OpenRaiser/Intern-Atlas huggingface dataset:
A Survey on Mobile Data Gathering in Wireless Sensor Networks - Bounded Relay
Venue: arXiv cs.NI 2014
Year: 2014

Most of the wireless sensor networks consist of static sensors, which can be deployed in a wide environment for monitoring applications. While transmitting the data from source to static sink, the amount of energy consumption of the sensor node is high. It results in reduced lifetime of the network.Some of the WSN architectures have been proposed based on Mobile Elements. There is large number of approaches to resolve the above problem. It is found those two approaches, namely Single Hop Data Gathering problem (SHDGP) and mobile Data Gathering, which is used to increase the lifetime of the network. Single Hop Data Gathering Problem is used to achieve the uniform energy consumption. The mobile Data Gathering algorithm is used to find the minimal set of points in the sensor network, which serves as data gathering points for mobile network. Even after so many decades of research, there are some unresolved problems like non uniform energy consumption, increased latency, which needs to be resolved.
Mnemonical Body Shortcuts: Gestural Interface for Mobile Devices
Venue: arXiv cs.HC 2014
Year: 2014

Mobile devices' user interfaces are still quite similar to traditional interfaces offered by desktop computers, but those can be highly problematic when used in a mobile context. Human gesture recognition in mobile interaction appears as an important area to provide suitable on-the-move usability. We present a body space based approach to improve mobile device interaction and mobile performance, which we named as Mnemonical Body Shortcuts. The human body is presented as a rich repository of meaningful relations which are always available to interact with. These body-based gestures allow the user to naturally interact with mobile devices with no movement limitations. Preliminary studies using Radio Frequency Identification (RFID) technology were performed, validating Mnemonical Body Shortcuts as an appropriate new mobile interaction mechanism. Following those studies, we developed inertial sensing prototypes using an accelerometer, ending in the construction and user testing of a gestural interface for mobile devices capable of properly recognizing Mnemonical Body Shortcuts and also providing suitable user control mechanisms and audio, visual and haptic feedback.
A Survey on Spatial Co-location Patterns Discovery from Spatial Datasets
Venue: arXiv cs.DB 2014
Year: 2014

Spatial data mining or Knowledge discovery in spatial database is the extraction of implicit knowledge, spatial relations and spatial patterns that are not explicitly stored in databases. Co-location patterns discovery is the process of finding the subsets of features that are frequently located together in the same geographic area. In this paper, we discuss the different approaches like Rule based approach, Join-less approach, Partial Join approach and Constraint neighborhood based approach for finding co-location patterns.
Simulation work on Fractional Order PIλ Control Strategy for speed control of DC motor based on stability boundary locus method
Venue: arXiv cs.SY 2014
Year: 2014

This paper deals with the design of Fractional Order Proportional Integral (FO-PIλ) controller for the speed control of DC motor. A mathematical model of DC motor control system is derived and based on this model fractional order PIλ controller is designed using stability boundary locus method to satisfy required gain margin (GM) and phase margin (PM) of the system. Servo and Regulatory tracking simulation runs are carried out for the speed control of DC motor. The performance of the fractional order PIλ (FO-PIλ) controller is compared with Integer Order Relay Feedback Proportional Integral (IO-RFPI) controller. Finally the stability of both control system is considered.
Towards a Characterization of Leaf Powers by Clique Arrangements
Venue: arXiv cs.DM 2014
Year: 2014

The class ${\cal L}_k$ of $k$-leaf powers consists of graphs $G=(V,E)$ that have a $k$-leaf root, that is, a tree $T$ with leaf set $V$, where $xy \in E$, if and only if the $T$-distance between $x$ and $y$ is at most $k$. Structure and linear time recognition algorithms have been found for $2$-, $3$-, $4$-, and, to some extent, $5$-leaf powers, and it is known that the union of all $k$-leaf powers, that is, the graph class ${\cal L} = \bigcup_{k=2}^\infty {\cal L}_k$, forms a proper subclass of strongly chordal graphs. Despite from that, no essential progress has been made lately. In this paper, we use the new notion of clique arrangements to suggest that leaf powers are a natural special case of strongly chordal graphs. The clique arrangement ${\cal A}(G)$ of a chordal graph $G$ is a directed graph that represents the intersections between maximal cliques of $G$ by nodes and the mutual inclusion of these vertex subsets by arcs. Recently, strongly chordal graphs have been characterized as the graphs that have a clique arrangement without bad $k$-cycles for $k \geq 3$. We show that the clique arrangement of every graph of ${\cal L}$ is free of bad $2$-cycles. The question whether this characterizes the class ${\cal L}$ exactly remains open.
Uncertainty Propagation in Elasto-Plastic Material
Venue: arXiv cs.CE 2014
Year: 2014

