Suppression of the α → β-nickel hydroxide transformation in concentrated alkali: Role of dissolved cations

The presence of dissolved cations such as Al and Zn in alkaline electrolyte (6 M KOH) suppresses the -nickel hydroxide transformation. The uptake of Al (10 mol%) and Zn (30 mol%) exhibited by the active material likely stabilizes the -phase. Dissolved Al is deleterious to the performance of the nickel hydroxide electrode, whereas, dissolved Zn enhances the specific discharge capacity of nickel hydroxide by approximately 25% showing that the mode of metal uptake is different in the two cases.     

Faceless identification based on temporal strips

This paper first presents a novel approach for modelling facial features, Local Directional Texture (LDT), which exploits the unique directional information in image textures for the problem of face recognition. A variant of LDT with privacy-preserving temporal strips (TS) is then considered to achieve faceless recognition with a higher degree of privacy while maintaining high accuracy. The TS uses two strips of pixel blocks from the temporal planes, XT and YT, for face recognition. By removing the reliance on spatial context (i.e., XY plane) for this task, the proposed method withholds facial appearance information from public view, where only one-dimensional temporal information that varies across time are extracted for recognition. Thus, privacy is assured, yet without impeding the facial recognition task which is vital for many security applications such as street surveillance and perimeter access control. To validate the reliability of the proposed method, experiments were carried out using the Honda/UCSD, CK+, CAS(ME)² and CASME II databases. The proposed method achieved a recognition rate of 98.26% in the standard video-based face recognition database, Honda/UCSD. It also offers a 81.92% reduction in the dimension length required for storing the extracted features, in contrast to the conventional LBP-TOP.

     

Improving delamination resistance of carbon fiber reinforced polymeric composite by interface engineering using carbonaceous nanofillers through electrophoretic deposition: An assessment at different in-service temperatures

In this article, modification of carbon fiber surface by carbon based nanofillers (multi-walled carbon nanotubes [CNT], carbon nanofibers, and multi-layered graphene) has been achieved by electrophoretic deposition technique to improve its interfacial bonding with epoxy matrix, with a target to improve the mechanical performance of carbon fiber reinforced polymer composites. Flexural and short beam shear properties of the composites were studied at extreme temperature conditions; in-situ cryo, room and elevated temperature (−196, 30, and 120°C respectively). Laminate reinforced with CNT grafted carbon fibers exhibited highest delamination resistance with maximum improvement in flexural strength as well as in inter-laminar shear strength (ILSS) among all the carbon fiber reinforced epoxy (CE) composites at all in-situ temperatures. CNT modified CE composite showed increment of 9% in flexural strength and 17.43% in ILSS when compared to that of unmodified CE composite at room temperature (30°C). Thermomechanical properties were investigated using dynamic mechanical analysis. Fractography was also carried out to study different modes of failure of the composites.     

Effects of fiber surface grafting by functionalized carbon nanotubes on the interfacial durability during cryogenic testing and conditioning of CFRP composites

Carbon fiber reinforced epoxy (CE) composite is ideal for a cryogenic fuel storage tank in space applications due to its unmatched specific strength and modulus. In this article, inter-laminar shear strength (ILSS) of carbon fiber/epoxy (CE) composite is shown to be considerably improved by engineering the interface with carboxyl functionalized multi-walled carbon nanotube (FCNT) using electrophoretic deposition technique. FCNT deposited fibers from different bath concentrations (0.3, 0.5, and 1.0 g/L) were used to fabricate the laminates, which were then tested at room (30°C) and in-situ liquid nitrogen (LN) (−196°C) temperature as well as conditioning for different time durations (0.25, 0.5, 1, 6, and 12 h) followed by immediate RT testing to study the applicability of these engineered materials at the cryogenic environment. A maximum increment in ILSS was noticed at bath concentration of 0.5 g/L, which was ~21% and ~ 17% higher than neat composite at 30°C and − 196°C, respectively. Short-term LN conditioning was found to be detrimental due to developed cryogenic shock, which was further found to be compensated by cryogenic interfacial clamping upon long-term exposure.     

