Human factors and qualitative pedagogical evaluation of a mobile augmented reality system for science education used by learners with physical disabilities

Technology-enhanced learning, employing novel forms of content representation and education service delivery by enhancing the visual perception of the real environment of the user, is favoured by proponents of educational inclusion for learners with physical disabilities. Such an augmented reality computer-mediated learning system has been developed as part of an EU funded research project, namely the CONNECT project. The CONNECT project brings together schools and science centres, and produces novel information and communication technologies based on augmented reality (AR) and web-based streaming and communication, in order to support learning in a variety of settings. The CONNECT AR interactive learning environment can assist users to better contextualize and reinforce their learning in school and in other settings where people learn (i.e. science centres and home). The CONNECT concept and associated technologies encourage users to visit science centres and perform experiments that are not possible in school. They can also build on these experiences back at school and at home with visual augmentations that they are communicated through web-based streaming technology. This paper particularly focuses on a user-centred evaluation approach of human factors and pedagogical aspects of the CONNECT system, as applied to a special needs user group. The main focus of the paper is on highlighting the human factors issues and challenges, in terms of wearability and technology acceptance, while elaborating on some qualitative aspects of the pedagogical effectiveness of the instructional medium that AR technology offers for this group of learners.

The structural degradation and lamellar to rod transition in the Bi-Cd eutectic during unidirectional growth

The Bi-Cd eutectic system is a prototype quasi-regular eutectic in which the bismuth-rich phase has a volume fraction of 57%. It shows a high degree of regularity but, clearly, is not a normal (regular) eutectic. Microstructural observations of unidirectionally-grown specimens show that the minor cadmium-rich phase degrades at small temperature gradients and small growth rates. However, the structural refinement resulting from rapid freezing or chemical addition is found to be analogous to that of the F/NF eutectics. A lamellar rod transition has been achieved at intermediate growth rates by adding 2.0 wt % Sn as a modifier to the eutectic alloy. However, this was accompanied by the bismuth phase showing cellular facets of the solid-liquid interface.Nomenclature G _L temperature gradient in the melt ahead of the solid/liquid interface (° C cm^–1) - G _S temperature gradient in the solid behind the solid-liquid interface (° C cm^–1) - R growth rate of solid (cm sec^–1) - S cooling rate (° C sec^–1, ° C h^–1) - K _S thermal conductivity in the solid (W m^–1 K^–1) - K _L thermal conductivity in the melt (W m^–1 K^–1) - L latent heat of fusion (J mol^–1) - T temperature difference, undercooling (° C) - K ₁ constant in Equation 2 - K ₂ constant in Equation 3 - D diffusion coefficient of solute in solid (m² sec^–1) - C solubility in solid (wt %, at %) - M molecular weight (g mol^–1) - density (g cm^–3) - interfacial energy, surface tension (J mm^–2) - R gas constant, 8.314J mol^–1 K^–1 - r radius of curvature (m) - T temperature (K) - t time (sec) - F faceted - NF non-faceted     

Activation of Manganese Ions in Lithium-ion Battery Anode Materials via Nickel and Cobalt Doping

Nanosized Ni_xMn_3?xO_z(x?=?0, 0.25, 0.50, 0.65, 0.75 and 1.0) and (1?y)Li₂MnO₃???(y)LiCoO₂ (y?=?0, 0.1, 0.25, 0.50 and 1.0) powders were synthesized by the Pechini process and electrochemically evaluated as battery anode materials for their lithium capacities and cycle life. The materials were investigated using x-ray diffraction (XRD), a scanning electron microscope (SEM) and electrochemical characterizations. Undoped anode materials (i.e., Mn₂O₃ when x?=?0 and Li₂MnO₃ when y?=?0) had the lowest first cycle Coulombic efficiencies and long-term cycling capacities. However, upon addition of Ni or Co elements, drastic improvements in battery performance was observed. The highest percentages of increase in first cycle performance were observed at an intermediate level of doping (i.e., x?=?0.25 or 0.50 and y?=?0.1 or 0.25). For extended cycling, on the other hand, anode materials with higher levels of nickel and cobalt doping are the best.     

The optimization of the surface roughness in the process of tangential turn-milling using genetic algorithm

Turn-milling is a relatively new process in manufacturing technology, where both the workpiece and the tool are given a rotary movement simultaneously. This paper presents an approach for optimization of cutting parameters at cylindrical workpieces leading to minimum surface roughness by using genetic algorithm in the tangential turn-milling process. During testing, the effects of the cutting parameters on the surface roughness were investigated. Additionally, by using genetic algorithms for each of the cutting parameters (depth of cut, workpiece speed, tool speed and feed rate) minimum surface roughness for the process of tangential turn-milling was determined according to the cutting parameters.     

