What are the trend and core knowledge of information security? A citation and co-citation analysis

Information technology brings business success opportunities, but also causes potential safety hazards to organizations. In response to the increasing academia and industry concerns regarding information security (ISec), this study systematically explored extant ISec research and identified eight core knowledge groups, including (1) intrusion detection, (2) privacy protection, (3) secure machine learning, (4) cryptosystem, (5) data service security, (6) malware analysis, (7) security decision-making, and (8) security management. The detection of research hotspots shows that data service security and risk management garner the most current research attention. Furthermore, we establish a comprehensive ISec framework to help systematically understand and achieve ISec.     

Stochastic modeling and analysis of road–tramway intersections

In the last decades, the socio-demographic evolution of the population has substantially changed mobility demand, posing new challenges in minimizing urban congestion and reducing environmental impact. In this scenario, understanding how different modes of transport can efficiently share (partially or totally) a common infrastructure is crucial for urban development. To this aim, we present a stochastic model-based analysis of critical intersections shared by tram traffic and private traffic, combining a microscopic model of the former with a macroscopic model of the latter. Advanced simulation tools are typically used for such kind of analyses, by playing various traffic scenarios. However, simulation is not an exhaustive approach, and some critical, possibly rare, event may be ignored. For this reason, our aim is instead to adopt suitable analytical solution techniques and tools that can support instead a complete, exhaustive analysis, so being able to take into account rare events as well. Transient analysis of the overall traffic model using the method of stochastic state classes is adopted to support the evaluation of relevant performance measures, namely the probability of traffic congestion over time and the average number of private vehicles in the queue over time. A sensitivity analysis is performed with respect to multiple parameters, notably including the arrival rate of private vehicles, the frequency of tram rides, and the time needed to recover from traffic congestion.

     

Modelling and analysis of a rigid–compliant parallel mechanism

This paper presents a two-staged parallel mechanism composed by a rigid platform in a serial connection with a compliant platform, and concentrates on its configuration and interrelation. The analysis starts with the operator of a 3UPU configuration with a central strut being derived. Configuration and displacement formulas of the compliant platform are demonstrated, leading to the analytic equations of the relationship between the actuated angles of the operator and the position parameters of the end-effector. The numerical evaluation of workspace of the two-staged parallel mechanism is then followed.     

Expert system applications in business: A review and analysis of the literature (1977–1993)

A survey of expert system (ES) business application papers published between 1977 and 1993 indicates that an increasing amount of ES research is being conducted for a diverse range of business activities. The classification of literature by (1) year of publication, (2) application area, (3) generic problem area addressed, (4) problem domain, (5) level of management, (6) level of task interdependence, (7) means of development, (8) corporate/academic interaction in development, and (9) technology integration provides some insights in the trend. Implications to ES developers are discussed.     

Classification of primitive shapes using brain–computer interfaces

Brain–computer interfaces (BCIs) are recent developments in alternative technologies of user interaction. The purpose of this paper is to explore the potential of BCIs as user interfaces for CAD systems. The paper describes experiments and algorithms that use the BCI to distinguish between primitive shapes that are imagined by a user. Users wear an electroencephalogram (EEG) headset and imagine the shape of a cube, sphere, cylinder, pyramid or a cone. The EEG headset collects brain activity from 14 locations on the scalp. The data is analyzed with independent component analysis (ICA) and the Hilbert–Huang Transform (HHT). The features of interest are the marginal spectra of different frequency bands (theta, alpha, beta and gamma bands) calculated from the Hilbert spectrum of each independent component. The Mann–Whitney U-test is then applied to rank the EEG electrode channels by relevance in five pair-wise classifications. The features from the highest ranking independent components form the final feature vector which is then used to train a linear discriminant classifier. Results show that this classifier can discriminate between the five basic primitive objects with an average accuracy of about 44.6% (compared to naïve classification rate of 20%) over ten subjects (accuracy range of 36%–54%). The accuracy classification changes to 39.9% when both visual and verbal cues are used. The repeatability of the feature extraction and classification was checked by conducting the experiment on 10 different days with the same participants. This shows that the BCI holds promise in creating geometric shapes in CAD systems and could be used as a novel means of user interaction.     

Closed-loop analysis and control of a non-inverting buck–boost converter

In this article, a cascade controller is designed and analysed for a non-inverting buck–boost converter. The fast inner current loop uses sliding mode control. The slow outer voltage loop uses the proportional–integral (PI) control. Stability analysis and selection of PI gains are based on the nonlinear closed-loop error dynamics incorporating both the inner and outer loop controllers. The closed-loop system is proven to have a nonminimum phase structure. The voltage transient due to step changes of input voltage or resistance is predictable. The operating range of the reference voltage is discussed. The controller is validated by a simulation circuit. The simulation results show that the reference output voltage is well-tracked under system uncertainties or disturbances, confirming the validity of the proposed controller.     

