OpenRaiser/Intern-Atlas huggingface dataset:
Using the Expectation Maximization Algorithm with Heterogeneous Mixture Components for the Analysis of Spectrometry Data
Venue: arXiv cs.OH 2014
Year: 2014

Coupling a multi-capillary column (MCC) with an ion mobility (IM) spectrometer (IMS) opened a multitude of new application areas for gas analysis, especially in a medical context, as volatile organic compounds (VOCs) in exhaled breath can hint at a person's state of health. To obtain a potential diagnosis from a raw MCC/IMS measurement, several computational steps are necessary, which so far have required manual interaction, e.g., human evaluation of discovered peaks. We have recently proposed an automated pipeline for this task that does not require human intervention during the analysis. Nevertheless, there is a need for improved methods for each computational step. In comparison to gas chromatography / mass spectrometry (GC/MS) data, MCC/IMS data is easier and less expensive to obtain, but peaks are more diffuse and there is a higher noise level. MCC/IMS measurements can be described as samples of mixture models (i.e., of convex combinations) of two-dimensional probability distributions. So we use the expectation-maximization (EM) algorithm to deconvolute mixtures in order to develop methods that improve data processing in three computational steps: denoising, baseline correction and peak clustering. A common theme of these methods is that mixture components within one model are not homogeneous (e.g., all Gaussian), but of different types. Evaluation shows that the novel methods outperform the existing ones. We provide Python software implementing all three methods and make our evaluation data available at http://www.rahmannlab.de/research/ims.
Application of Artificial Neural Networks in Predicting Abrasion Resistance of Solution Polymerized Styrene-Butadiene Rubber Based Composites
Venue: arXiv cs.CE 2014
Year: 2014

Abrasion resistance of solution polymerized styrene-butadiene rubber (SSBR) based composites is a typical and crucial property in practical applications. Previous studies show that the abrasion resistance can be calculated by the multiple linear regression model. In our study, considering this relationship can also be described into the non-linear conditions, a Multilayer Feed-forward Neural Networks model with 3 nodes (MLFN-3) was successfully established to describe the relationship between the abrasion resistance and other properties, using 23 groups of data, with the RMS error 0.07. Our studies have proved that Artificial Neural Networks (ANN) model can be used to predict the SSBR-based composites, which is an accurate and robust process.
Minimum Information Dominating Set for Opinion Sampling
Venue: arXiv cs.SI 2014
Year: 2014

We consider the problem of inferring the opinions of a social network through strategically sampling a minimum subset of nodes by exploiting correlations in node opinions. We first introduce the concept of information dominating set (IDS). A subset of nodes in a given network is an IDS if knowing the opinions of nodes in this subset is sufficient to infer the opinion of the entire network. We focus on two fundamental algorithmic problems: (i) given a subset of the network, how to determine whether it is an IDS; (ii) how to construct a minimum IDS. Assuming binary opinions and the local majority rule for opinion correlation, we show that the first problem is co-NP-complete and the second problem is NP-hard in general networks. We then focus on networks with special structures, in particular, acyclic networks. We show that in acyclic networks, both problems admit linear-complexity solutions by establishing a connection between the IDS problems and the vertex cover problem. Our technique for establishing the hardness of the IDS problems is based on a novel graph transformation that transforms the IDS problems in a general network to that in an odd-degree network. This graph transformation technique not only gives an approximation algorithm to the IDS problems, but also provides a useful tool for general studies related to the local majority rule. Besides opinion sampling for applications such as political polling and market survey, the concept of IDS and the results obtained in this paper also find applications in data compression and identifying critical nodes in information networks.
Hyper-Minimization for Deterministic Weighted Tree Automata
Venue: arXiv cs.FL 2014
Year: 2014

Hyper-minimization is a state reduction technique that allows a finite change in the semantics. The theory for hyper-minimization of deterministic weighted tree automata is provided. The presence of weights slightly complicates the situation in comparison to the unweighted case. In addition, the first hyper-minimization algorithm for deterministic weighted tree automata, weighted over commutative semifields, is provided together with some implementation remarks that enable an efficient implementation. In fact, the same run-time O(m log n) as in the unweighted case is obtained, where m is the size of the deterministic weighted tree automaton and n is its number of states.
Cover Story Management
Venue: arXiv cs.CR 2014
Year: 2014

In a multilevel database, cover stories are usually managed using the ambiguous technique of polyinstantiation. In this paper, we define a new technique to manage cover stories and propose a formal representation of a multilevel database containing cover stories. Our model aims to be a generic model, that is, it can be interpreted for any kind of database (e.g. relational, object- oriented etc). We then consider the problem of updating a multilevel database containing cover stories managed with our technique.
Bargaining-based Mobile Data Offloading
Venue: arXiv cs.GT 2014
Year: 2014

