Predicting phishing websites based on self-structuring neural network

Internet has become an essential component of our everyday social and financial activities. Nevertheless, internet users may be vulnerable to different types of web threats, which may cause financial damages, identity theft, loss of private information, brand reputation damage and loss of customer’s confidence in e-commerce and online banking. Phishing is considered as a form of web threats that is defined as the art of impersonating a website of an honest enterprise aiming to obtain confidential information such as usernames, passwords and social security number. So far, there is no single solution that can capture every phishing attack. In this article, we proposed an intelligent model for predicting phishing attacks based on artificial neural network particularly self-structuring neural networks. Phishing is a continuous problem where features significant in determining the type of web pages are constantly changing. Thus, we need to constantly improve the network structure in order to cope with these changes. Our model solves this problem by automating the process of structuring the network and shows high acceptance for noisy data, fault tolerance and high prediction accuracy. Several experiments were conducted in our research, and the number of epochs differs in each experiment. From the results, we find that all produced structures have high generalization ability.     

Merge of motion analysis,multibody dynamics and finite element method for the subject-specific analysis of cartilage loading patterns during gait: differences between rotation and moment-driven models of human knee joint

Understanding joint loading is important when evaluating sports training methods, sports equipment design, preventive training regimens, post-op recovery procedures, or in osteoarthritis’ etiology research. A number of methods have been introduced to estimate joint loads but they have been limited by the lack of accuracy in the joint models, including primarily the lack of patient-specific motion inputs in the models with sophisticated, fibril-reinforced material models. The method reported here records and applies patient-specific human motion for in-depth cartilage stress estimation. First, the motion analysis of a subject was conducted. Due to skin motion, multibody simulation was used to correct motion capture. These data was used as an input in a finite element model. The model geometry was based on magnetic resonance imaging and cartilage was modeled as a fibril-reinforced poroviscoelastic material. Based on the experimental motion data (motion analysis and multibody simulation), two models were created: a rotation-controlled and a moment-controlled model. For comparison, a model with motion input from the literature was created. The rotation-controlled model showed the most even stress distribution between lateral and medial compartments and smallest stresses and strains in a depth-wise manner. The model based on the literature motion simulated very high stresses and uneven stress distribution between the joint compartments. Our new approach to determine dynamic knee cartilage loading enables estimations of stresses and strains for a specific subject over the entire motion cycle.     

A computationally efficient tracker with direct appearance-kinematic measure and adaptive Kalman filter

Visual tracking is considered a common procedure in many real-time applications. Such systems are required to track objects under changes in illumination, dynamic viewing angle, image noise and occlusions (to name a few). But to maintain real-time performance despite these challenging conditions, tracking methods should require extremely low computational resources, therefore facing a trade-off between robustness and speed. Emergence of new consumer-level cameras capable of capturing video in 60 fps challenges this tradeoff even further. Unfortunately, state-of-the-art tracking techniques struggle to meet frame rates over 30 VGA-resolution fps with standard desktop power, let alone on typically-weaker mobile devices. In this paper we suggest a significantly cheaper computational method for tracking in colour video clips, that greatly improves tracking performance, in terms of robustness/speed trade-off. The suggested approach employs a novel similarity measure that explicitly combines appearance with object kinematics and a new adaptive Kalman filter extends the basic tracking to provide robustness to occlusions and noise. The linear time complexity of this method is reflected in computational efficiency and high processing rate. Comparisons with two recent trackers show superior tracking robustness at more than 5 times faster operation, all using naïve C/C++ implementation and built-in OpenCV functions.     

Multiple source imagery and linear features for detection of urban expansion in Aqaba City,Jordan

Aqaba is one of the most strategic cities in Jordan and the entire region, as it is the only seaport for Jordan and has a special economic zone as the only window to global markets. The main purpose of this study is to detect urban development in Aqaba region by detecting and registering linear features in images with various geometric and radiometric properties taken at different times. This article used linear features for image registration that were chosen since they can be reliably extracted from imagery with significantly different geometric and radiometric properties. The modified iterated Hough transform (MIHT) is used as the matching strategy for automatically deriving an estimate of the parameters involved in the transformation function relating the images to be registered as well as the correspondence between conjugate lines. Derived edges from the registered images are used as the basis for change detection. The utilization of edges is motivated by the fact that they are invariant with respect to possible radiometric differences between the images in question. Linear features extraction, feature matching, image registration and pixel–pixel subtraction have been implemented using SPOT, Landsat, Ikonos and aerial photographs that have different radiometric, spatial and temporal resolutions. It has been shown that linear features (straight-line segments) have high semantics and can be reliably extracted from the images. These linear features can be used for accurate co-registration as an essential prerequisite for a reliable change detection procedure. For the purpose of change detection, image–image registration is more crucial than image–ground registration, where corresponding features in images are registered with respect to each other regardless of the associated absolute errors. The results illustrate that using edges as the base for change detection in urban areas is efficient and reliable.     

