge of an expert. The paper presents the full RTS language in hopes of shifting the current research focus to the development of general RTS agents. General RTS agents are AI gaming systems that can play any RTS games, defined in the RTS language. This prevents game specific knowledge from being hard coded into the system, thereby facilitating research that addresses the fundamental concerns of artificial intelligence.
Exploiting Spectral Leakage for Spectrogram Frequency Super-resolution
Venue: arXiv cs.IT 2014
Year: 2014

The spectrogram is a classical DSP tool used to view signals in both time and frequency. Unfortunately, the Heisenberg Uncertainty Principal limits our ability to use them for detecting and measuring narrowband signal modulation in wideband environments. On a spectrogram, instantaneous frequency can only be measured to the nearest bin without additional interpolation. This work presents a novel technique for extracting higher accuracy frequency estimates. Whereas most practitioners seek to suppress spectral leakage, we use mismatched windows to exploit such artifacts in order to produce super-resolved spectral displays. We present a derivation of our methodology and exhibit several interesting examples.
Evolution Towards 5G Multi-tier Cellular Wireless Networks: An Interference Management Perspective
Venue: arXiv cs.NI 2014
Year: 2014

The evolving fifth generation (5G) cellular wireless networks are envisioned to overcome the fundamental challenges of existing cellular networks, e.g., higher data rates, excellent end-to-end performance and user-coverage in hot-spots and crowded areas with lower latency, energy consumption and cost per information transfer. To address these challenges, 5G systems need to adopt a multi-tier architecture consisting of macrocells, different types of licensed small cells, relays, and device-to-device (D2D) networks to serve users with different quality-of-service (QoS) requirements in a spectrum and energy-efficient manner. Starting with the visions and requirements of 5G multi-tier networks, this article outlines the challenges of interference management (e.g., power control, cell association) in these networks with shared spectrum access (i.e., when the different network tiers shares the same licensed spectrum). It is argued that the existing interference management schemes will not be able to address the interference management problem in prioritized 5G multi-tier networks where users in different tiers have different priorities for channel access. In this context, a survey and qualitative comparison of the potential existing cell association and power control schemes is provided to demonstrate their limitations for interference management in 5G networks. Open challenges are highlighted and guidelines are provided to modify the existing schemes in order to overcome these limitations and make them suitable for the emerging 5G systems.
Learning Mid-Level Features and Modeling Neuron Selectivity for Image Classification
Venue: arXiv cs.CV 2014
Year: 2014

We now know that mid-level features can greatly enhance the performance of image learning, but how to automatically learn the image features efficiently and in an unsupervised manner is still an open question. In this paper, we present a very efficient mid-level feature learning approach (MidFea), which only involves simple operations such as $k$-means clustering, convolution, pooling, vector quantization and random projection. We explain why this simple method generates the desired features, and argue that there is no need to spend much time in learning low-level feature extractors. Furthermore, to boost the performance, we propose to model the neuron selectivity (NS) principle by building an additional layer over the mid-level features before feeding the features into the classifier. We show that the NS-layer learns category-specific neurons with both bottom-up inference and top-down analysis, and thus supports fast inference for a query image. We run extensive experiments on several public databases to demonstrate that our approach can achieve state-of-the-art performances for face recognition, gender classification, age estimation and object categorization. In particular, we demonstrate that our approach is more than an order of magnitude faster than some recently proposed sparse coding based methods.
On Discrete Alphabets for the Two-user Gaussian Interference Channel with One Receiver Lacking Knowledge of the Interfering Codebook
Venue: arXiv cs.IT 2014
Year: 2014

In multi-user information theory it is often assumed that every node in the network possesses all codebooks used in the network. This assumption is however impractical in distributed ad-hoc and cognitive networks. This work considers the two- user Gaussian Interference Channel with one Oblivious Receiver (G-IC-OR), i.e., one receiver lacks knowledge of the interfering cookbook while the other receiver knows both codebooks. We ask whether, and if so how much, the channel capacity of the G-IC- OR is reduced compared to that of the classical G-IC where both receivers know all codebooks. Intuitively, the oblivious receiver should not be able to jointly decode its intended message along with the unintended interfering message whose codebook is unavailable. We demonstrate that in strong and very strong interference, where joint decoding is capacity achieving for the classical G-IC, lack of codebook knowledge does not reduce performance in terms of generalized degrees of freedom (gDoF). Moreover, we show that the sum-capacity of the symmetric G-IC- OR is to within O(log(log(SNR))) of that of the classical G-IC. The key novelty of the proposed achievable scheme is the use of a discrete input alphabet for the non-oblivious transmitter, whose cardinality is appropriately chosen as a function of SNR.
On Controllability and Near-controllability of Multi-input Discrete-time Bilinear Systems in Dimension Two
Venue: arXiv cs.SY 2014
Year: 2014

