OpenRaiser/Intern-Atlas huggingface dataset:
Ontology-supported processing of clinical text using medical knowledge integration for multi-label classification of diagnosis coding
Venue: arXiv cs.LG 2010
Year: 2010

This paper discusses the knowledge integration of clinical information extracted from distributed medical ontology in order to ameliorate a machine learning-based multi-label coding assignment system. The proposed approach is implemented using a decision tree based cascade hierarchical technique on the university hospital data for patients with Coronary Heart Disease (CHD). The preliminary results obtained show a satisfactory finding.
Spectral Methods for Matrices and Tensors
Venue: arXiv cs.DS 2010
Year: 2010

While Spectral Methods have long been used for Principal Component Analysis, this survey focusses on work over the last 15 years with three salient features: (i) Spectral methods are useful not only for numerical problems, but also discrete optimization problems (Constraint Optimization Problems - CSP's) like the max. cut problem and similar mathematical considerations underlie both areas. (ii) Spectral methods can be extended to tensors. The theory and algorithms for tensors are not as simple/clean as for matrices, but the survey describes methods for low-rank approximation which extend to tensors. These tensor approximations help us solve Max-$r$-CSP's for $r>2$ as well as numerical tensor problems. (iii) Sampling on the fly plays a prominent role in these methods. A primary result is that for any matrix, a random submatrix of rows/columns picked with probabilities proportional to the squared lengths (of rows/columns), yields estimates of the singular values as well as an approximation to the whole matrix.
A Survey on Preprocessing Methods for Web Usage Data
Venue: arXiv cs.IR 2010
Year: 2010

World Wide Web is a huge repository of web pages and links. It provides abundance of information for the Internet users. The growth of web is tremendous as approximately one million pages are added daily. Users' accesses are recorded in web logs. Because of the tremendous usage of web, the web log files are growing at a faster rate and the size is becoming huge. Web data mining is the application of data mining techniques in web data. Web Usage Mining applies mining techniques in log data to extract the behavior of users which is used in various applications like personalized services, adaptive web sites, customer profiling, prefetching, creating attractive web sites etc., Web usage mining consists of three phases preprocessing, pattern discovery and pattern analysis. Web log data is usually noisy and ambiguous and preprocessing is an important process before mining. For discovering patterns sessions are to be constructed efficiently. This paper reviews existing work done in the preprocessing stage. A brief overview of various data mining techniques for discovering patterns, and pattern analysis are discussed. Finally a glimpse of various applications of web usage mining is also presented.
Construction of minimal DFAs from biological motifs
Venue: arXiv cs.FL 2010
Year: 2010

Deterministic finite automata (DFAs) are constructed for various purposes in computational biology. Little attention, however, has been given to the efficient construction of minimal DFAs. In this article, we define simple non-deterministic finite automata (NFAs) and prove that the standard subset construction transforms NFAs of this type into minimal DFAs. Furthermore, we show how simple NFAs can be constructed from two types of patterns popular in bioinformatics, namely (sets of) generalized strings and (generalized) strings with a Hamming neighborhood.
Provable Secure Identity Based Generalized Signcryption Scheme
Venue: arXiv cs.CR 2010
Year: 2010

According to actual needs, generalized signcryption scheme can flexibly work as an encryption scheme, a signature scheme or a signcryption scheme. In this paper, firstly, we give a security model for identity based generalized signcryption which is more complete than existing model. Secondly, we propose an identity based generalized signcryption scheme. Thirdly, we give the security proof of the new scheme in this complete model. Comparing with existing identity based generalized signcryption, the new scheme has less implementation complexity. Moreover, the new scheme has comparable computation complexity with the existing normal signcryption schemes.
GeneSyst: a Tool to Reason about Behavioral Aspects of B Event Specifications. Application to Security Properties.
Venue: arXiv cs.LO 2010
Year: 2010

In this paper, we present a method and a tool to build symbolic labelled transition systems from B specifications. The tool, called GeneSyst, can take into account refinement levels and can visualize the decomposition of abstract states in concrete hierarchical states. The resulting symbolic transition system represents all the behaviors of the initial B event system. So, it can be used to reason about them. We illustrate the use of GeneSyst to check security properties on a model of electronic purse.
Optimal stochastic planarization
Venue: arXiv cs.CG 2010
Year: 2010

It has been shown by Indyk and Sidiropoulos [IS07] that any graph of genus g>0 can be stochastically embedded into a distribution over planar graphs with distortion 2^O(g). This bound was later improved to O(g^2) by Borradaile, Lee and Sidiropoulos [BLS09]. We give an embedding with distortion O(log g), which is asymptotically optimal. Apart from the improved distortion, another advantage of our embedding is that it can be computed in polynomial time. In contrast, the algorithm of [BLS09] requires solving an NP-hard problem. Our result implies in particular a reduction for a large class of geometric optimization problems from instances on genus-g graphs, to corresponding ones on planar graphs, with a O(log g) loss factor in the approximation guarantee.
Fuzzy Logic of Speed and Steering Control System for Three Dimensional Line Following of an Autonomous Vehicle
Venue: arXiv cs.RO 2010
Year: 2010

