Internal curing of high performance concrete using lightweight and recycled aggregates

Concrete curing is of paramount importance in order for concrete to meet performance requirements. Conventionally, curing has been conducted by means of water sparkling, wet burlap or a curing compound. For performance and environmental reasons, internal curing has been gaining increased attention. However, more data is needed for the effectiveness of this curing technique when used in various concrete mixtures. This investigation addresses potential utilization of internal curing in high performance concrete (HPC). Internal curing was introduced by means of three aggregates: perlite, pumice and recycled aggregates; all of which were incorporated into HPC mixtures. Conventional mixtures were prepared and were thoroughly cured either by water or by a curing compound or left non-cured. Fresh concrete and Hardened concrete properties were assessed including slump, unit weight, compressive and flexural strength, and durability tests as shrinkage assessment, rapid chloride permeability test (RCPT) and abrasion resistance. Experimental work is backed up with a simplified feasibility analysis with case study, incorporating initial and future costs to better judge potential of this technique. The outcome of this study uncovers that the addition of pre-wetted lightweight aggregates can prompt an enhancement in concrete workability and durability accompanied by a reduced shrinkage. Compressive and flexural strengths decreased with the increased replacement dosages, however several dosages were tested to reach a figure of optimum replacement. Results of this study reveal the potential of this technology in saving fresh water as well as the costs saved in maintenance and rehabilitation works

Cobalt Sulfide/Spongy functionalized Graphene nanostructured electrodes for High-Performance Supercapacitors

A simple approach is illustrated for the preparation of functionalized spongy graphene/cobalt sulfide (FG-CoS) nanocomposites as unified, porous 3-dimensional (3D) network crinkly sheets. These crinkly sheets contain the reduced spongy graphene oxide (SGO) sheets and the intercalated CoS nanoparticles within the spongy graphene. The fabricated FG-CoS composites were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and Raman spectroscopy. The synthesized materials were examined as supercapacitor materials in an aqueous electrolyte (3M KOH) using cyclic voltammetry (CV) at a wide range of potential scan rates, and galvanostatic charge/discharge at various current densities. The FG-CoS electrode yielded a maximum specific capacitance of 1072 F/g at a scan rate of 1 mV/s. In addition, it showed outstanding cyclability retention of 117% after the 1000th cycle at 100mV/s. The obtained energy density is 35.2 Wh/kg along with a power density of 250 W/kg at 1.0 A/g. Such high performance can be attributed to the synergistic effect of graphene and CoS, where CoS is sandwiched between graphene nanosheets. This makes the FG/CoS composite a promising electrode material for a superior-performance supercapacitor

Integrating identity-based cryptography in IMS service authentication

Nowadays, the IP Multimedia Subsystem (IMS) is a promising research field. Many ongoing works related to the security and the performances of its employment are presented to the research community. Although, the security and data privacy aspects are very important in the IMS global objectives, they observe little attention so far. Secure access to multimedia services is based on SIP and HTTP digest on top of IMS architecture. The standard deploys AKA-MD5 for the terminal authentication. The third Generation Partnership Project (3GPP) provided Generic Bootstrapping Architecture (GBA) to authenticate the subscriber before accessing multimedia services over HTTP. In this paper, we propose a new IMS Service Authentication scheme using Identity Based cryptography (IBC). This new scheme will lead to better performances when there are simultaneous authentication requests using Identity-based Batch Verification. We analyzed the security of our new protocol and we presented a performance evaluation of its cryptographic operationsComment: 13Page

