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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jss.2008.10.012 Byline: Ebrahim Bagheri, Ali A. Ghorbani Keywords: Collaborative modeling; Viewpoint integration; Conceptualization; Inconsistency management; Belief theory Abstract: Merging and integrating different conceptual models which have been collaboratively developed by domain experts and analysts with dissimilar perspectives on the same issue has been the subject of tremendous amount of research. In this paper, we focus on the fact that human analysts' opinions possess a degree of uncertainty which can be exploited while integrating such information. We propose an underlying modeling construct which is the basis for transforming conceptual models into a manipulatable format. Based on this construct, methods for formally negotiating over and merging of conceptual models are proposed. The approach presented in this paper focuses on the formalization of uncertainty and expert reliability through the employment of belief theory. The proposed work has been evaluated for its effectiveness and usability. The evaluators (a group of Computer Science graduate students) believed that the proposed framework has the capability to fulfil its intended tasks. The obtained results from the performance perspective are also promising. Author Affiliation: Faculty of Computer Science, University of New Brunswick, 540 Windsor Street, Fredericton, NB, Canada Article History: Received 13 August 2007; Revised 2 October 2008; Accepted 7 October 2008

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jss.2007.08.033 Byline: S. Hossein Sadat-Mohtasham, Ali A. Ghorbani Keywords: Adaptive web system; Domain-specific programming language; Aspect-oriented programming Abstract: Adaptive Web systems (AWS) are Web-based systems that can adapt their features such as, presentation, content, and structure, based on users' behaviour and preferences, device capabilities, and environment attributes. A framework was developed in our research group to provide the necessary components and protocols for the development of adaptive Web systems; however, there were several issues and shortcomings (e.g. low productivity, lack of verification mechanisms, etc.) in using the framework that inspired the development of a domain-specific language for the framework. This paper focuses on the proposal, design, and implementation of AWL, the Adaptive Web Language, which is used to develop adaptive Web systems within our framework. Not only does AWL address the existing issues in the framework, but it also offers mechanisms to increase software quality attributes, especially, reusability. An example application named PENS (a personalized e-News system) is explained and implemented in AWL. AWL has been designed based on the analysis of the adaptive Web domain, having taken into account the principles of reuse-based software engineering (product-lines), domain-specific languages, and aspect-oriented programming. Specially, a novel design decision, inspired by aspect-oriented programming paradigm, allows separate specification of presentation features in an application from its adaptation features. The AWL's design decisions and their benefits are explained. Author Affiliation: Intelligent and Adaptive Systems Group, Faculty of Computer Science, University of New Brunswick, Fredericton, NB, Canada E3B 5A3 Article History: Received 20 July 2006; Revised 23 August 2007; Accepted 24 August 2007

Cutting edge Deep Learning (DL) techniques have been widely applied to areas like image processing and speech recognition so far. Likewise, some DL work has been done in the area of cybersecurity. In this survey, we focus on recent DL approaches that have been proposed in the area of cybersecurity, namely intrusion detection, malware detection, phishing/spam detection, and website defacement detection. First, preliminary definitions of popular DL models and algorithms are described. Then, a general DL framework for cybersecurity applications is proposed and explained based on the four major modules it consists of. Afterward, related papers are summarized and analyzed with regard to the focus area, methodology, model applicability, and feature granularity. Finally, concluding remarks and future work are discussed including the possible research topics that can be taken into consideration to enhance various cybersecurity applications using DL models. [ABSTRACT FROM AUTHOR]

Highlights • A more realistic framework for calculation of GRC in medium rock mass is presented. • Proposed solution for elastoplastic-EDZ rock is validated using field measurements. • Using Unified criterion, effects of intermediate principle stress are evaluated. • Material softening and the exponential decay of dilation are, also, considered. • Weight of the damaged zone and Young's modulus' variation in EDZ are investigated. Abstract Although the determination of ground reaction curve (GRC) for tunnels has been extensively studied, formation of a damaged zone around the tunnel along with effects of some new features, including intermediate principle stress, exponential decaying dilation parameter, weight of the damaged rock and Young's modulus variation in the excavation damaged zone (EDZ) on the GRC development have not yet been considered. In this paper, considering all the affecting parameters including the previously studied ones and the new features, a comprehensive solution for the calculation of GRC of circular tunnels is presented. First, defining a more realistic medium for medium quality rock mass, behavior of tunnel's surrounding rock mass is categorized into elastic, plastic and excavation damaged zones, where materials in the plastic zone experience a strain softening. Also, rock mass through this strain softening, elastic-plastic-EDZ medium obeys Unified strength criterion (USC). Next, regarding the new defined medium, radial stress at the plastic-EDZ boundary is numerically calculated. Defining separate normalized radiuses for the plastic and damaged zones, thickness of annuluses, also, stress and strain increments are derived for different regions through finite difference solution of governing equilibrium and compatibility equations. The results of the proposed algorithm are verified using the field measurement data of Hanlingjie tunnel, China and its high accuracy is shown. Also, omitting the new features of the proposed algorithm, its comprehensiveness is discussed through comparison with some available solutions in the literature and a very good consistency is obtained. On the other hand, considering new features of the proposed algorithm, a considerable discrepancy is achieved indicating the importance of consideration of these features in the ground reaction curve development. [ABSTRACT FROM AUTHOR]

