Computer aided manual tracking

A scheme was developed to assist the human operator by augmenting an optic sight manual tracking loop with target rate estimates from a computer control algorithm which can either be a Kalman Filter or an alpha, beta, gamma filter. The idea is for the computer to provide rate tracking while the human operator is responsible for nullifying the tracking error. A simple schematic is shown to illustrate the implementation of this concept. A hybrid real-time man-in-loop simulation was used to compare the tracking performance of the same flight trajectory with or without this form of computer-aided track. Preliminary results show the advantage of computer-aided track against high speed aircraft at close range. However, good tracking before target state estimator maturity becomes more critical for aided track than without. Results are presented for a constant velocity flight trajectory

The development of absorptive capacity-based innovation in a construction SME

Traditionally, construction has been a transaction-oriented industry. However, it is changing from the design-bid-build process into a business based on innovation capability and performance management, in which contracts are awarded on the basis of factors such as knowledge, intellectual capital and skills. This change presents a challenge to construction-sector SMEs with scarce resources, which must find ways to innovate based on those attributes to ensure their future competitiveness. This paper explores how dynamic capability, using an absorptive capacity framework in response to these challenges, has been developed in a construction-based SME. The paper also contributes to the literature on absorptive capacity and innovation by showing how the construct can be operationalized within an organization. The company studied formed a Knowledge Transfer Partnership using action research over a two-year period with a local university. The aim was to increase its absorptive capacity and hence its ability to meet the changing market challenges. The findings show that absorptive capacity can be operationalized into a change management approach for improving capability-based competitiveness. Moreover, it is important for absorptive capacity constructs and language to be contextualized within a given organizational setting (as in the case of the construction-based SME in the present study)

Quantum walks: the first detected transition time

We consider the quantum first detection problem for a particle evolving on a graph under repeated projective measurements with fixed rate $1/\tau$. A general formula for the mean first detected transition time is obtained for a quantum walk in a finite-dimensional Hilbert space where the initial state $|\psi_{\rm in}\rangle$ of the walker is orthogonal to the detected state $|\psi_{\rm d}\rangle$. We focus on diverging mean transition times, where the total detection probability exhibits a discontinuous drop of its value, by mapping the problem onto a theory of fields of classical charges located on the unit disk. Close to the critical parameter of the model, which exhibits a blow-up of the mean transition time, we get simple expressions for the mean transition time. Using previous results on the fluctuations of the return time, corresponding to $|\psi_{\rm in}\rangle = |\psi_{\rm d}\rangle$, we find close to these critical parameters that the mean transition time is proportional to the fluctuations of the return time, an expression reminiscent of the Einstein relation

RsyGAN: Generative Adversarial Network for Recommender Systems

© 2019 IEEE. Many recommender systems rely on the information of user-item interactions to generate recommendations. In real applications, the interaction matrix is usually very sparse, as a result, the model cannot be optimised stably with different initial parameters and the recommendation performance is unsatisfactory. Many works attempted to solve this problem, however, the parameters in their models may not be trained effectively due to the sparse nature of the dataset which results in a lower quality local optimum. In this paper, we propose a generative network for making user recommendations and a discriminative network to guide the training process. An adversarial training strategy is also applied to train the model. Under the guidance of a discriminative network, the generative network converges to an optimal solution and achieves better recommendation performance on a sparse dataset. We also show that the proposed method significantly improves the precision of the recommendation performance on several datasets

Detecting changes in sediment overburden using distributed temperature sensing: an experimental and numerical study

