A semantic image classifier based on hierarchical fuzzy association rule mining

One of the major challenges in the content-based information retrieval and machine learning techniques is to-build-the-so-called “semantic classifier” which is able to effectively and efficiently classify semantic concepts in a large database. This paper dealt with semantic image classification based on hierarchical Fuzzy Association Rules (FARs) mining in the image database. Intuitively, an association rule is a unique and significant combination of image features and a semantic concept, which determines the degree of correlation between features and concept. The main idea behind this approach is that any image visual concept has some associated features, so that, there are strong correlations between the concepts and their corresponding features. Regardless of the semantic gap, an image concept appears when the corresponding features emerge in an image and vice versa. Specially, this paper’s contribution was to propose a novel Fuzzy Association Rule for improving traditional association rules. Moreover, it was concerned with establishing a hierarchical fuzzy rule base in the training phase and setup corresponding fuzzy inference engine in order to classify images in the testing phase. The presented approach was independent from image segmentation and can be applied on multi-label images. Experimental results on a database of 6000 general-purpose images demonstrated the superiority of the proposed algorithm.     

An analytical model for manufacturing service supply contracts

The practice of service-based manufacturing, utilized in various industries, particularly in electronics, pharmaceuticals, and automotive, is on the rise as it improves enterprise effectiveness in dynamic markets. The mutual responsibilities between the supplier(s) and user(s) of such services are spelled out in defined-time-horizon contracts. While such contracts define mutual obligations of both parties on a tactical/operational level, the long-term strategic objectives of the parties may be in conflict. This paper is focused on studying the dynamics of manufacturing service contracts. It investigates the factors affecting the shape of the negotiation space for such contracts and also the way the space should be navigated in response to changing market conditions. The paper presents an analytical framework developed to facilitate behavior analysis of the actors involved in the contract.     

Detailed Real-Time Urban 3D Reconstruction from Video

The paper presents a system for automatic, geo-registered, real-time 3D reconstruction from video of urban scenes. The system collects video streams, as well as GPS and inertia measurements in order to place the reconstructed models in geo-registered coordinates. It is designed using current state of the art real-time modules for all processing steps. It employs commodity graphics hardware and standard CPU’s to achieve real-time performance. We present the main considerations in designing the system and the steps of the processing pipeline. Our system extends existing algorithms to meet the robustness and variability necessary to operate out of the lab. To account for the large dynamic range of outdoor videos the processing pipeline estimates global camera gain changes in the feature tracking stage and efficiently compensates for these in stereo estimation without impacting the real-time performance. The required accuracy for many applications is achieved with a two-step stereo reconstruction process exploiting the redundancy across frames. We show results on real video sequences comprising hundreds of thousands of frames.     

Dependency-based security risk assessment for cyber-physical systems

A cyber-physical attack is a security breach in cyber space that impacts on the physical environment. The number and diversity of such attacks against Cyber-Physical Systems (CPSs) are increasing at impressive rates. In times of Industry 4.0 and Cyber-Physical Systems, providing security against cyber-physical attacks is a serious challenge which calls for cybersecurity risk assessment methods capable of investigating the tight interactions and interdependencies between the cyber and the physical components in such systems. However, existing risk assessment methods do not consider this specific characteristic of CPSs. In this paper, we propose a dependency-based, domain-agnostic cybersecurity risk assessment method that leverages a model of the CPS under study that captures dependencies among the system components. The proposed method identifies possible attack paths against critical components of a CPS by taking an attacker’s viewpoint and prioritizes these paths according to their risk to materialize, thus allowing the defenders to define efficient security controls. We illustrate the workings of the proposed method by applying it to a case study of a CPS in the energy domain, and we highlight the advantages that the proposed method offers when used to assess cybersecurity risks in CPSs.

     

Hamshahri: A standard Persian text collection

The Persian language is one of the dominant languages in the Middle East, so there are significant amount of Persian documents available on the Web. Due to the different nature of the Persian language compared to the other languages such as English, the design of information retrieval systems in Persian requires special considerations. However, there are relatively few studies on retrieval of Persian documents in the literature and one of the main reasons is the lack of a standard test collection. In this paper, we introduce a standard Persian text collection, named Hamshahri, which is built from a large number of newspaper articles according to TREC specifications. Furthermore, statistical information about documents, queries and their relevance judgments are presented in this paper. We believe that this collection is the largest Persian text collection, so far.     

An algorithm for polygonal approximation of a digital object

A fast and simple heuristic algorithm for polygonal approximation is presented. The algorithm is based on a mark and sweep technique. Results of computer implementation with various images are reported.     

Properties and Mechanism of Al/St Bimetal Tube Bonding Produced by Cold Spin-Bonding (CSB) Process

Spin-bonding is a novel tube cladding method for fabrication of bilayer tubes based on flow-forming process. The bimetal Al/St tubular components have extensive application in different industries. In this paper, an Al/St bimetal tube was successfully produced at different thickness reductions from 35 to 65% and mechanical and metallurgical aspects of the joint were investigated. Peeling tests were done to investigate the strength of the bond. The results showed that an increase in the thickness reduction led to a significant increase in the bond strength. Besides, the bonding mechanism between Al as inner tube to St as an outer one resulting from spin-bonding process was investigated. The results showed that an excellent bonding of Al and St tubes could be achieved from this process. The results showed that the bonding process consisted of three stages. First, removal of surface layers resulting in contact between the virgin metals of two bond surfaces and then an unstable bond was formed that stabilized as deformation proceeded. Finally the bond strengthening occurred. The SEM micrographs of the peeled surfaces showed that removing surface films in aluminum and steel in the first stage was based on different mechanisms. Also, SEM back-scatter images of bond interface showed that no intermetallic phases were formed.     

Tracking Performance of an Adaptive MIMO-OFDM LS Estimator via MSE Criterion Over a Wireless Time Correlated Fading Channel

In this contribution, the performance of an adaptive least squares channel estimator for a time correlated MIMO-OFDM channel is presented in a closed form relation. As a criterion for performance evaluation, the well-known mean square error (MSE) is employed. The pilot aided channel estimation is used to extract the channel coefficients. To minimize the MSE and arrange phase shift orthogonally, the pilots are constructed with equal power and space. The model of the channel is developed by implementing a first order Markov model, and it is proved that the performance of the system is dependent upon the defined forgetting factor, the number of transmit antennas, the number of multipath channel taps, transmitted power, and Doppler shift. The effect of each parameter on the performance of the system is discussed separately. The computer simulation results follow with the analytical results comprehensively.