In this study, a coupled numerical modeling and soft computing was carried out to investigate the seismic response and liquefaction resistance of two common types of foundations used for offshore wind turbines (OWT), namely the Monopile and Suction Bucket Foundations under combined loading of wave, wind and earthquake. A series of fully coupled non-linear dynamic analysis was performed using FLAC-3D to produce the database required in the soft computing procedure by evaluating the effect of different factors such as foundation's geometrical properties (foundation's type and its aspect ratio), soil properties (relative density and depth of liquefiable layer) and the input ground motion parameters (frequency and amplitude). Parameters of SANISAND constitutive model were calibrated using centrifuge studies performed on OWTs. Afterwards, genetic algorithm (GA) was used to develop prediction models for prediction the seismic response parameters, especially the maximum value of tower's rotation, which was verified against the results of centrifuge experiments. • Preforming a comprehensive parametric study on the seismic response of OWT foundations in liquefiable soil. • Performing a series of advanced fully coupled non-linear dynamic analysis using FLAC-3D. • Calibration of SANISAND parameters using centrifuge experiments. • Comparison of the obtained results, by elaborating the mechanisms behind the observed behavior. • Using genetic algorithm to develop prediction models for the seismic response parameters, verified by centrifuge experiments. [ABSTRACT FROM AUTHOR]

Abstract: A comprehensive dynamic three dimensional finite element model, which includes the effect of lots of important parameters on the micropiles seismic performance, has been presented. The validation of the built model has been carried out using remodeling a single degree of freedom shaking table test done by Mc Manus at the University of Canterbury. The gained results proved the accuracy of the constructed model. Then, using the parametric analysis, effects of all the earthquake characteristics, soil properties, superstructure and micropiles' cap and micropiles structure on the seismic performance of micropiles have been investigated by means of presenting internal forces and displacements which occurred as the main result of earthquake. Furthermore, using the data analysis, the most and the least influential parameters on internal forces are obtained based on the Cosine Amplitude Method (CAM). [Copyright &y& Elsevier]

Abstract: Geophysical and geotechnical field investigations have introduced several techniques to measure in-situ shear wave velocity of soils. However, there are some difficulties for the easy and economical use of these techniques in the routine geotechnical engineering works. For the soil deposits, researchers have developed correlations between shear wave velocity and SPT-N values. In the present study, a new database containing the measured shear wave velocity of soil deposits have been compiled from the previously published studies. Using polynomial neural network (PNN), a new correlation has been subsequently developed for the prediction of shear wave velocity. The developed relationship shows an acceptable performance compared with the available relationships. Three examples are then presented to confirm accuracy and applicability of the proposed equation in the field of liquefaction potential assessment. [Copyright &y& Elsevier]

Summary: Background: Prosthetic joint infection (PJI) can present a diagnostic challenge, especially with slow-growing and poorly virulent bacteria. Objective: To describe the epidemiological, clinical and biological characteristics of Propionibacterium acnes PJI, their treatments and outcomes and compare 2 clinical pictures (according to the time PJI symptoms appeared after the index operation: ≤2 years, >2 years). Methods: We conducted a cohort study on P. acnes PJI. Diagnosis was based on ≥2 positive cultures of intraoperative specimens taken during revision arthroplasties for infection or presumed aseptic loosening. Results: Fifty patients with prosthetic hip (34), knee (10) or shoulder (6) infections were included and analyzed according to their symptom-free interval: ≤2 years for 35 and >2 years for 15 (mean interval: 11±6 years). The numbers of previous prostheses (p =0.04) were higher for the shorter-interval group, which had more frequent signs of infection (p =0.004). These findings suggest infection in most of the patients whose PJI symptoms appeared: ≤2 years after the index operation, and colonization in the majority of those whose symptoms appeared >2 years after index surgery. Treatment combining exchange arthroplasty with prolonged intravenous antibiotics was successful for 92% of the patients. Conclusion: P. acnes can cause different types of PJI: late chronic infections, colonization of loosened prostheses and, exceptionally, acute postoperative infections. [Copyright &y& Elsevier]