Wii remote–based low-cost motion capture for automated assembly simulation

This paper describes the development of a Wii remote (Wiimote)–based low-cost motion capture system and demonstrates its application for automated assembly simulation. Multiple Wiimotes are used to form a vision system to perform motion capture in 3D space. A hybrid algorithm for calibrating a multi-camera stereo vision system has been developed based on Zhang’s and Svoboda’s calibration algorithms. This hybrid algorithm has been evaluated and shown accuracy improvement over Svoboda’s algorithm for motion capture with multiple cameras. The captured motion data are used to automatically generate an assembly simulation of objects represented by CAD models in real time. The Wiimote-based motion capture system is practically attractive because it is inexpensive, wireless, and easily portable. Application examples have been developed for a single vision system with two Wiimotes to track the assembly of a microsatellite prototype frame and for an integrated vision system with four Wiimotes to track the assembly of a bookshelf.     

Metal-Organic Framework Thin Films Grown on Functionalized Graphene as Solid-State Ion-Gated FETs

The unique properties of 2D-materials like graphene are exploited in various electronic devices. In sensor applications, graphene shows a very high sensitivity, but only a low specificity. This shortcoming can be mastered by using heterostructures, where graphene is combined with materials exhibiting high analyte selectivities. Herein, this study demonstrates the precise deposition of nanoporous metal-organic frameworks (MOFs) on graphene, yielding bilayers with excellent specificity while the sensitivity remains large. The key for the successful layer-by-layer deposition of the MOF films (SURMOFs) is the use of planar polyaromatic anchors. Then, the MOF pores are loaded with ionic liquid (IL). For functioning sensor devices, the IL@MOF films are grown on graphene field-effect transistors (GFETs). Adding a top-gate electrode yields an ion-gated GFET. Analysis of the transistor characteristics reveals a clear Dirac point at low gate voltages, good on-off ratios, and decent charge mobilities and densities in the graphene channel. The GFET-sensor reveals a strong and selective response. Compared to other ion-gated-FET devices, the IL@MOF material is relatively hard, allowing the manufacturing of ultrathin devices. The new MOF-anchoring strategy offers a novel approach generally applicable for the functionalization of 2D-materials, where MOF/2D-material hetero-bilayers carry a huge potential for a wide variety of applications.     

Polynomial based scheme (PBS) for establishing Authentic Associations in Wireless Mesh Networks

The varying degree of mobility of Mesh Clients has provided much more flexibility in Wireless Mesh Networks, and establishing an Authentic Association among entities is a non-trivial problem. In this paper, we introduce a Polynomial Based scheme which provides pair-wise connectivity, low communication, marginal storage overhead and high scalability while making on the fly Authentic Association feasible. The proposed scheme is also observed to be resilient against both traffic analysis and node capture attacks.     

Observing Human-Object Interactions: Using Spatial and Functional Compatibility for Recognition

Interpretation of images and videos containing humans interacting with different objects is a daunting task. It involves understanding scene/event, analyzing human movements, recognizing manipulable objects, and observing the effect of the human movement on those objects. While each of these perceptual tasks can be conducted independently, recognition rate improves when interactions between them are considered. Motivated by psychological studies of human perception, we present a Bayesian approach which integrates various perceptual tasks involved in understanding human-object interactions. Previous approaches to object and action recognition rely on static shape/appearance feature matching and motion analysis, respectively. Our approach goes beyond these traditional approaches and applies spatial and functional constraints on each of the perceptual elements for coherent semantic interpretation. Such constraints allow us to recognize objects and actions when the appearances are not discriminative enough. We also demonstrate the use of such constraints in recognition of actions from static images without using any motion information.     

Inventory and flow control of the IGCC process with CO2 recycles

We present control strategies for an Integrated Gasification Combined Cycle (IGCC) power plant with CO₂ recycles. One recycle allows for composition control and is useful when the side objective is to produce synthesis gas for chemicals. The second recycle enables temperature control in the gas turbine by using CO₂ as a diluent. The main advantages of the second recycle are that NO_x is not produced and that CO₂/H₂O separation is significantly easier than CO₂/N₂ separation, which reduces cost if the CO₂ is to be sequestered. Models and control systems are developed using process network theory. We introduce a novel method for controlling quality variables and functions of inventories. Dynamic simulations using MATLAB/Simulink models show the response to step changes in setpoints and disturbances. The inventory control method is derived from conservation laws and the second law and it is applicable to process system models of any degree of complexity. A steady-state sensitivity analysis is performed, examining the effect of changing the temperature and C:O ratio within the gasifier on the power production.