... This paper is to describe exploratory research on the design of a modular autonomous mobile robot controller. The controller incorporates a fuzzy logic [8] [9] approach for steering and speed control [37], a FL approach for ultrasound sensing and an overall expert system for guidance. The advantages of a modular system are related to portability and transportability, i.e. any vehicle can become autonomous with minimal modifications. A mobile robot test bed has been constructed in university of Cincinnati using a golf cart base. This cart has full speed control with guidance provided by a vision system and obstacle avoidance using ultrasonic sensors. The speed and steering fuzzy logic controller is supervised through a multi-axis motion controller. The obstacle avoidance system is based on a microcontroller interfaced with ultrasonic transducers. This micro-controller independently handles all timing and distance calculations and sends distance information back to the fuzzy logic controller via the serial line. This design yields a portable independent system in which high speed computer communication is not necessary. Vision guidance has been accomplished with the use of CCD cameras judging the current position of the robot.[34] [35][36] It will be generating a good image for reducing an uncertain wrong command from ground coordinate to tackle the parameter uncertainties of the system, and to obtain good WMR dynamic response.[1] Here we Apply 3D line following mythology. It transforms from 3D to 2D and also maps the image coordinates and vice versa, leading to the improved accuracy of the WMR position. ...
A reversible high embedding capacity data hiding technique for hiding secret data in images
Venue: arXiv cs.MM 2010
Year: 2010

As the multimedia and internet technologies are growing fast, the transmission of digital media plays an important role in communication. The various digital media like audio, video and images are being transferred through internet. There are a lot of threats for the digital data that are transferred through internet. Also, a number of security techniques have been employed to protect the data that is transferred through internet. This paper proposes a new technique for sending secret messages securely, using steganographic technique. Since the proposed system uses multiple level of security for data hiding, where the data is hidden in an image file and the stego file is again concealed in another image. Previously, the secret message is being encrypted with the encryption algorithm which ensures the achievement of high security enabled data transfer through internet.
A Robust Fuzzy Clustering Technique with Spatial Neighborhood Information for Effective Medical Image Segmentation
Venue: arXiv cs.CV 2010
Year: 2010

Medical image segmentation demands an efficient and robust segmentation algorithm against noise. The conventional fuzzy c-means algorithm is an efficient clustering algorithm that is used in medical image segmentation. But FCM is highly vulnerable to noise since it uses only intensity values for clustering the images. This paper aims to develop a novel and efficient fuzzy spatial c-means clustering algorithm which is robust to noise. The proposed clustering algorithm uses fuzzy spatial information to calculate membership value. The input image is clustered using proposed ISFCM algorithm. A comparative study has been made between the conventional FCM and proposed ISFCM. The proposed approach is found to be outperforming the conventional FCM.
Design And Implementation Of Multilevel Access Control In Medical Image Transmission Using Symmetric Polynomial Based Audio Steganography
Venue: arXiv cs.MM 2010
Year: 2010

...The steganography scheme makes it possible to hide the medical image in different bit locations of host media without inviting suspicion. The Secret file is embedded in a cover media with a key. At the receiving end the key can be derived by all the classes which are higher in the hierarchy using symmetric polynomial and the medical image file can be retrieved. The system is implemented and found to be secure, fast and scalable. Simulation results show that the system is dynamic in nature and allows any type of hierarchy. The proposed approach performs better even during frequent member joins and leaves. The computation cost is reduced as the same algorithm is used for key computation and descendant key derivation. Steganographic technique used in this paper does not use the conventional LSB's and uses two bit positions and the hidden data occurs only from a frame which is dictated by the key that is used. Hence the quality of stego data is improved.
Mathematical Principles in Software Quality Engineering
Venue: arXiv cs.SE 2010
Year: 2010

Mathematics has many useful properties for developing of complex software systems. One is that it can exactly describe a physical situation of the object or outcome of an action. Mathematics support abstraction and this is an excellent medium for modeling, since it is an exact medium there is a little possibility of ambiguity. This paper demonstrates that mathematics provides a high level of validation when it is used as a software medium. It also outlines distinguishing characteristics of structural testing which is based on the source code of the program tested. Structural testing methods are very amenable to rigorous definition, mathematical analysis and precise measurement. Finally, it also discusses functional and structural testing debate to have a sense of complete testing. Any program can be considered to be a function in the sense that program input forms its domain and program outputs form its range. In general discrete mathematics is more applicable to functional testing, while graph theory pertains more to structural testing.
Phase Transitions for Greedy Sparse Approximation Algorithms
Venue: arXiv cs.IT 2010
Year: 2010