This study presents a comprehensive, energy-based model for the evaluation of the liquefaction potential of all types of sandy soils, including clean, silty, and clayey sands. Unlike previous energy-based capacity models, this study considers the effect of Plasticity Index (PI) and loading Frequency (Frq) in the proposed model. Introducing an innovative method, the model was developed in two steps. At first, a small-scale model was developed using Evolutionary Polynomial Regression method (EPR), considering PI, Frq, Fine Content (FC), mean grain size (D 50), and uniformity coefficient (C u). For this aim, 63 laminar shaking table tests were performed on different fine-grained soils mixed with sand, with a wide range of PI (from 0 to 26) to provide a comprehensive data bank for EPR modeling. Then, by introducing an appropriate scaling factor, the model was scaled up to the field condition considering effective stress (σ v ′) and relative density (D r). The model was successfully verified using a number of 100 case-histories worldwide with various soil properties. The results showed that the present model is considerably superior to previous energy-based models. Parametric analysis demonstrated that the liquefaction capacity energy of sandy soils with high fine content is mainly influenced by FC and PI, respectively. [ABSTRACT FROM AUTHOR]

Digital forensic investigators' aim is identifying, collecting and presenting reliable, accurate, and admissible evidence in court. However, anti-forensics manipulate, obfuscate, hide, and remove the remaining piece of evidence in a compromised system. Anti-forensics interrupt investigation procedures; thus, the investigators require specific defensive strategies (counter-anti-forensics) against anti-forensics. This paper mounts a survey to explore existing anti-forensic research, and constitute a taxonomy on behaviour of anti-forensics and another taxonomy on further research tasks of anti-forensics. The knowledge of interactions between forensic agents' (an investigator and an attacker) in a forensic environment helps the investigator to evaluate the existing counter-anti-forensics, and enables him/her to design and develop more advanced counter-anti-forensics. Therefore, in this paper, first, we formulate a set of characteristics to model interactions between the attacker and the investigator (players) in a realistic forensic environment. Next, we propose a game-theoretic approach to model the players' interactions. The attacker uses anti-forensics (i.e. rootkits) and the investigator employs counter-anti-forensics (i.e. anti-rootkits). We select and evaluate a set of game-theoretic models and algorithms to simulate the players' interactions. Results of the evaluation show that a gradient play algorithm has satisfactory performance, among the selected game-theoretic models and algorithms to simulate the interactions in the forensic environment. The gradient play algorithm identifies the investigator's most stable and desired strategies after spending 10.0E-4 s and consuming 5.8 KB. • A taxonomy on various behaviors of anti-forensics is provided. • A taxonomy on future research tasks in anti-forensics is presented. • Interactions in a forensic environment can be modelled by some characteristics. • The evaluation of game-theoretic algorithms in a forensic environment is achievable. [ABSTRACT FROM AUTHOR]

Forensic science aims to present evidence in the courtroom, in a forensically sound manner. Therefore, forensic procedures must guarantee the provability, admissibility, accuracy, and authenticity of the case's evidence. However, anti-forensics threaten forensic procedures by forging, hiding, and even modifying remaining evidence in a crime scene. For instance, rootkits hide traces of attacks in a compromised system. To prevent anti-forensics, forensic investigators use de-anti-forensic methods (e.g. anti-rootkits). The necessity of more research on anti-forensics motivated us to propose a game-theoretic approach to model the interactions between an attacker and an investigator (players) who use rootkits and anti-rootkits, respectively. We assume these players act competitively, and each does not know his/her opponent's pay-off. We identify sets of characteristics for rootkits and anti-rootkits to profile them and define each player's actions. We examine the existence of the Nash Equilibrium for a two-player game. Experimental results show the simulated game is convergent. Thus, we identify the investigators' most desirable and stable defensive strategies against the attacker's most desirable and stable offensive strategies. We also formulate a relationship between characteristics of rootkits and anti-rootkits using the Nash Equilibrium of the game. Finally, we propose some general features to help investigators to evaluate anti-rootkits and design more efficient defensive tools. • Rootkits and anti-rootkits can be profiled by a set of comprehensive characteristics. • Game theory models forensic agents' interactions who use rootkits and anti-rootkits • The investigator's best defensive strategies can be identified against an attacker. • There is a relationship among characteristics of rootkits and anti-rootkits [ABSTRACT FROM AUTHOR]