The unprecedented growth of mobile data traffic challenges the performance and economic viability of today's cellular networks, and calls for novel network architectures and communication solutions. Data offloading through third-party WiFi or femtocell access points (APs) can effectively alleviate the cellular network congestion in a low operational and capital expenditure. This solution requires the cooperation and agreement of mobile cellular network operators (MNOs) and AP owners (APOs). In this paper, we model and analyze the interaction among one MNO and multiple APOs (for the amount of MNO's offloading data and the respective APOs' compensations) by using the Nash bargaining theory. Specifically, we introduce a one-to-many bargaining game among the MNO and APOs, and analyze the bargaining solution (game equilibrium) systematically under two different bargaining protocols: (i) sequential bargaining, where the MNO bargains with APOs sequentially, with one APO at a time, in a given order, and (ii) concurrent bargaining, where the MNO bargains with all APOs concurrently. We quantify the benefits for APOs when bargaining sequentially and earlier with the MNO, and the losses for APOs when bargaining concurrently with the MNO. We further study the group bargaining scenario where multiple APOs form a group bargaining with the MNO jointly, and quantify the benefits for APOs when forming such a group. Interesting, our analysis indicates that grouping of APOs not only benefits the APOs in the group, but may also benefit some APOs not in the group. Our results shed light on the economic aspects and the possible outcomes of the MNO/APOs interactions, and can be used as a roadmap for designing policies for this promising data offloading solution.
HyperForce: Hypervisor-enForced Execution of Security-Critical Code
Venue: arXiv cs.SE 2014
Year: 2014

The sustained popularity of the cloud and cloud-related services accelerate the evolution of virtualization-enabling technologies. Modern off-the-shelf computers are already equipped with specialized hardware that enables a hypervisor to manage the simultaneous execution of multiple operating systems. Researchers have proposed security mechanisms that operate within such a hypervisor to protect the \textit{virtualized} operating systems from attacks. These mechanisms improve in security over previous techniques since the defense system is no longer part of an operating system's attack surface. However, due to constant transitions between the hypervisor and the operating systems, these countermeasures typically incur a significant performance overhead. In this paper we present HyperForce, a framework which allows the deployment of security-critical code in a way that significantly outperforms previous \textit{in-hypervisor} systems while maintaining similar guarantees with respect to security and integrity. HyperForce is a hybrid system which combines the performance of an \textit{in-guest} security mechanism with the security of in-hypervisor one. We evaluate our framework by using it to re-implement an invariance-based rootkit detection system and show the performance benefits of a HyperForce-utilizing countermeasure.
Hello rootKitty: A lightweight invariance-enforcing framework
Venue: arXiv cs.OS 2014
Year: 2014

In monolithic operating systems, the kernel is the piece of code that executes with the highest privileges and has control over all the software running on a host. A successful attack against an operating system's kernel means a total and complete compromise of the running system. These attacks usually end with the installation of a rootkit, a stealthy piece of software running with kernel privileges. When a rootkit is present, no guarantees can be made about the correctness, privacy or isolation of the operating system. In this paper we present \emph{Hello rootKitty}, an invariance-enforcing framework which takes advantage of current virtualization technology to protect a guest operating system against rootkits. \emph{Hello rootKitty} uses the idea of invariance to detect maliciously modified kernel data structures and restore them to their original legitimate values. Our prototype has negligible performance and memory overhead while effectively protecting commodity operating systems from modern rootkits.
Semi-supervised Spectral Clustering for Classification
Venue: arXiv cs.CV 2014
Year: 2014

We propose a Classification Via Clustering (CVC) algorithm which enables existing clustering methods to be efficiently employed in classification problems. In CVC, training and test data are co-clustered and class-cluster distributions are used to find the label of the test data. To determine an efficient number of clusters, a Semi-supervised Hierarchical Clustering (SHC) algorithm is proposed. Clusters are obtained by hierarchically applying two-way NCut by using signs of the Fiedler vector of the normalized graph Laplacian. To this end, a Direct Fiedler Vector Computation algorithm is proposed. The graph cut is based on the data structure and does not consider labels. Labels are used only to define the stopping criterion for graph cut. We propose clustering to be performed on the Grassmannian manifolds facilitating the formation of spectral ensembles. The proposed algorithm outperformed state-of-the-art image-set classification algorithms on five standard datasets.
Modeling, Analysis and Impact of a Long Transitory Phase in Random Access Protocols
Venue: arXiv cs.NI 2014
Year: 2014