Classification of finite-dimensional estimation algebras of maximal rank with arbitrary state–space dimension and mitter conjecture

In the late seventies, the concept of the estimation algebra of a filtering system was introduced. It was proven to be an invaluable tool in the study of non-linear filtering problems. In the early eighties, Brockett proposed to classify finite dimensional estimation algebras and Mitter conjectured that all functions in finite dimensional estimation algebras are necessarily polynomials of total degree at most one. Despite the massive effort in understanding the finite dimensional estimation algebras, the 20 year old problem of Brockett and Mitter conjecture remains open. In this paper, we give a classification of finite dimensional estimation algebras of maximal rank and solve the Mitter conjecture affirmatively for finite dimensional estimation algebras of maximal rank. In particular, for an estimation algebra E of maximal rank, we give a necessary and sufficient conditions for E to be finite dimensional in terms of the drift f_i (x) and observation h_j (x). As an important corollary, we show that the number of statistics needed to compute the conditional density of the state given the observation {y(s):0?≤?s?≤?t} by the algebraic method is n where n is the dimension of the state.     

Lie symmetry analysis and conservation law of variable-coefficient Davey–Stewartson equation

A variable-coefficient Davey–Stewartson (vcDS) equation is investigated in this paper. Infinitesimal generators and symmetry groups are presented by the Lie group method, and the optimal system is presented with adjoint representation. Based on the optimal system, similarity reductions to partial differential equations (PDEs) are obtained, then some PDEs are reduced to ordinary differential equations (ODEs) by two-dimensional subalgebras, and the similarity solutions are provided, including periodic solutions and elliptic function solutions. With Lagrangian, it is shown that vcDS is nonlinearly self-adjoint. Furthermore, based on nonlinear self-adjointness, conservation laws for vcDS equation are derived.     

Identification and spatio-temporal analysis of earthquake clusters using SOM–DBSCAN model

Neural Computing and Applications - Seismic catalogs are vital to understanding and analyzing the progress of active fault systems. The background seismicity rate in a seismic catalog, strongly...     

The Depletion–Power–Integration–Latency (DPIL) model of spaced and massed repetition

Although several models have been suggested in the literature to describe the relationship between learning and forgetting, this relationship is still not fully understood. This paper proposes the Depletion–Power–Integration–Latency (DPIL) model, which assumes that performing a task repetitively depletes the available encoding resources for that task. The DPIL model fitted five empirical datasets well, reflecting different procedural/episodic learning settings, experimental paradigms (massed/spaced repetition, study time), tests (accuracy, latency), and retention intervals. The model was also fitted to empirical data collected from a quality inspection station at an industrial firm. The DPIL model has the advantage of predicting the length of the final break (interruption) that optimizes performance. This finding is important as it has many industrial engineering applications. The numerical results in this paper show that performance improves as the length of each break preceding the final break increases. This is consistent with empirical findings that moderately short breaks are optimal for performance.     

Classification of radar echoes with a textural–fuzzy approach: an application for the removal of ground clutter observed in Sétif (Algeria) and Bordeaux (France) sites

This work deals with the classification of radar echoes and the removal of clutter caused by the Earth’s surface. Two incoherent radar sites are considered, which are the regions of Sétif (Algeria) and Bordeaux (France) where different climates and landforms prevail. To perform this task, we used a combination of textural and fuzzy approaches. For the textural technique, we applied grey-level co-occurrence matrices that are widely used in the analysis of texture images. We have shown that among nine parameters, only energy and local homogeneity are considered to be effective in discriminating between precipitation echoes and clutter. Then, these parameters are used as inputs for the fuzzy system, while the two radar echo types are its output classes. Image processing done by using this approach has reduced ground echoes by more than 93.5% for Sétif and 92.3% for Bordeaux sites, while more than 97.6% of precipitation echoes are stored at both sites. In addition, over 96% of the anomalous propagations observed only in Bordeaux site are removed. The proposed approach gives a filtering average rate that is 94.5% higher than that obtained for the textural technique alone, which is 91.5%.     

Image indexing and content analysis in children’s picture books using a large-scale database

In this paper we introduce a visual database for children’s picture book and we also present an intelligent robot trained on this database. Firstly, a large-scale image dataset is built that contains image samples of book pages. It can be used to verify image indexing algorithms and content recognition algorithms. Secondly, we study the state-of-the-art algorithms in image matching and object recognition. Several approaches are presented and compared from the aspects of computational efficiency and recognition accuracy. In order to improve the speed we proposed a novel hierarchical algorithm for fast search. Finally, using this large-scale database we are able to build a robot that can read children’s picture books and initial experimental results are presented. We can see that both the training database and the algorithms are promising, yet there are still a few open challenges concerning the costs and robustness.