Fibre optic cables can be used as sensors to monitor temperature changes through the analysis of back scattered light. This can be linked to changes in the ambient conditions surrounding the fibre optic cable. Active distributed temperature sensing relies on an external heat source relative to the fibre optic cable to measure the properties of, and changes in, the surrounding medium. An experiment was conducted using distributed temperature sensing technology to monitor changes in sediment overburden for the purpose of determining whether scour could be measured above buried power cables containing fibre optic cables. Fibre optic cables were buried in a channel containing saturated sand and water with an external heat source. The depth of overburden sediment above the fibre optic cables was reduced, whilst the associated temperature response along the fibre optic cable was monitored. The data was matched to a finite element model so that the heat transfer taking place could be simulated and then the thermal conductivity of the soil modified to observe the potential changes in heat detected by the fibre optic cables. This paper explains the characteristics of heat transfer from an active heat source to the surrounding soil medium providing a means to translate the temperature measurement to the associated overburden thickness and to model the same response in different materials

Program Performance and Multiple Constituency Theory

This paper seeks to deepen our understanding of performance measurement in the nonprofit human services sector by investigating issues related to funder and provider motivations for collecting and analyzing program level performance information. Using survey and interview data from nonprofit human service organizations and their funders (nonprofit and local government), we analyze this study’s research questions through the lens of multiple constituency theory. Consistent with multiple constituency theory, the study found similarities and differences in funder and provider motivations for collecting performance information. The study also indicates other key constituents (such as service beneficiaries, donors to nonprofit organizations and other levels of government that provide resources to local governments) play a role in defining program performance. The paper suggests that multiple constituency theory applies to program level performance and that understanding program performance requires considering the perspectives of multiple stakeholders

Peroxi-electrocoagulation for Treatment of Trace Organic Compounds and Natural Organic Matter at Neutral pH

Iron-based oxidation technologies can be advantageous for mitigating trace organic compounds (TOrCs) during water and wastewater treatment due to their production of hydroxyl radicals. However, iron-based oxidation often occurs at acidic pH to promote Fenton\u27s reaction, which limits the processes\u27 feasibility for treatment applications. This study focused on utilizing iron-electrocoagulation (EC) paired with ex situ H2O2 addition (peroxi-electrocoagulation [EC:H2O2]) to promote oxidative reactions at neutral pH conditions. The hydroxyl radical probe para-chlorobenzoic acid (pCBA) was used to gauge oxidant activity and serve as a representative TOrC. The impact of water pH, current density, iron dose, H2O2 dose (i.e., [H2O2]initial/[Fe2+]generated ratio), and the presence of natural organic matter (NOM) were evaluated. Multivariable regressions showed that high levels of H2O2 relative to iron (i.e., [H2O2]initial/[Fe2+]generated ratio \u3e0.7) inhibited the rate of pCBA oxidation, likely due to additional radical quenching from extra H2O2. Oxidation of pCBA was confirmed at neutral pH conditions, indicating that EC:H2O2 may potentially serve as a multi-mechanistic treatment technology capable of oxidation. Experiments were also conducted in real-world water samples to gauge EC:H2O2 applications for treating groundwater, river water, and primary treated wastewater. Overall, H2O2 addition enhanced the oxidative degradation of TOrCs while still removing NOM. The one exception was the primary effluent sample, which had the highest degree of oxidant scavenging of all matrices tested. The electrical energy per order (EEO) metric demonstrated that EC:H2O2 is competitive with other TOrC oxidation technologies, with the added benefit of NOM mitigation in the same unit process

Revisiting Politics in Political CSR: How coercive and deliberative dynamics operate through institutional work in a Colombian company

This article analyses the political dynamics taking place within a Colombian supplier company during the implementation of a client’s global Corporate Social Responsibility (CSR) programme, which radically transformed the local understandings of the supplier’s social responsibilities. We distinguish two forms of politics in political CSR – coercive and deliberative politics – and examine how they unfold through lower-level managers’ institutional work. Our longitudinal case study identifies four types of institutional work, which combine into three political configurations – irreconcilable politics, complementary politics and aligned deliberative politics – resulting in the hybridization of explicit and implicit CSR. By analysing how local managers from emerging countries and at the bottom of the supply chain cope with the new political role of MNCs, we expand the political microfoundations of CSR and highlight the interactive and political nature of institutional work aimed at addressing major societal challenges