In the present study, industrial wastes such as Granulated Blast Furnace Slag (GBFS) and Basic Oxygen Furnace Slag (BOFS) activated with calcium oxide (CaO) and medium reactive magnesia (MgO) are used for chemical stabilization of a soft clay. This environmentally friendly approach can eliminate the hazards associated with improper waste disposal and reduce greenhouse gas emissions generated by cement production. To this end, various amounts of additives (ranging from 2.5 to 20%) with the activator:slag ratio of 1:3 are added to kaolinite clay and cured at two temperatures of 20 and 45°C. A series of laboratory tests, including pH, Electrical Conductivity (EC), one-dimensional consolidation, Unconfined Compressive Strength (UCS), are conducted on the stabilized samples. The increasing temperature causes a faster formation of cementitious products and a higher UCS value, as confirmed by the SEM micrographs and XRD analysis, particularly in the case of MgO-BOFS (MB) and CaO-BOFS (CB) samples with the UCS values of 4 and 4.7 MPa after 90 days of curing, respectively. Furthermore, the MB- and CB-stabilized clay samples show a better compressibility characteristic compared to the MgO-GBFS (MG) and CaO-GBFS (CG) blends. To further enhance the activity of the additives and to prepare a slag-clay based geopolymers, two types of alkaline solutions at various Na 2 SiO 3 :NaOH ratios are added to the mixtures at the final step. In addition, the energy absorption capacity (E u) and the secant modulus (E 50) of the optimum blends are determined to assess the toughness and stiffness of the samples. The results indicate that the UCS values of the MB and CB samples increase up to 7.41 MPa and 8.44 MPa after 90 days of curing, respectively, when the Na 2 SiO 3 :NaOH ratio is 80:20. Generally, the use of slag-clay based geopolymers, particularly BOFS, is very effective to address the problems associated with the soft soil and the optimum mixtures are successful in decreasing settlements and enhancing compressive strength of the soft soil, which can be considered for use as a pavement base material. • Soft clays can be satisfactorily treated when GBFS and BOFS are activated by CaO and MgO. • Increasing temperature can give rise to the faster formation of cementitious products, particularly in MB and CB samples. • The clay-BOFS based geopolymers show the highest increase on the UCSs of the samples in the Na 2 SiO3:NaOH ratio of 80:20. • The MB- and CB-treated samples represent a better compressibility compared to the MG and CG treatment. [ABSTRACT FROM AUTHOR]

A network intrusion detection system is an essential part of network security research. It detects intrusion behaviors through active defense technology and takes emergency measures such as alerting and terminating intrusions. To this end, with the rapid development of learning technology, various machine-learning-based and deep-learning-based approaches have been developed, but there is a limitation in the detection accuracy. We believe that dealing with network traffic as if they are vibrations, waves, or sounds would allow us to detect intruders better. In this work, we envisioned a novel Network Intrusion Detection System called "the sound of intrusion". The proposed system transforms the traffic flow features into waves and utilizes advanced audio/speech recognition deep-learning-based techniques to detect intruders. We used several deep-learning-based techniques including long short-term memory, deep belief networks, and convolutional neural networks. The proposed approach has been validated using two well-known and recent benchmark datasets namely NSLKDD and CIC-IDS2017. It achieves the highest detection accuracy, 84.82%, and 99.41%, with the lowest false alarm rate of 0.12% and 0.004% on two common network intrusion detection systems datasets, namely NSL-KDD and CICIDS2017, respectively. It demonstrates improvements over existing approaches, and shows a strong potential for use as a modern Network Intrusion Detection System. [Display omitted] • Deep-learning-based NIDS has been proven to be successful and effective. • Network flow features have been considered as sounds. • Highest detection accuracy with the lowest false alarm have been achieved. [ABSTRACT FROM AUTHOR]