In random access protocols, the service rate depends on the number of stations with a packet buffered for transmission. We demonstrate via numerical analysis that this state-dependent rate along with the consideration of Poisson traffic and infinite (or large enough to be considered infinite) buffer size may cause a high-throughput and extremely long (in the order of hours) transitory phase when traffic arrivals are right above the stability limit. We also perform an experimental evaluation to provide further insight into the characterisation of this transitory phase of the network by analysing statistical properties of its duration. The identification of the presence as well as the characterisation of this behaviour is crucial to avoid misprediction, which has a significant potential impact on network performance and optimisation. Furthermore, we discuss practical implications of this finding and propose a distributed and low-complexity mechanism to keep the network operating in the high-throughput phase.
Case study to approaches to finding patterns in citation networks
Venue: arXiv cs.DL 2014
Year: 2014

Analysis of a dataset including a network of LED patents and their metadata is carried out using several methods in order to answer questions about the domain. We are interested in finding the relationship between the metadata and the network structure; for example, are central patents in the network produced by larger or smaller companies? We begin by exploring the structure of the network without any metadata, applying known techniques in citation analysis and a simple clustering scheme. These techinques are then combined with metadata analysis to draw preliminary conclusions about the dataset.
Prediction of Foreign Box Office Revenues Based on Wikipedia Page Activity
Venue: arXiv cs.SI 2014
Year: 2014

A number of attempts have been made at estimating the amount of box office revenue a film will generate during its opening weekend. One such attempt makes extensive use of the number of views a film's Wikipedia page has attracted as a predictor of box office success in the United States. In this paper we develop a similar method of approximating box office success. We test our method using 325 films from the United States and then apply it to films from four foreign markets: Japan (95 films), Australia (118 films), Germany (105 films), and the United Kingdom (141 films). We find the technique to have inconsistent performance in these nations. While it makes relatively accurate predictions for the United States and Australia, its predictions in the remaining markets are not accurate enough to be useful.
Isometry on Interval-valued Fuzzy Graphs
Venue: arXiv cs.DM 2014
Year: 2014

Especially in research areas of computer science such as data mining, image segmentation, clustering image capturing and networking. The interval-valued fuzzy graphs are more flexible and compatible than fuzzy graphs due to the fact that they allowed the degree of membership of a vertex to an edge to be represented by interval valued in [0,1] rather than the crisp real values between 0 and 1.
On the effectiveness of virtualization-based security
Venue: arXiv cs.CR 2014
Year: 2014

Protecting commodity operating systems and applications against malware and targeted attacks has proven to be difficult. In recent years, virtualization has received attention from security researchers who utilize it to harden existing systems and provide strong security guarantees. This has lead to interesting use cases such as cloud computing where possibly sensitive data is processed on remote, third party systems. The migration and processing of data in remote servers, poses new technical and legal questions, such as which security measures should be taken to protect this data or how can it be proven that execution of code wasn't tampered with. In this paper we focus on technological aspects. We discuss the various possibilities of security within the virtualization layer and we use as a case study \HelloRootkitty{}, a lightweight invariance-enforcing framework which allows an operating system to recover from kernel-level attacks. In addition to \HelloRootkitty{}, we also explore the use of special hardware chips as a way of further protecting and guaranteeing the integrity of a virtualized system.
A comparison of three heuristics to choose the variable ordering for CAD
Venue: arXiv cs.SC 2014
Year: 2014

Cylindrical algebraic decomposition (CAD) is a key tool for problems in real algebraic geometry and beyond. When using CAD there is often a choice over the variable ordering to use, with some problems infeasible in one ordering but simple in another. Here we discuss a recent experiment comparing three heuristics for making this choice on thousands of examples.
Using the Regular Chains Library to build cylindrical algebraic decompositions by projecting and lifting
Venue: arXiv cs.SC 2014
Year: 2014

Cylindrical algebraic decomposition (CAD) is an important tool, both for quantifier elimination over the reals and a range of other applications. Traditionally, a CAD is built through a process of projection and lifting to move the problem within Euclidean spaces of changing dimension. Recently, an alternative approach which first decomposes complex space using triangular decomposition before refining to real space has been introduced and implemented within the RegularChains Library of Maple. We here describe a freely available package ProjectionCAD which utilises the routines within the RegularChains Library to build CADs by projection and lifting. We detail how the projection and lifting algorithms were modified to allow this, discuss the motivation and survey the functionality of the package.
An evolutionary computational based approach towards automatic image registration
Venue: arXiv cs.CV 2014
Year: 2014