Macroscopically heterogeneous materials, characterised mostly by comparable heterogeneity lengthscale and structural sizes, can no longer be modelled by deterministic approach instead. It is convenient to introduce stochastic approach with uncertain material parameters quantified as random fields and/or random variables. The present contribution is devoted to propagation of these uncertainties in mechanical modelling of inelastic behaviour. In such case the Monte Carlo method is the traditional approach for solving the proposed problem. Nevertheless, convergence rate is relatively slow, thus new methods (e.g. stochastic Galerkin method, stochastic collocation approach, etc.) have been recently developed to offer fast convergence for sufficiently smooth solution in the probability space. Our goal is to accelerate the uncertainty propagation using a polynomial chaos expansion based on stochastic collocation method. The whole concept is demonstrated on a simple numerical example of uniaxial test at a material point where interesting phenomena can be clearly understood.
Dictionary Learning over Distributed Models
Venue: arXiv cs.LG 2014
Year: 2014

In this paper, we consider learning dictionary models over a network of agents, where each agent is only in charge of a portion of the dictionary elements. This formulation is relevant in Big Data scenarios where large dictionary models may be spread over different spatial locations and it is not feasible to aggregate all dictionaries in one location due to communication and privacy considerations. We first show that the dual function of the inference problem is an aggregation of individual cost functions associated with different agents, which can then be minimized efficiently by means of diffusion strategies. The collaborative inference step generates dual variables that are used by the agents to update their dictionaries without the need to share these dictionaries or even the coefficient models for the training data. This is a powerful property that leads to an effective distributed procedure for learning dictionaries over large networks (e.g., hundreds of agents in our experiments). Furthermore, the proposed learning strategy operates in an online manner and is able to respond to streaming data, where each data sample is presented to the network once.
TDOA--based localization in two dimensions: the bifurcation curve
Venue: arXiv cs.SD 2014
Year: 2014

In this paper, we complete the study of the geometry of the TDOA map that encodes the noiseless model for the localization of a source from the range differences between three receivers in a plane, by computing the Cartesian equation of the bifurcation curve in terms of the positions of the receivers. From that equation, we can compute its real asymptotic lines. The present manuscript completes the analysis of [Inverse Problems, Vol. 30, Number 3, Pages 035004]. Our result is useful to check if a source belongs or is closed to the bifurcation curve, where the localization in a noisy scenario is ambiguous.
The Tactical Optimal Strategy Game (TOSG) Protocol Cockpit Software Control For Massive Ordnance Penetrator Release
Venue: arXiv cs.CY 2014
Year: 2014

The Massive Ordnance Penetrator(MOP) has been developed to destroy deeply buried nuclear components by controlled release from a B2 or B52 airplane. This type of release must be cockpit software controlled by the Tactical Optimal Strategy Game(TOSG) Protocol to optimally determine the war game aspects of the dueling from other countries' MOP releases, and the depth at which the MOP explosions can occur for maximal safety and risk concerns. The TOSG Protocol characteristics of games of strategy, games of optimal strategy and tactical games are defined initially by the game of strategy as a certain series of events, each of which must have a finite number of distinct results. The outcome of a game of strategy, in some cases, depends on chance. All other events depend on the free decision of the players. A game has a solution if there exist two strategies, which become optimal strategies when each mathematically attains the value of the game. The TOSG Protocol war game tactical problem for a class of games can be mathematically modeled as a combat between two airplanes, each carrying a MOP as the specification of the accuracy of the firing machinery and the total amount of ammunition that each plane carries. This silent duel occurs, because each MOP bomber is unable to determine the number of times its opponent has missed. The TOSG Protocol realizes a game theory solution of the tactical optimal strategy game utilizing the theory of games of timing, games of pursuit, games of time lag, games of sequence, games of maneuvering, games of search, games of positioning and games of aiming and evasion.
PRESS: A Novel Framework of Trajectory Compression in Road Networks
Venue: arXiv cs.DB 2014
Year: 2014

Location data becomes more and more important. In this paper, we focus on the trajectory data, and propose a new framework, namely PRESS (Paralleled Road-Network-Based Trajectory Compression), to effectively compress trajectory data under road network constraints. Different from existing work, PRESS proposes a novel representation for trajectories to separate the spatial representation of a trajectory from the temporal representation, and proposes a Hybrid Spatial Compression (HSC) algorithm and error Bounded Temporal Compression (BTC) algorithm to compress the spatial and temporal information of trajectories respectively. PRESS also supports common spatial-temporal queries without fully decompressing the data. Through an extensive experimental study on real trajectory dataset, PRESS significantly outperforms existing approaches in terms of saving storage cost of trajectory data with bounded errors.
The Performance of Successive Interference Cancellation in Random Wireless Networks
Venue: arXiv cs.IT 2014
Year: 2014

