Behavior of FRP Strengthened Reinforced Concrete Beams under Torsion

The use of fiber reinforced plastics (FRPs) for flexural and shear strengthening of reinforced concrete beams has been scrutinized to a considerable depth by researchers worldwide. The area of torsional strengthening however has not been as popular. This paper presents the results of an experimental investigation together with a numerical study on reinforced concrete beams subjected to torsion that are strengthened with FRP wraps in a variety of configurations. In the experimental study, the increase in the ultimate torque for different strengthening configurations, failure mechanisms, crack patterns, and ductility levels are monitored and presented. Experimental results show that FRP wraps can increase the ultimate torque of fully wrapped beams considerably in addition to enhancing the ductility. The experimental results upgrade the weak archival data on torsional strengthening by application of FRP. The numerical section reports on analyses performed by the ANSYS finite element program. Predictions are compared with experimental findings and are in reasonable agreement.     

A new formulation of fringing capacitance and its application to the control of parallel-plate electrostatic micro actuators

Though the effect of fringing field in electrostatic parallel-plate actuators is a well-understood phenomenon, the existing formulations often result in complicated mathematical models from which it is difficult to determine the deflection of the moving plate for given voltages and hence, they are not suitable for accurate actuation control. This work presents a new formulation for tackling the fringing field, in which the effect of fringing field is modeled as a variable serial capacitor. Based on this model, a robust control scheme is constructed using the theory of input-to-state stabilization (ISS) and backstepping state feedback design. This method allows loosening the stringent requirements on modeling accuracy without compromising the performance. The stability and the performance of the system using this control scheme are demonstrated through both stability analysis and numerical simulation.     

A Gauss–Newton approach to joint image registration and intensity correction

We develop a new efficient numerical methodology for automated simultaneous registration and intensity correction of images. The approach separates the intensity correction term from the images being registered in a regularized expression. Our formulation is consistent with the existing non-parametric image registration techniques, however, an extra additive intensity correction term is carried throughout. An objective functional is formed for which the corresponding Hessian and Jacobian is computed and employed in a multi-level Gauss–Newton minimization approach. In this paper, our experiments are based on elastic regularization on the transformation and total variation on the intensity correction. Validations on dynamic contrast enhanced MR abdominal images for both real and simulated data verified the efficacy of the model.     

Boundary query solution using convex hull algorithm

An important issue in database (DB) systems is responding to different users’ queries in an acceptable time. To do this, we should define different queries based on users’ real needs and we should consider suitable solutions. In this article, we express a new query called ‘boundary query’ which is used for achieving an overall view of a subject in the DB. This query does not return all query answers but it returns boundary values that cover all answers for the related query. In this article, we map a DB environment to a vector space based on necessary attributes. Then we implement the proposed method, and based on the results, we observe that the proposed method's run time is acceptable for huge DBs.     

A graph mining approach for detecting unknown malwares

Nowadays malware is one of the serious problems in the modern societies. Although the signature based malicious code detection is the standard technique in all commercial antivirus softwares, it can only achieve detection once the virus has already caused damage and it is registered. Therefore, it fails to detect new malwares (unknown malwares). Since most of malwares have similar behavior, a behavior based method can detect unknown malwares. The behavior of a program can be represented by a set of called API's (application programming interface). Therefore, a classifier can be employed to construct a learning model with a set of programs' API calls. Finally, an intelligent malware detection system is developed to detect unknown malwares automatically. On the other hand, we have an appealing representation model to visualize the executable files structure which is control flow graph (CFG). This model represents another semantic aspect of programs. This paper presents a robust semantic based method to detect unknown malwares based on combination of a visualize model (CFG) and called API's. The main contribution of this paper is extracting CFG from programs and combining it with extracted API calls to have more information about executable files. This new representation model is called API-CFG. In addition, to have fast learning and classification process, the control flow graphs are converted to a set of feature vectors by a nice trick. Our approach is capable of classifying unseen benign and malicious code with high accuracy. The results show a statistically significant improvement over n-grams based detection method.     

A high‐voltage gain nonisolated noncoupled inductor based multi‐input DC‐DC topology with reduced number of components for renewable energy systems

This paper proposes a modular nonisolated noncoupled inductor‐based high‐voltage gain multi‐input DC‐DC converter. Despite the high‐voltage gain of the proposed topology, the average of normalized voltage stress (NVS) on its switches/diodes is low. This property leads to less loss and cost of switches/diodes. Using the same number of components, the proposed topology produces higher voltage gains, in comparison with recently presented high step‐up topologies. Also, the proposed topology utilizes less number of components (capacitors, inductors, diodes, and switches) for producing a desired voltage gain, which can reduce the size, mass, cost, complexity, and losses and improve the efficiency of converter. Continuous current of input sources is another main advantage of the proposed topology. All the abovementioned characteristics have made the proposed topology very suitable for renewable energy systems (or even hybrid/electric vehicles). Design considerations of the proposed topology have also been presented. For better evaluation, the proposed topology has been compared with some of recently presented high step‐up structures, from viewpoints of producible voltage gain, number of components, and normalized voltage stress (NVS) on switches/diodes. Finally, the prototype of 2‐input version has been experimentally implemented. Obtained experimental results confirm appropriate performance of the proposed topology.     

A selective modified bentonite–porphyrin carbon paste electrode for determination of Mn(II) by using anodic stripping voltammetry

A novel voltammetric sensor based on chemically modified bentonite–porphyrin carbon paste electrode (MBPCE) has been introduced for the determination of trace amount of Mn(II) in wheat flour, wheat rice and vegetables. In this method Mn(II) gives well-defined voltammetric peak at the pH range of 3.5–7.5. For the preliminary screening purpose, the catalyst was prepared by modification of bentonite with porphyrin and characterized by thermogravimetric method (TG) and UV–vis spectroscopy. The detection limit (three times signal-to-noise) with 4 min accumulation is 1.07 × 10⁻⁷ mol L⁻¹ Mn(II). The peak currents increases linearly with Mn(II) concentration over the range of 6.0 × 10⁻⁷ to 5.0 × 10⁻⁴ mol L⁻¹ (r² = 0.9959). Statistical treatment of the results gave a relative standard deviation lower than 2.30%. The chemical and instrumental parameters have been optimized and the results showed that 1000-fold excess of the additive ions had not interferences on the determination of Mn(II).     

The effect of promoters on the CO<Subscript>2</Subscript> reforming activity and coke formation of nanocrystalline Ni/Al<Subscript>2</Subscript>O<Subscript>3</Subscript> catalysts prepared by microemulsion method

Mesoporous nanocrystalline nickel-alumina promoted catalysts with high surface area were prepared by microemulsion (ME) method and employed in dry reforming of methane reaction. The catalysts were characterized by X-ray diffraction (XRD), Brunauer-Emmett-Teller surface area analysis (BET), temperature programmed reduction (TPR) and temperature programmed oxidation (TPO) techniques. The results showed that the prepared catalysts had high porosity with great surface area and small crystallite size. Among the K₂O, MgO, CaO and BaO promoters, the MgO promoter showed considerable effect on catalytic performance and coke suppression of catalyst.