Drivers of change in agricultural water productivity and its improvement at basin scale in developing economies

We approach the issue of water productivity in agriculture by identifying five sets of drivers of change. We find that irrigation efficiencies at the field level can result in real water savings under certain conditions, but that small farmers in most of South Asia and Africa have little incentive to adopt the appropriate measures. Although water productivity improvement and water savings at the regional level are possible through a shift to economically efficient crops, such changes may be constrained by concerns with respect to domestic and regional food security, rural employment, and farming system resilience.     

Concept-based near-duplicate video clip detection for novelty re-ranking of web video search results

State-of-the-art near-duplicate video clip (NDVC) detection for novelty re-ranking uses non-semantic low-level features (color/texture) to detect and eliminate “content-based NDVC” and increases content level novelty in the top results. However, humans may perceive a video as near duplicate from a semantic perspective as well. In this paper, we propose concept-based near-duplicate video clip (CBNDVC) detection technique for novelty re-ranking. We identify “semantic NDVC”, making use of the semantic features (events/concepts) and re-rank the top results to increase the content as well as semantic novelty. Videos are represented as a multivariate time series of confidence values of relevant concepts and thereafter discovery of CBNDVC clusters is achieved by conceptual clustering. Obtained results show higher precision and recall from the user’s perspective.     

Grounded discovery of symbols as concept–language pairs

In human designer usage, symbols have a rich semantics, grounded on experience, which permits flexible usage — e.g. design ideation is improved by meanings triggered by contrastive words. In computational usage however, symbols are syntactic tokens whose semantics is mostly left to the implementation, resulting in brittle failures in many knowledge-based systems. Here we ask if one may define symbols in computational design as {label,meaning} pairs, as opposed to merely the label. We consider three questions that must be answered to bootstrap a symbol learning process: (a) which concepts are most relevant in a given domain, (b) how to define the semantics of such symbols, and (c) how to learn labels for these so as to form a grounded symbol. We propose that relevant symbols may be discovered by learning patterns of functional viability. The stable patterns are information-conserving codes, also called chunks in cognitive science, which relate to the process of acquiring expertise in humans. Regions of a design space that contain functionally superior designs can be mapped to a lower-dimensional manifold; the inter-relations of the design variables discovered thus constitute the chunks. Using these as the initial semantics for symbols, we show how the system can acquire labels for them by communicating with human designers. We demonstrate the first steps in this process in our baby designer approach, by learning two early grounded symbols, tight and loose.     

Thermal, mechanical and vibration characteristics of epoxy-clay nanocomposites

Diglycidyl ether of bisphenol-A (DGEBA) epoxy resin system filled individually with organoclay (OC) and unmodified clay (UC) were synthesized by mechanical shear mixing with the addition of diamino-diphenylmethane (DDM) hardener. The unmodified clay used was Na⁺-Montmorillonite (MMT) and the organoclay was alkyl ammonium treated MMT clay. The reinforcement effect of OC and UC in the epoxy polymer on thermal, mechanical and vibration properties were studied. X-ray diffraction (XRD) and Transmission electron microscopy (TEM) were used to study the structure and morphology of nanocomposites. Curing study shows that the addition of OC in epoxy resin aids the polymerization by catalytic effect, and UC addition does not show any effect in the curing behavior of epoxy polymer. Thermogravimetry analysis (TGA) shows enhanced thermal stability for epoxy with OC fillers than that of epoxy with UC fillers. The epoxy with OC fillers shows considerable improvement on tensile and impact properties over pure epoxy polymer and epoxy with UC fillers. The improvement in tensile and impact properties of nanocomposites is supported with the fracture surface studies. Epoxy with OC fillers shows enhanced vibration characteristics than that of the pure epoxy polymer and epoxy with UC fillers.     

Effect of fiber orientation on the structural behavior of FRP wrapped concrete cylinders

In this study, 27 concrete cylinders with a diameter of 152.4 and a height of 304.8 mm were prepared. Among them, 18 cylinders were wrapped using two layers of fiber reinforced polymer (FRP) with six fiber orientations; six cylinders were wrapped using four layers of FRP with fibers in axial or hoop direction only; the remaining three cylinders were used as control. The FRP used was E-glass fiber reinforced ultraviolet (UV) curing vinyl ester. Fifteen coupon specimens were prepared to experimentally determine the tensile strength of the FRP with fibers oriented at 0°, 45°, and 90° from the loading direction. Co-axial compression tests were conducted on the wrapped cylinders and control cylinders. The test results were compared with existing confinement models. It is found that the strength, ductility, and failure mode of FRP wrapped concrete cylinders depend on the fiber orientation and wall thickness. Fibers oriented at a certain angle in between the hoop direction and axial direction may result in strength lower than fibers along hoop or axial direction. A larger database is desired in order to refine the existing design-oriented confinement models.     