This paper provides a unified framework to study the performance of successive interference cancellation (SIC) in wireless networks with arbitrary fading distribution and power-law path loss. An analytical characterization of the performance of SIC is given as a function of different system parameters. The results suggest that the marginal benefit of enabling the receiver to successively decode k users diminishes very fast with k, especially in networks of high dimensions and small path loss exponent. On the other hand, SIC is highly beneficial when the users are clustered around the receiver and/or very low-rate codes are used. Also, with multiple packet reception, a lower per-user information rate always results in higher aggregate throughput in interference-limited networks. In contrast, there exists a positive optimal per-user rate that maximizes the aggregate throughput in noisy networks. The analytical results serve as useful tools to understand the potential gain of SIC in heterogeneous cellular networks (HCNs). Using these tools, this paper quantifies the gain of SIC on the coverage probability in HCNs with non-accessible base stations. An interesting observation is that, for contemporary narrow-band systems (e.g., LTE and WiFi), most of the gain of SIC is achieved by canceling a single interferer.
New Outer Bounds for the Interference Channel with Unilateral Source Cooperation
Venue: arXiv cs.IT 2014
Year: 2014

This paper studies the two-user interference channel with unilateral source cooperation, which consists of two source-destination pairs that share the same channel and where one full-duplex source can overhear the other source through a noisy in-band link. Novel outer bounds of the type 2Rp+Rc/Rp+2Rc are developed for the class of injective semi-deterministic channels with independent noises at the different source-destination pairs. The bounds are then specialized to the Gaussian noise case. Interesting insights are provided about when these types of bounds are active, or in other words, when unilateral cooperation is too weak and leaves "holes" in the system resources.
Independent Set Reconfiguration in Cographs
Venue: arXiv cs.DM 2014
Year: 2014

We study the following independent set reconfiguration problem, called TAR-Reachability: given two independent sets $I$ and $J$ of a graph $G$, both of size at least $k$, is it possible to transform $I$ into $J$ by adding and removing vertices one-by-one, while maintaining an independent set of size at least $k$ throughout? This problem is known to be PSPACE-hard in general. For the case that $G$ is a cograph (i.e. $P_4$-free graph) on $n$ vertices, we show that it can be solved in time $O(n^2)$, and that the length of a shortest reconfiguration sequence from $I$ to $J$ is bounded by $4n-2k$, if such a sequence exists. More generally, we show that if $X$ is a graph class for which (i) TAR-Reachability can be solved efficiently, (ii) maximum independent sets can be computed efficiently, and which satisfies a certain additional property, then the problem can be solved efficiently for any graph that can be obtained from a collection of graphs in $X$ using disjoint union and complete join operations. Chordal graphs are given as an example of such a class $X$.
Numerical solving the boundary value problem for fractional powers of elliptic operators
Venue: arXiv cs.NA 2014
Year: 2014

A boundary value problem for a fractional power of the second-order elliptic operator is considered. It is solved numerically using a time-dependent problem for a pseudo-parabolic equation. For the auxiliary Cauchy problem, the standard two-level schemes with weights are applied. Stability conditions are obtained for the fully discrete schemes under the consideration. The numerical results are presented for a model two-dimensional boundary value problem wit a fractional power of an elliptic operator. The dependence of accuracy on grids in time and in space is studied.
Vertical Clustering of 3D Elliptical Helical Data
Venue: arXiv cs.CE 2014
Year: 2014

This research proposes an effective vertical clustering strategy of 3D data in an elliptical helical shape based on 2D geometry. The clustering object is an elliptical cross-sectioned metal pipe which is been bended in to an elliptical helical shape which is used in wearable muscle support designing for welfare industry. The aim of this proposed method is to maximize the vertical clustering (vertical partitioning) ability of surface data in order to run the product evaluation process addressed in research [2]. The experiment results prove that the proposed method outperforms the existing threshold no of clusters that preserves the vertical shape than applying the conventional 3D data. This research also proposes a new product testing strategy that provides the flexibility in computer aided testing by not restricting the sequence depending measurements which apply weight on measuring process. The clustering algorithms used for the experiments in this research are self-organizing map (SOM) and K-medoids.
Frequency-Based Patrolling with Heterogeneous Agents and Limited Communication
Venue: arXiv cs.MA 2014
Year: 2014