This paper completely solves the controllability problems of two-dimensional multi-input discrete-time bilinear systems with and without drift. Necessary and sufficient conditions for controllability, which cover the existing results, are obtained by using an algebraic method. Furthermore, for the uncontrollable systems, near-controllability is studied and necessary and sufficient conditions for the systems to be nearly controllable are also presented. Examples are provided to demonstrate the conceptions and results of the paper.
Dimensional operators for mathematical morphology on simplicial complexes
Venue: arXiv cs.DM 2014
Year: 2014

In this work we study the framework of mathematical morphology on simplicial complex spaces. Simplicial complexes are widely used to represent multidimensional data, such as meshes, that are two dimensional complexes, or graphs, that can be interpreted as one dimensional complexes. Mathematical morphology is one of the most powerful frameworks for image processing, including the processing of digital structures, and is heavily used for many applications. However, mathematical morphology operators on simplicial complex spaces is not a concept fully developed in the literature. Specifically, we explore properties of the dimensional operators, small, versatile operators that can be used to define new operators on simplicial complexes, while maintaining properties from mathematical morphology. These operators can also be used to recover many morphological operators from the literature. Matlab code and additional material, including the proofs of the original properties, are freely available at \url{https://code.google.com/p/math-morpho-simplicial-complexes.}
Enhancing Mobile Object Classification Using Geo-referenced Maps and Evidential Grids
Venue: arXiv cs.RO 2014
Year: 2014

Evidential grids have recently shown interesting properties for mobile object perception. Evidential grids are a generalisation of Bayesian occupancy grids using Dempster- Shafer theory. In particular, these grids can handle efficiently partial information. The novelty of this article is to propose a perception scheme enhanced by geo-referenced maps used as an additional source of information, which is fused with a sensor grid. The paper presents the key stages of such a data fusion process. An adaptation of conjunctive combination rule is presented to refine the analysis of the conflicting information. The method uses temporal accumulation to make the distinction between stationary and mobile objects, and applies contextual discounting for modelling information obsolescence. As a result, the method is able to better characterise the occupied cells by differentiating, for instance, moving objects, parked cars, urban infrastructure and buildings. Experiments carried out on real- world data illustrate the benefits of such an approach.
How science maps reveal knowledge transfer: new measurement for a historical case
Venue: arXiv cs.DL 2014
Year: 2014

Modelling actors of science via science (overlay) maps has recently become a popular practice in Interdisciplinarity Research (IDR). The benefits of this toolkit have also been recognized for other areas of scientometrics, such as the study of science dynamics. In this paper we propose novel methods of measuring knowledge diffusion/integration based on previous applications of the overlay methodology. New indices called Mean Overlay Distance and Overlay Diversity Ratio, respectively, are being drawn from previous uses of the Stirling index as the main proxy for knowledge diversification. We demonstrate the added value of this proposal via a case study addressing the development of a rather complex discourse in biology, usually referred to as the Species Problem. The selected topic is known for a history connecting various research fields and traditions, being, therefore, both an ideal and challenging case for the study of knowledge diffusion.
Capacities and Capacity-Achieving Decoders for Various Fingerprinting Games
Venue: arXiv cs.IT 2014
Year: 2014

Combining an information-theoretic approach to fingerprinting with a more constructive, statistical approach, we derive new results on the fingerprinting capacities for various informed settings, as well as new log-likelihood decoders with provable code lengths that asymptotically match these capacities. The simple decoder built against the interleaving attack is further shown to achieve the simple capacity for unknown attacks, and is argued to be an improved version of the recently proposed decoder of Oosterwijk et al. With this new universal decoder, cut-offs on the bias distribution function can finally be dismissed. Besides the application of these results to fingerprinting, a direct consequence of our results to group testing is that (i) a simple decoder asymptotically requires a factor 1.44 more tests to find defectives than a joint decoder, and (ii) the simple decoder presented in this paper provably achieves this bound.
Sentence Compression as Tree Transduction
Venue: arXiv cs.CL 2014
Year: 2014

This paper presents a tree-to-tree transduction method for sentence compression. Our model is based on synchronous tree substitution grammar, a formalism that allows local distortion of the tree topology and can thus naturally capture structural mismatches. We describe an algorithm for decoding in this framework and show how the model can be trained discriminatively within a large margin framework. Experimental results on sentence compression bring significant improvements over a state-of-the-art model.