A major enterprise in compressed sensing and sparse approximation is the design and analysis of computationally tractable algorithms for recovering sparse, exact or approximate, solutions of underdetermined linear systems of equations. Many such algorithms have now been proven to have optimal-order uniform recovery guarantees using the ubiquitous Restricted Isometry Property (RIP). However, it is unclear when the RIP-based sufficient conditions on the algorithm are satisfied. We present a framework in which this task can be achieved; translating these conditions for Gaussian measurement matrices into requirements on the signal's sparsity level, length, and number of measurements. We illustrate this approach on three of the state-of-the-art greedy algorithms: CoSaMP, Subspace Pursuit (SP), and Iterative Hard Thresholding (IHT). Designed to allow a direct comparison of existing theory, our framework implies that, according to the best known bounds, IHT requires the fewest number of compressed sensing measurements and has the lowest per iteration computational cost of the three algorithms compared here.
Maximized Posteriori Attributes Selection from Facial Salient Landmarks for Face Recognition
Venue: arXiv cs.CV 2010
Year: 2010

This paper presents a robust and dynamic face recognition technique based on the extraction and matching of devised probabilistic graphs drawn on SIFT features related to independent face areas. The face matching strategy is based on matching individual salient facial graph characterized by SIFT features as connected to facial landmarks such as the eyes and the mouth. In order to reduce the face matching errors, the Dempster-Shafer decision theory is applied to fuse the individual matching scores obtained from each pair of salient facial features. The proposed algorithm is evaluated with the ORL and the IITK face databases. The experimental results demonstrate the effectiveness and potential of the proposed face recognition technique also in case of partially occluded faces.
k-Edge-Connectivity: Approximation and LP Relaxation
Venue: arXiv cs.DM 2010
Year: 2010

In the k-edge-connected spanning subgraph problem we are given a graph (V, E) and costs for each edge, and want to find a minimum-cost subset F of E such that (V, F) is k-edge-connected. We show there is a constant eps > 0 so that for all k > 1, finding a (1 + eps)-approximation for k-ECSS is NP-hard, establishing a gap between the unit-cost and general-cost versions. Next, we consider the multi-subgraph cousin of k-ECSS, in which we purchase a multi-subset F of E, with unlimited parallel copies available at the same cost as the original edge. We conjecture that a (1 + Theta(1/k))-approximation algorithm exists, and we describe an approach based on graph decompositions applied to its natural linear programming (LP) relaxation. The LP is essentially equivalent to the Held-Karp LP for TSP and the undirected LP for Steiner tree. We give a family of extreme points for the LP which are more complex than those previously known.
A note on decidability of cellularity
Venue: arXiv cs.FL 2010
Year: 2010

A regular language L is said to be cellular if there exists a 1-dimensional cellular automaton CA such that L is the language consisting of the finite blocks associated with CA. It is shown that cellularity of a regular language is decidable using a new characterization of cellular languages formulated by Freiling, Goldstein and Moews and implied by a deep result of Boyle in symbolic dynamics.
State-Space Dynamics Distance for Clustering Sequential Data
Venue: arXiv cs.LG 2010
Year: 2010

This paper proposes a novel similarity measure for clustering sequential data. We first construct a common state-space by training a single probabilistic model with all the sequences in order to get a unified representation for the dataset. Then, distances are obtained attending to the transition matrices induced by each sequence in that state-space. This approach solves some of the usual overfitting and scalability issues of the existing semi-parametric techniques, that rely on training a model for each sequence. Empirical studies on both synthetic and real-world datasets illustrate the advantages of the proposed similarity measure for clustering sequences.
Improved information security using robust Steganography system
Venue: arXiv cs.CR 2010
Year: 2010

Steganography is an emerging area which is used for secured data transmission over any public media.Steganography is a process that involves hiding a message in an appropriate carrier like image or audio. It is of Greek origin and means "covered or hidden writing". The carrier can be sent to a receiver without any one except the authenticated receiver knowing the existence of this information. In this paper, a specific image based steganography technique for communicating information more securely between two locations is proposed. The author incorporated the idea of secret key and password security features for authentication at both ends in order to achieve high level of security. As a further improvement of security level, the information has been permuted, encoded and then finally embedded on an image to form the stego image. In addition segmented objects extraction and reassembly of the stego image through normalized cut method has been carried out at the sender side and receiver side respectively in order to prevent distortion of the Stego image during transmission.
Capacity Theorems for the AWGN Multi-Way Relay Channel
Venue: arXiv cs.IT 2010
Year: 2010