Normal hearing system is an essential factor for accurate production of speech segments. It seems that cochlear implant prosthesis helps children with hearing impairment to speak more accurately than before receiving prosthesis. The current research aimed to compare the vowel duration in school-aged children with cochlear implants and that in children with normal hearing. Additionally, the performance of girls and boys in two groups were investigated. A cross-sectional and descriptive-analytical study was carried out to compare the vowel duration in 9- to 12-year-old children with cochlear implant and those with normal hearing. Participants were 52 children who were matched by age and sex. We asked the children to read the target words with each word including one vowel and then participants' voice samples were recorded. Then, vowel duration was measured using Praat software. Finally, the vowel duration was compared between the two groups running independent sample t -test. The level of significance was (P < 0.05). There was no statistically significant difference observed between the two groups in the mean values of the vowel duration for the six Persian vowels (P > 0.05). Also, no significant difference was found between boys and girls in the mean value of the vowel duration between the two groups (P > 0.05). Persian vowels in school-aged children with cochlear implant and with typical hearing are produced with similar durations. This finding is probably related to the increased duration of using prosthesis in this age range and speech mode used to measure vowel duration in the present study. [ABSTRACT FROM AUTHOR]

An RFID ownership transfer protocol enables a tag owner to transfer the ownership of the tag to a new owner. While there have been a large number of such protocols in the literature, designing secure and efficient protocols remains a challenging task. In this paper, we propose a scalable and secure RFID ownership transfer protocol that can be deployed in resource-constrained EPC class tags in a large RFID inventory system. The contribution of this paper include: employing a Semi-Trusted Party (STP) to leverage the essence of typical complex ownership transfer process for the end users, introducing a new variant of mutual authentication scheme from Learning Parity from Noise (LPN) problem to the typical ownership transfer protocol, allowing multiple tags from an owner to be transferred to the new owner by combining homomorphic aggregated signature (HomSig) and pseudo-inverse matrix properties. We demonstrate that the scheme is secure under the standard model. To the best of our knowledge, this is the first provably secure LPN-based ownership transfer protocol that allows relatively small gate-count and code size suitable for the low-cost and resource-constrained IoT devices. [ABSTRACT FROM AUTHOR]

The increasing performance and wider spread use of automated semantic annotation and entity linking platforms has empowered the possibility of using semantic information in information retrieval. While keyword-based information retrieval techniques have shown impressive performance, the addition of semantic information can increase retrieval performance by allowing for more accurate sense disambiguation, intent determination, and instance identification, just to name a few. Researchers have already delved into the possibility of integrating semantic information into practical search engines using a combination of techniques such as using graph databases, hybrid indices and adapted inverted indices, among others. One of the challenges with the efficient design of a search engine capable of considering semantic information is that it would need to be able to index information beyond the traditional information stored in inverted indices, including entity mentions and type relationships. The objective of our work in this paper is to investigate various ways in which different data structure types can be adopted to integrate three types of information including keywords, entities and types. We will systematically compare the performance of the different data structures for scenarios where (i) the same data structure types are adopted for the three types of information, and (ii) different data structure types are integrated for storing and retrieving the three different information types. We report our findings in terms of the performance of various query processing tasks such as Boolean and ranked intersection for the different indices and discuss which index type would be appropriate under different conditions for semantic search. [ABSTRACT FROM AUTHOR]

The current paper aims to study the free vibration analysis of a sandwich plate in contact with quiescent fluid. The structure is made of an electro-rheological (ER) fluid core, and two laminated composite skins. The fluid is ideal, interacting partially with a plate, and fluid potential velocity is derived, satisfying continuity equation. Higher-order shear deformable theory is employed for the displacement field, and nonlinear Von-Karman strains are taken into account. After calculating the structural strain energy and kinetic energies of the fluid and plate, Galerkin approach and harmonic balance method are adopted to obtain natural frequencies of the system. Next, the accuracy and reliability of the developed model are confirmed, and then a detailed parametric study is conducted to examine the effects of different parameters such as geometrical dimensions of plate, fluid parameters and electric field strength on vibrational characteristics of the structure. The novelty of the presented model focuses on the nonlinear analysis of an ER sandwich panel coupled to ideal fluid, and the obtained results can guide the future design of composite ER panels. • Studied the vibrational response of a sandwich panel with a smart fluid in interaction with quiescent fluid. • Studied the effects of geometric nonlinearity on the vibrational characteristics of the panel. • Considered the impacts of transverse shear stresses and rotary inertias for both skins and core in analysis. • Studied the fluid–structure interaction effects of an electro-rheological sandwich panel. • Studied the effects of electric field intensity on the modal loss factor and natural frequencies. [ABSTRACT FROM AUTHOR]