This paper investigates multi-agent frequencybased patrolling of intersecting, circle graphs under conditions where graph nodes have non-uniform visitation requirements and agents have limited ability to communicate. The task is modeled as a partially observable Markov decision process, and a reinforcement learning solution is developed. Each agent generates its own policy from Markov chains, and policies are exchanged only when agents occupy the same or adjacent nodes. This constraint on policy exchange models sparse communication conditions over large, unstructured environments. Empirical results provide perspectives on convergence properties, agent cooperation, and generalization of learned patrolling policies to new instances of the task. The emergent behavior indicates learned coordination strategies between heterogeneous agents for patrolling large, unstructured regions as well as the ability to generalize to dynamic variation in node visitation requirements.
On Scalability of Wireless Networks: A Practical Primer for Large Scale Cooperation
Venue: arXiv cs.IT 2014
Year: 2014

An intuitive overview of the scalability of a variety of types of wireless networks is presented. Simple heuris- tic arguments are demonstrated here for scaling laws presented in other works, as well as for conditions not previously considered in the literature. Unicast and multicast messages, topology, hierarchy, and effects of reliability protocols are discussed. We show how two key factors, bottlenecks and erasures, can often domi- nate the network scaling behavior. Scaling of through- put or delay with the number of transmitting nodes, the number of receiving nodes, and the file size is described.
Cascading Failures in Power Grids - Analysis and Algorithms
Venue: arXiv cs.SY 2014
Year: 2014

This paper focuses on cascading line failures in the transmission system of the power grid. Recent large-scale power outages demonstrated the limitations of percolation- and epid- emic-based tools in modeling cascades. Hence, we study cascades by using computational tools and a linearized power flow model. We first obtain results regarding the Moore-Penrose pseudo-inverse of the power grid admittance matrix. Based on these results, we study the impact of a single line failure on the flows on other lines. We also illustrate via simulation the impact of the distance and resistance distance on the flow increase following a failure, and discuss the difference from the epidemic models. We then study the cascade properties, considering metrics such as the distance between failures and the fraction of demand (load) satisfied after the cascade (yield). We use the pseudo-inverse of admittance matrix to develop an efficient algorithm to identify the cascading failure evolution, which can be a building block for cascade mitigation. Finally, we show that finding the set of lines whose removal has the most significant impact (under various metrics) is NP-Hard and introduce a simple heuristic for the minimum yield problem. Overall, the results demonstrate that using the resistance distance and the pseudo-inverse of admittance matrix provides important insights and can support the development of efficient algorithms.
A Study Of Cyber Security Challenges And Its Emerging Trends On Latest Technologies
Venue: arXiv cs.CR 2014
Year: 2014

Cyber Security plays an important role in the field of information technology .Securing the information have become one of the biggest challenges in the present day. When ever we think about the cyber security the first thing that comes to our mind is cyber crimes which are increasing immensely day by day. Various Governments and companies are taking many measures in order to prevent these cyber crimes. Besides various measures cyber security is still a very big concern to many. This paper mainly focuses on challenges faced by cyber security on the latest technologies .It also focuses on latest about the cyber security techniques, ethics and the trends changing the face of cyber security.
Sparse Illumination Learning and Transfer for Single-Sample Face Recognition with Image Corruption and Misalignment
Venue: arXiv cs.CV 2014
Year: 2014

Single-sample face recognition is one of the most challenging problems in face recognition. We propose a novel algorithm to address this problem based on a sparse representation based classification (SRC) framework. The new algorithm is robust to image misalignment and pixel corruption, and is able to reduce required gallery images to one sample per class. To compensate for the missing illumination information traditionally provided by multiple gallery images, a sparse illumination learning and transfer (SILT) technique is introduced. The illumination in SILT is learned by fitting illumination examples of auxiliary face images from one or more additional subjects with a sparsely-used illumination dictionary. By enforcing a sparse representation of the query image in the illumination dictionary, the SILT can effectively recover and transfer the illumination and pose information from the alignment stage to the recognition stage. Our extensive experiments have demonstrated that the new algorithms significantly outperform the state of the art in the single-sample regime and with less restrictions. In particular, the single-sample face alignment accuracy is comparable to that of the well-known Deformable SRC algorithm using multiple gallery images per class. Furthermore, the face recognition accuracy exceeds those of the SRC and Extended SRC algorithms using hand labeled alignment initialization.
Revisiting the Learned Clauses Database Reduction Strategies
Venue: arXiv cs.AI 2014
Year: 2014

In this paper, we revisit an important issue of CDCL-based SAT solvers, namely the learned clauses database management policies. Our motivation takes its source from a simple observation on the remarkable performances of both random and size-bounded reduction strategies. We first derive a simple reduction strategy, called Size-Bounded Randomized strategy (in short SBR), that combines maintaing short clauses (of size bounded by k), while deleting randomly clauses of size greater than k. The resulting strategy outperform the state-of-the-art, namely the LBD based one, on SAT instances taken from the last SAT competition. Reinforced by the interest of keeping short clauses, we propose several new dynamic variants, and we discuss their performances.