Enablers That Help Foreign Architectural, Engineering, and Construction Firms Win Construction Contracts in China

With China’s fast economic growth and entry into the World Trade Organization (WTO), more foreign architectural, engineering, and construction (AEC) firms are expected to venture into this huge and attractive market. This paper explores the important strategies to help foreign AEC firms clinch construction projects in China. Using a questionnaire survey approach complemented by in-depth interviews, it was found that firms need to pay more attention to the market and working conditions in China and to strengthen their own capabilities. To win projects in China, foreign AEC firms should also be able to offer project financing services. The findings are useful to foreign AEC firms because it may help them win projects in the Chinese construction industry.     

Interpretation of Temperature-Dependent Resistivity of La–Pb–MnO3: Role of Electron–Phonon Interaction

The present paper deals with the theoretical investigation of temperature-dependent resistivity of the perovskite manganites La_0.78Pb_0.22MnO_3-δ within the framework of the classical electron–phonon model of resistivity, i.e., the Bloch–Gruneisen model. Due to inherent acoustic (low-frequency) phonons (ω_ac) as well as high-frequency optical phonons (ω_op), the contributions to the electron–phonon resistivity have first been estimated. At low temperatures the acoustic phonons of the oxygen-breathing mode yield a relatively larger contribution to the resistivity as compared to the contribution of optical phonons. Furthermore, the nature of phonons changes around T = 215 K exhibiting a crossover from an acoustic to optical phonon regime with elevated temperature. The contribution to resistivity estimated by considering both phonons, i.e., ω_ac and ω_op, when subtracted from experimental data, infers a T^4.5 temperature dependence over most of the temperature range. Deduced T^4.5 temperature dependence of ρ_diff = [ρ_exp − {ρ₀ + ρ_e-ph( = ρ_ac + ρ_op)}] is justified in terms of electron–magnon scattering within the double exchange (DE) process. Within the proposed scheme, the present numerical analysis of temperature dependent resistivity shows similar results as those revealed by experiments     

Video arrays for real-time tracking of person,head, and face in an intelligent room

Real-time three-dimensional tracking of people is an important requirement for a growing number of applications. In this paper we describe two trackers; both of them use a network of video cameras for person tracking. These trackers are called a rectilinear video array tracker (R-VAT) and an omnidirectional video array tracker (O-VAT), indicating the two different ways of video capture. The specific objectives of this paper are twofold: (i) to present a systematic comparison of these two trackers using an extensive series of experiments conducted in an `intelligent' room; (ii) to develop a real-time system for tracking the head and face of a person, as an extension of the O-VAT approach. The comparative research indicates that O-VAT is more robust to the number of people, less complex and runs faster, needs manual camera calibration, and the integrated omnidirectional video network has better reconfigurability. The person head and face tracker study shows that such a system can serve as a most effective input stage for face recognition and facial expression analysis modules.     

Robust Algorithms for Object Localization

Model-based localization, the task of estimating an object's pose from sensed and corresponding model features, is a fundamental task in machine vision. Exact constant time localization algorithms have been developed for the case where the sensed features and the model features are the same type. Still, it is not uncommon for the sensed features and the model features to be of different types, i.e., sensed data points may correspond to model faces or edges. Previous localization approaches have handled different model and sensed features of different types via sampling and synthesizing virtual features to reduce the problem of matching features of dissimilar types to the problem of matching features of similar types. Unfortunately, these approaches may be suboptimal because they introduce artificial errors. Other localization approaches have reformulated object localization as a nonlinear least squares problem where the error is between the sensed data and model features in image coordinates (the Euclidean image error metric). Unfortunately, all of the previous approaches which minimized the Euclidean image error metric relied on gradient descent methods to find the global minima, and gradient descent methods may suffer from problems of local minima. In this paper, we describe an exact, efficient solution to the nonlinear least squares minimization problem based upon resultants, linear algebra, and numerical techniques. On a SPARC 20, our localization algorithm runs in a few microseconds for rectilinear polygonal models, a few milliseconds for generic polygonal models, and one second for generalized polygonal models (models composed of linear edges and circular arcs).