Laser conservation of art

Focusing a laser on the dirt covering a precious work of art may seem like a dangerous thing to do, but this unexpected technique has found a variety of cleaning applications. Analogies from other fields of materials science can provide guidance for its use, and model experiments ensure it doesn't all end in disaster.     

Sepiolite as an Alternative Liner Material in Municipal Solid Waste Landfills

Compacted clay has traditionally been used as a lining material in municipal solid waste landfills. However, natural clays may not always provide good contaminant sorption properties. One alternative material that is abundant in some parts of Europe and Turkey as well as Western United States is sepiolite. A laboratory study was undertaken to investigate the feasibility of sepiolite as a liner material. Two clays, one rich in sepiolite and the other one rich in kaolinite mineral, as well as their mixtures were subjected to geomechanical, hydraulic, and environmental tests. The same soils were also subjected to strength and hydraulic conductivity tests after a series of freeze and thaw cycles. The results of the study indicated that relatively high hydraulic conductivity and shrinkage capacity of sepiolite necessitates addition of kaolinite before being used as a landfill material. The valence of the salt solutions affected the swell and hydraulic conductivity characteristics of the clays tested. Retardation factors for sepiolite for metal solutions are 1.2–2.2 times higher than those calculated for the clay that is rich in kaolinite, and the inorganic contaminant adsorption capacity of the clay can be improved by addition of sepiolite. The results indicated that the clay mixtures utilized in this study provide good geomechanical, hydraulic, and metal adsorption properties which may justify their potential use as a liner material in solid waste landfills.     

CAIMAN: An online algorithm repository for Cancer Image Analysis

CAIMAN (CAncer IMage ANalysis: http://www.caiman.org.uk) is an online algorithm repository that provides specifically designed algorithms to analyse the images produced by experiments relevant to Cancer Research and Life Sciences, especially vascular biology. CAIMAN is accessed through a user-friendly website where researchers can upload their images and the results are returned by email. CAIMAN does not intend to replace more sophisticated software solutions such as ImageJ, Matlab, or commercial packages, but it will provide a first stop where any researcher can upload images and can obtain quantitative results without having to do any programming at all.     

Improved reconfigurability and noise margins in threshold logic gates via back-gate biasing in DG-MOSFETs

We present a compact and error tolerant implementation of reconfigurable threshold logic gates (TLG) based on nanoscale DG-MOSFET transistors. The use of independently driven double-gate (IDDG) MOSFETs to build a TLG leads not only to fine-grain reconfigurability by way of voltage-adjustable threshold level (T), but also allows one to vary input weights (w _i ) or reduce number of inputs (x _i ), depending on the design preferences. Operation of the proposed TLG circuits is verified using UFDG SPICE model, and design trade-offs in terms of size, functionality and performance are also indicated. We show that IDDG MOSFETs lead to more efficient and compact TLG circuits that have better design latitude and noise immunity than the conventional counterparts, while also improving the overall reconfigurability. When the back-gate dynamic threshold adjustment afforded by the ultra-thin (<10 nm) DG-MOSFETs on SOI substrates is properly understood and utilized, similar to the floating-gate logic architectures, it can be effectively harnessed to create reconfigurability beyond T and can simplify TLG circuit design.     

Finding optimum route of electrical energy transmission line using multi-criteria with Q-learning

Due to an increasing energy requirement the consideration of route determination is becoming important. The aim of this project is to find an optimum result considering its important criteria. Finding an optimum route is a complex problem. It does not mean the shortest path to the problem. It is important to find the best way under the criterion that is determined by experts. Because of this we did not use the classical shortest path algorithm and we applied one of algorithms of the Artificial Intelligence. In this work, Geographic Information System (GIS)-based energy transmission route planning had been performed. In this optimization, using Multiagent Systems (MAS) which is a subdirectory of Distributed Artificial Intelligence the multi-criteria affecting energy transmission line (ETL) had been severally analyzed. The application had been actualized on the Selcuk University Campus Area. Therefore, the digital map of the campus area particularly had been composed containing of relevant criteria. Using Q- learning Algorithm of Multiagent System the optimum route had been determined.     

Experimental investigation of cutting parameters in machining of 100Cr6 with tangential turn-milling method

The turn-milling methods for machining operation have been developed to increase efficiency of conventional machines recently. These methods are used especially by coupling some apparatuses on the computer numerical control (CNC) machine to decrease the production time and machine costs, ensure the maximum production and increase the quality of machining. In this study, 100Cr6 bearing steel extensively used in industry has been machined by tangential turn-milling method. This paper presents an approach for optimization of the effects of the cutting parameters including cutter speed, workpiece speed, axial feed rate, and depth of cut on the surface roughness in the machining of 100Cr6 steel with tangential turn-milling method by using genetic algorithm (GA). Tangential turning-milling method has been determined to have optimum effects of cutting parameters on the machining of 100Cr6 steel. The experimental results show that the surface roughness quality is close to that of grinding process.