     

5–6–7 Meshes: Remeshing and analysis

We introduce a new type of meshes called 5–6–7 meshes. For many mesh processing tasks, low- or high-valence vertices are undesirable. At the same time, it is not always possible to achieve complete vertex valence regularity, i.e. to only have valence-6 vertices. A 5–6–7 mesh is a closed triangle mesh where each vertex has valence 5, 6, or 7. An intriguing question is whether it is always possible to convert an arbitrary mesh into a 5–6–7 mesh. In this paper, we answer the question in the positive. We present a 5–6–7 remeshing algorithm which converts a closed triangle mesh with arbitrary genus into a 5–6–7 mesh which (a) closely approximates the original mesh geometrically, e.g. in terms of feature preservation and (b) has a comparable vertex count as the original mesh. We demonstrate the results of our remeshing algorithm on meshes with sharp features and different topology and complexity.     

Dissipative stability analysis and control of two-dimensional Fornasini–Marchesini local state-space model

This paper is concerned with the problems of dissipative stability analysis and control of the two-dimensional (2-D) Fornasini–Marchesini local state-space (FM LSS) model. Based on the characteristics of the system model, a novel definition of 2-D FM LSS (Q, S, R)-α-dissipativity is given first, and then a sufficient condition in terms of linear matrix inequality (LMI) is proposed to guarantee the asymptotical stability and 2-D (Q, S, R)-α-dissipativity of the systems. As its special cases, 2-D passivity performance and 2-D H_∞ performance are also discussed. Furthermore, by use of this dissipative stability condition and projection lemma technique, 2-D (Q, S, R)-α-dissipative state-feedback control problem is solved as well. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.     

Overall availability and risk analysis of a general robot–safety device system

We analyse the availability of a general robot–safety device system characterised by the feature of cold standby and by an admissible risky state. In contrast to the previous literature, we allow a general failure-free time distribution for the robot and, as an example, we present computational results for Coxian failure and repair time distributions. In order to decide whether the risky state is admissible, we introduce a risk criterion based on the notion of rare events. The criterion is always satisfied in the case of fast repair.     

Knowledge Based Pipeline Network Classification and Recognition Method of Maps

Map recognition is an essential data input means of Geographic Information System (GIS). How to solve the problems in the procedure, such as recognition of maps with crisscross pipeline networks, classification of buildings and roads, and processing of connected text, is a critical step for GIS keeping high-speed development. In this paper, a new recognition method of pipeline maps is presented, and some common patterns of pipeline connection and component labels are established. Through pattern matching, pipelines and component labels are recognized and peeled off from maps. After this approach, maps simply consist of buildings and roads, which are recognized and classified with fuzzy classification method. In addition, the Double Sides Scan (DSS) technique is also described, through which the effect of connected text can be eliminated.     

A Hierarchical Classification and Iterative Model based Methodfor Remote Sensing Classification of Land Cover

Land cover classification based on remote sensing is an important means to analyze the change and spatial pattern of land use.In order to further improve the classification accuracy,this paper proposed a hierarchical classification and iterative CART model based method for remote sensing classification of landcover.Firstly,the extraction order of land cover classes was determined based on the class separability evaluation,which was water,vegetation,bare soil and built-up land.Secondly,we selected the optimal image segmentation parameters and a set of sensitive features for each class during the hierarchical classification process.Finally,object-based training samples were selected to be fed into the iterative CART algorithm for the successive extraction of the first three classes,with the remaining unclassified objects being directly assigned to the last class.Results demonstrated that the proposed method can significantly reduce the mixture between bare soil and built-up land,and is capable of achieving landcover classification with much higher accuracy.The proposed method achieved an overall accuracy of 85.76% and a Kappa efficient of 0.72,with the performance improvements ranging from 10.67% to 16.5% and 0.15 to 0.21 as compared SVM and CART single classification methods.The classification accuracy of a specific class can be flexibly adjusted using this method,giving different purposes of classification.This method can also be easily extended to other districts and disciplines involving remote sensing image classification.     

Sensitivity analysis and optimization of vehicle–bridge systems based on combined PEM–PIM strategy

This paper presents a new optimization method for coupled vehicle–bridge systems subjected to uneven road surface excitation. The vehicle system is simplified as a multiple rigid-body model and the single-span bridge is modeled as a simply supported Bernoulli–Euler beam. The pseudo-excitation method transforms the random surface roughness into the superposition of a series of deterministic pseudo-harmonic excitations, which enables convenient and accurate computation of first and second order sensitivity information. The precise integration method is used to compute the vertical random vibrations for both the vehicle and the bridge. The sensitivities are used to find the optimal solution, with vehicle ride comfort taken as the objective function. Optimization efficiency and computational accuracy are demonstrated numerically.