Image registration is a key component of various image processing operations which involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however inability to properly model object shape as well as contextual information had limited the attainable accuracy. In this paper, we propose a framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as Vector Machines, Cellular Neural Network (CNN), SIFT, coreset, and Cellular Automata. CNN has found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using corset optimization The salient features of this work are cellular neural network approach based SIFT feature point optimisation, adaptive resampling and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. System has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. Methodology also illustrated to be effective in providing intelligent interpretation and adaptive resampling.
Real-Time Estimation of the Distribution of Brake Response Times for an Individual Driver Using Vehicular Ad Hoc Network
Venue: arXiv cs.OH 2014
Year: 2014

Adapting the functioning of the collision warning systems to the specific drivers' characteristics is of great benefit to drivers. For example, by customizing collision warning algorithms we can minimize false alarms, thereby reducing injuries and deaths in highway traffic accidents. In order to take the behaviors of individual drivers into account, the system needs to have a Real-Time estimation of the distribution of brake response times for an individual driver. In this paper, we propose a method for doing this estimation which is not computationally intensive and can take advantage of the information contained in all data points.
Generating Natural Language Descriptions from OWL Ontologies: the NaturalOWL System
Venue: arXiv cs.CL 2014
Year: 2014

We present NaturalOWL, a natural language generation system that produces texts describing individuals or classes of OWL ontologies. Unlike simpler OWL verbalizers, which typically express a single axiom at a time in controlled, often not entirely fluent natural language primarily for the benefit of domain experts, we aim to generate fluent and coherent multi-sentence texts for end-users. With a system like NaturalOWL, one can publish information in OWL on the Web, along with automatically produced corresponding texts in multiple languages, making the information accessible not only to computer programs and domain experts, but also end-users. We discuss the processing stages of NaturalOWL, the optional domain-dependent linguistic resources that the system can use at each stage, and why they are useful. We also present trials showing that when the domain-dependent llinguistic resources are available, NaturalOWL produces significantly better texts compared to a simpler verbalizer, and that the resources can be created with relatively light effort.
Human Face as human single identity
Venue: arXiv cs.CV 2014
Year: 2014

Human face as a physical human recognition can be used as a unique identity for computer to recognize human by transforming human face with face algorithm as simple text number which can be primary key for human. Human face as single identity for human will be done by making a huge and large world centre human face database, where the human face around the world will be recorded from time to time and from generation to generation. Architecture database will be divided become human face image database which will save human face images and human face output code which will save human face output code as a transformation human face image with face algorithm. As an improvement the slightly and simple human face output code database will make human face searching process become more fast. Transaction with human face as a transaction without card can make human no need their card for the transaction and office automation and banking system as an example for implementation architecture. As an addition suspect human face database can be extended for fighting crime and terrorism by doing surveillance and searching suspect human face around the world.
Performance Estimation of 2*3 MIMO-MC-CDMA in Rayleigh Fading Channel
Venue: arXiv cs.IT 2014
Year: 2014

In this paper we analyze the performance of 2by3 MIMOMCCDMA system in MATLAB which greatly reduces BER by increasing the efficiency of system. MIMO and MCCDMA system arrangement is used to decrease bit error rate and also figure a new system called MCCDMA which is multiple user and multiple access system used to enhance the performance of the system. MCCDMA is a narrowband flat fading in character which changes frequency selective to several narrowband flat fading multiple parallel subcarriers to enhance the effectiveness of the system. Now this MCCDMA further improved by grouping by 2by3 MIMO system which make use of ZF decoder at the receiver to reduce BER in which half rate convolutional encoded Alamouti STBC block code is intended for channel encoding as transmit diversity for MIMO with multiple transmit and receive antennas. Main improvement of using MIMOMCCDMA is for reducing complication of system and also for dropping BER and finally increasing gain of the system. Then we estimate the system in different modulation techniques like, 64QAM, 8PSK, 16QAM, QPSK, 32QAM and 8QAM using MATLAB in Rayleigh fading channel.
Automated Fabric Defect Inspection: A Survey of Classifiers
Venue: arXiv cs.CV 2014
Year: 2014

Quality control at each stage of production in textile industry has become a key factor to retaining the existence in the highly competitive global market. Problems of manual fabric defect inspection are lack of accuracy and high time consumption, where early and accurate fabric defect detection is a significant phase of quality control. Computer vision based, i.e. automated fabric defect inspection systems are thought by many researchers of different countries to be very useful to resolve these problems. There are two major challenges to be resolved to attain a successful automated fabric defect inspection system. They are defect detection and defect classification. In this work, we discuss different techniques used for automated fabric defect classification, then show a survey of classifiers used in automated fabric defect inspection systems, and finally, compare these classifiers by using performance metrics. This work is expected to be very useful for the researchers in the area of automated fabric defect inspection to understand and evaluate the many potential options in this field.