Solvability of static output-feedback stabilization for LTI positive systems

This paper addresses the stabilization problem of positive linear systems which have nonnegative states whenever the initial conditions are nonnegative. The synthesis of static output-feedback controllers that ensure the positivity and asymptotic stability of the closed-loop system is investigated. It is shown that this important problem is completely solved for single-input and single-output positive systems. The proposed approach can be applied to multi-input positive systems with controllers having one rank gains. All the provided conditions are necessary and sufficient and can be solved in terms of Linear Programming.     

A two-stage Ant Colony Optimization algorithm to minimize the makespan on unrelated parallel machines with sequence-dependent setup times

This paper addresses the non-preemptive unrelated parallel machine scheduling problem with machine-dependent and sequence-dependent setup times. All jobs are available at time zero, all times are deterministic, and the objective is to minimize the makespan. An Ant Colony Optimization (ACO) algorithm is introduced in this paper and is applied to this NP-hard problem; in particular, the proposed ACO tackles a special structure of the problem, where the ratio of the number of jobs to the number of machines is large (i.e., for a highly utilized set of machines). Its performance is evaluated by comparing its solutions to solutions obtained using Tabu Search and other existing heuristics for the same problem, namely the Partitioning Heuristic and Meta-RaPS. The results show that ACO outperformed the other algorithms.     

Personalised Information Retrieval: survey and classification

Information Retrieval (IR) systems assist users in finding information from the myriad of information resources available on the Web. A traditional characteristic of IR systems is that if different users submit the same query, the system would yield the same list of results, regardless of the user. Personalised Information Retrieval (PIR) systems take a step further to better satisfy the user’s specific information needs by providing search results that are not only of relevance to the query but are also of particular relevance to the user who submitted the query. PIR has thereby attracted increasing research and commercial attention as information portals aim at achieving user loyalty by improving their performance in terms of effectiveness and user satisfaction. In order to provide a personalised service, a PIR system maintains information about the users and the history of their interactions with the system. This information is then used to adapt the users’ queries or the results so that information that is more relevant to the users is retrieved and presented. This survey paper features a critical review of PIR systems, with a focus on personalised search. The survey provides an insight into the stages involved in building and evaluating PIR systems, namely: information gathering, information representation, personalisation execution, and system evaluation. Moreover, the survey provides an analysis of PIR systems with respect to the scope of personalisation addressed. The survey proposes a classification of PIR systems into three scopes: individualised systems, community-based systems, and aggregate-level systems. Based on the conducted survey, the paper concludes by highlighting challenges and future research directions in the field of PIR.     

An efficient algorithm for constructing delay bounded minimum cost multicast trees

Multimedia applications are usually resource intensive, have stringent quality of service requirements, and in many cases involve large groups of participants. Multicasting is poised to play an important role in future deployment of these applications. This paper focuses on developing delay-bounded, minimum-cost multicast trees, linking a source to a set of multicast destination nodes. The approach taken in this paper is efficient, flexible and unique in the sense that it cleverly limits its computation only to paths that originate at multicast nodes, thereby avoiding computing paths that exclusively link non-multicast nodes. The simulation results show that the multicast trees produced by the proposed heuristic are of lower cost than those produced by other well-known heuristics, including those which use an expensive k-shortest-paths procedure to minimize the cost of the multicast tree. Furthermore, the results show that, in comparison to other heuristics, the proposed scheme results in a significant reduction in the computation time required to build the multicast tree.     

Two‐dimensional finite element method solution of a class of integro‐differential equations: Application to non‐Fickian transport in disordered media

A finite element method is developed to solve a class of integro‐differential equations and demonstrated for the important specific problem of non‐Fickian contaminant transport in disordered porous media. This transient transport equation, derived from a continuous time random walk approach, includes a memory function. An integral element is the incorporation of the well‐known sum‐of‐exponential approximation of the kernel function, which allows a simple recurrence relation rather than storage of the entire history. A two‐dimensional linear element is implemented, including a streamline upwind Petrov–Galerkin weighting scheme. The developed solver is compared with an analytical solution in the Laplace domain, transformed numerically to the time domain, followed by a concise convergence assessment. The analysis shows the power and potential of the method developed here. Copyright © 2017 John Wiley & Sons, Ltd.     

Sequential circuit design for networks of threshold functions in nanotechnology

Microsystem Technologies - While a general strategy for designing combinational circuits exists, little work has been done on sequential circuits using nanotechnology. This is due to the logic used...