The L-user additive white Gaussian noise multi-way relay channel is considered, where multiple users exchange information through a single relay at a common rate. Existing coding strategies, i.e., complete-decode-forward and compress-forward are shown to be bounded away from the cut-set upper bound at high signal-to-noise ratios (SNR). It is known that the gap between the compress-forward rate and the capacity upper bound is a constant at high SNR, and that between the complete-decode-forward rate and the upper bound increases with SNR at high SNR. In this paper, a functional-decode-forward coding strategy is proposed. It is shown that for L >= 3, complete-decode-forward achieves the capacity when SNR <= 0 dB, and functional-decode-forward achieves the capacity when SNR >= 0 dB. For L=$, functional-decode-forward achieves the capacity asymptotically as SNR increases.
Kinematic modelling of a 3-axis NC machine tool in linear and circular interpolation
Venue: arXiv cs.OH 2010
Year: 2010

Machining time is a major performance criterion when it comes to high-speed machining. CAM software can help in estimating that time for a given strategy. But in practice, CAM-programmed feed rates are rarely achieved, especially where complex surface finishing is concerned. This means that machining time forecasts are often more than one step removed from reality. The reason behind this is that CAM routines do not take either the dynamic performances of the machines or their specific machining tolerances into account. The present article seeks to improve simulation of high-speed NC machine dynamic behaviour and machining time prediction, offering two models. The first contributes through enhanced simulation of three-axis paths in linear and circular interpolation, taking high-speed machine accelerations and jerks into account. The second model allows transition passages between blocks to be integrated in the simulation by adding in a polynomial transition path that caters for the true machining environment tolerances. Models are based on respect for path monitoring. Experimental validation shows the contribution of polynomial modelling of the transition passage due to the absence of a leap in acceleration. Simulation error on the machining time prediction remains below 1%.
On the optimal stacking of noisy observations
Venue: arXiv cs.IT 2010
Year: 2010

Observations where additive noise is present can for many models be grouped into a compound observation matrix, adhering to the same type of model. There are many ways the observations can be stacked, for instance vertically, horizontally, or quadratically. An estimator for the spectrum of the underlying model can be formulated for each stacking scenario in the case of Gaussian noise. We compare these spectrum estimators for the different stacking scenarios, and show that all kinds of stacking actually decreases the variance when compared to just taking an average of the observations. We show that, regardless of the number of observations, the variance of the estimator is smallest when the compound observation matrix is made as square as possible. When the number of observations grow, however, it is shown that the difference between the estimators is marginal: Two stacking scenarios where the number of columns and rows grow to infinity are shown to have the same variance asymptotically, even if the asymptotic matrix aspect ratios differ. Only the cases of vertical and horizontal stackings display different behaviour, giving a higher variance asymptotically. Models where not all kinds of stackings are possible are also discussed.
How to prevent type-flaw and multi-protocol attacks on cryptographic protocols under Exclusive-OR
Venue: arXiv cs.CR 2010
Year: 2010

Type-flaw attacks and multi-protocol attacks on security protocols have been frequently reported in the literature. Heather et al. and Guttman et al. have proven that these could be prevented by tagging encrypted components with distinct constants in a standard protocol model with free message algebra and perfect encryption. However, most "real-world" protocols such as SSL 3.0 are designed with the Exclusive-OR (XOR) operator that possesses algebraic properties, breaking the free algebra assumption. These algebraic properties induce equational theories that need to be considered when analyzing protocols that use the operator. This is the problem we consider in this paper: We prove that, under certain assumptions, tagging encrypted components still prevents type-flaw and multi-protocol attacks even in the presence of the XOR operator and its algebraic properties.
How Much Multiuser Diversity is Required for Energy Limited Multiuser Systems?
Venue: arXiv cs.IT 2010
Year: 2010

Multiuser diversity (MUDiv) is one of the central concepts in multiuser (MU) systems. In particular, MUDiv allows for scheduling among users in order to eliminate the negative effects of unfavorable channel fading conditions of some users on the system performance. Scheduling, however, consumes energy (e.g., for making users' channel state information available to the scheduler). This extra usage of energy, which could potentially be used for data transmission, can be very wasteful, especially if the number of users is large. In this paper, we answer the question of how much MUDiv is required for energy limited MU systems. Focusing on uplink MU wireless systems, we develop MU scheduling algorithms which aim at maximizing the MUDiv gain. Toward this end, we introduce a new realistic energy model which accounts for scheduling energy and describes the distribution of the total energy between scheduling and data transmission stages. Using the fact that such energy distribution can be controlled by varying the number of active users, we optimize this number by either (i) minimizing the overall system bit error rate (BER) for a fixed total energy of all users in the system or (ii) minimizing the total energy of all users for fixed BER requirements. We find that for a fixed number of available users, the achievable MUDiv gain can be improved by activating only a subset of users. Using asymptotic analysis and numerical simulations, we show that our approach benefits from MUDiv gains higher than that achievable by generic greedy access algorithm, which is the optimal scheduling method for energy unlimited systems.