MAT-754: INTERNAL CURING OF HIGH PERFORMANCE CONCRETE USING LIGHTWEIGHT AND RECYCLED CONCRETE AGGREGATES

Concrete curing is of paramount importance in order for concrete to meet performance requirements. Conventionally, curing has been conducted by means of water sparkling, wet burlap or a curing compound. For performance and environmental reasons, internal curing has been gaining increased attention. However, more data is needed for the effectiveness of this curing technique when used in various concrete mixtures. This investigation addresses potential utilization of internal curing in high performance concrete (HPC). Internal curing was introduced by means of three aggregates: perlite, pumice and recycled aggregates; all of which were incorporated into HPC mixtures. Conventional mixtures were prepared and were thoroughly cured either by water or by a curing compound or left non-cured. Fresh concrete and Hardened concrete properties were assessed including slump, unit weight, compressive and flexural strength, and durability tests such as shrinkage assessment, rapid chloride permeability test (RCPT) and abrasion resistance. Experimental work is backed up with a simplified feasibility analysis with case study, incorporating initial and future costs to better judge potential of this technique. The outcome of this study uncovers that the addition of pre-wetted lightweight aggregates can prompt an enhancement in concrete workability and durability accompanied by a reduced shrinkage. Compressive and flexural strengths decreased with the increased replacement dosages, however several dosages were tested to reach a figure of optimum replacement. Results of this study reveal the potential of this technology in saving fresh water as well as the costs saved in maintenance and rehabilitation works

Finite element based overall optimization of switched reluctance motor using multi-objective genetic algorithm (NSGA-II)

The design of switched reluctance motor (SRM) is considered a complex problem to be solved using conventional design techniques. This is due to the large number of design parameters that should be considered during the design process. Therefore, optimization techniques are necessary to obtain an optimal design of SRM. This paper presents an optimal design methodology for SRM using the non-dominated sorting genetic algorithm (NSGA-II) optimization technique. Several dimensions of SRM are considered in the proposed design procedure including stator diameter, bore diameter, axial length, pole arcs and pole lengths, back iron length, shaft diameter as well as the air gap length. The multi-objective design scheme includes three objective functions to be achieved, that is, maximum average torque, maximum efficiency and minimum iron weight of the machine. Meanwhile, finite element analysis (FEA) is used during the optimization process to calculate the values of the objective functions. In this paper, two designs for SRMs with 8/6 and 6/4 configurations are presented. Simulation results show that the obtained SRM design parameters allow better average torque and efficiency with lower iron weight. Eventually, the integration of NSGA-II and FEA provides an effective approach to obtain the optimal design of SRM

Multi-objective optimization of switched reluctance machine design using Jaya algorithm (MO-Jaya)

The switched reluctance machine (SRM) design is different from the design of most of other machines. SRM has many design parameters that have non-linear relationships with the performance indices (i.e., average torque, efficiency, and so forth). Hence, it is difficult to design SRM using straight forward equations with iterative methods, which is common for other machines. Optimization techniques are used to overcome this challenge by searching for the best variables values within the search area. In this paper, the optimization of SRM design is achieved using multi-objective Jaya algorithm (MO-Jaya). In the Jaya algorithm, solutions are moved closer to the best solution and away from the worst solution. Hence, a good intensification of the search process is achieved. Moreover, the randomly changed parameters achieve good search diversity. In this paper, it is suggested to also randomly change best and worst solutions. Hence, better diversity is achieved, as indicated from results. The optimization with the MO-Jaya algorithm was made for 8/6 and 6/4 SRM. Objectives used are the average torque, efficiency, and iron weight. The results of MO-Jaya are compared with the results of the non-dominated sorting genetic algorithm (NSGA-II) for the same conditions and constraints. The optimization program is made in Lua programming language and executed by FEMM4.2 software. The results show the success of the approach to achieve better objective values, a broad search, and to introduce a variety of optimal solutions

Deep learning can improve early skin cancer detection

Skin cancer is the most common form of cancer affecting humans. Melanoma is the most dangerous type of skin cancer; and early diagnosis is extremely vital in curing the disease. So far, the human knowledge in this field is very limited, thus, developing a mechanism capable of identifying the disease early on can save lives, reduce intervention and cut unnecessary costs. In this paper, the researchers developed a new learning technique to classify skin lesions, with the purpose of observing and identifying the presence of melanoma.  This new technique is based on a convolutional neural network solution with multiple configurations; where the researchers employed an International Skin Imaging Collaboration (ISIC) dataset. Optimal results are achieved through a convolutional neural network composed of 14 layers. This proposed system can successfully and reliably predict the correct classification of dermoscopic lesions with 97.78% accuracy