Rate Allocation for Noncollaborative Multiuser Speech Communication Systems Based on Bargaining Theory

We propose a novel rate allocation algorithm for multiuser speech communication systems based on bargaining theory. Specifically, we apply the generalized Kalai-Smorodinsky bargaining solution since it allows varying bargaining powers to match the dynamic nature of speech signals. We propose a novel method to derive bargaining powers based on the short-time energy of the input speech signals, and subsequently allocate rates accordingly to the users. An important merit of the proposed framework is that it is general and can be applicable for resource allocation across a variety of multirate speech coders, and it is robust to a variety of speech quality metrics. The proposed system is also shown to involve a quick and low-complexity training process. We generalize the algorithm to scenarios in which users have unequally weighted priorities. These scenarios might arise in emergency situations, in which certain users are more important than others. The proposed rate allocation system is shown to increase the utility measures for both the Itakura and segmental signal-to-noise ratio (SNR) functions relative to the baseline system that performs uniform rate allocation. Additionally, although the instantaneous bitrate resolution of the speech encoder is not changed, the proposed system is shown to increase the short-time average bitrate resolution, and therefore provides a greater number of operational rate modes for the network     

Supply Chain Management in Food Chains: Improving Performance by Reducing Uncertainty

This paper investigates the impact of Supply Chain Management on logistical performance indicators in food supply chains. From a review of quantitative and more qualitative managerial literature, we believe that Supply Chain Management should be concerned with the reduction or even elimination of uncertainties to improve the performance of the chain. The following clusters of sources of uncertainty are identified: order forecast horizon, input data, administrative and decision processes and inherent uncertainties. For each source of uncertainty, several improvement principles are identified. A case study was conducted in a food chain in which a simulation model helped quantify the effects of alternative configurations and operational management concepts. By comparing this simulation study with a pilot study, the model is validated against real data, and organisational consequences are identified. The results of the case study suggest that reduction of uncertainties can improve service levels significantly, although current supply chain configurations restrict possible benefits. The availability of real-time information systems is found to be a requirement for obtaining efficient and effective Supply Chain Management concepts.     

Infiltration of Water into Soil with Cracks

This paper presents the physical basis of the FRACTURE submodel for simulating infiltration of precipitation∕irrigation water into relatively dry, cracked, fine-textured soils. The FRACTURE submodel forms part of the HYDRUS-ET variably saturated flow∕transport model. Infiltration into the soil matrix is formally divided into two components: (1) Vertical infiltration through the soil surface; and (2) lateral infiltration via soil cracks. The first component is described and solved using the 1D Richards' equation. Excess water that does not infiltrate through the soil surface is either considered to be runoff, if no soil cracks are present, or routed into soil cracks from where it may laterally infiltrate into the soil matrix. Horizontal infiltration from soil cracks into the soil matrix is calculated using the Green-Ampt approach and incorporated as a positive source∕sink term Sf in the Richards' equation describing flow in the matrix. In addition to the hydraulic properties of the soil matrix, the FRACTURE submodel requires parameters characterizing the soil cracks, notably the specific crack length per surface area lc and the relationship between crack porosity Pc and the gravimetric soil water content w. An example problem shows that infiltration from soil cracks can be an important process affecting the soil water regime of cracked soils. A comparison with the more traditional approach, involving surface infiltration only, indicates important differences in the soil water content distribution during a rainfall∕irrigation event. This extension of the classical approach to include crack infiltration significantly improves the identification and prediction of the soil water regime.     

User-centric query refinement and processing using granularity-based strategies

Under the context of large-scale scientific literatures, this paper provides a user-centric approach for refining and processing incomplete or vague query based on cognitive- and granularity-based strategies. From the viewpoints of user interests retention and granular information processing, we examine various strategies for user-centric unification of search and reasoning. Inspired by the basic level for human problem-solving in cognitive science, we refine a query based on retained user interests. We bring the multi-level, multi-perspective strategies from human problem-solving to large-scale search and reasoning. The power/exponential law-based interests retention modeling, network statistics–based data selection, and ontology-supervised hierarchical reasoning are developed to implement these strategies. As an illustration, we investigate some case studies based on a large-scale scientific literature dataset, DBLP. The experimental results show that the proposed strategies are potentially effective.     

Viscous Open Data: The Roles of Intermediaries in an Open Data Ecosystem

Open data have the potential to improve the governance of universities as public institutions. In addition, open data are likely to increase the quality, efficacy and efficiency of the research and analysis of higher education systems by providing a shared empirical base for critical interrogation and reinterpretation. Drawing on research conducted by the Emerging Impacts of Open Data in Developing Countries project, and using an ecosystems approach, this research paper considers the supply, demand and use of open data as well as the roles of intermediaries in the governance of South African public higher education. It shows that government's higher education database is a closed and isolated data source in the data ecosystem; and that the open data that are made available by government is inaccessible and rarely used. In contrast, government data made available by data intermediaries in the ecosystem are being used by key stakeholders. Intermediaries are found to play several important roles in the ecosystem: (i) they increase the accessibility and utility of data; (ii) they may assume the role of a “keystone species” in a data ecosystem; and (iii) they have the potential to democratize the impacts and use of open data. The article concludes that despite poor data provision by government, the public university governance open data ecosystem has evolved because intermediaries in the ecosystem have reduced the viscosity of government data. Further increasing the fluidity of government open data will improve access and ensure the sustainability of open data supply in the ecosystem.     

Development of a Cloud Trust Label: A Delphi Approach

The purpose of this research is to identify the potential information components of an online, real-time trust label, which is proposed as a communication mechanism to encourage trust in cloud service providers and cloud computing products. An online Delphi process was used with 28 cloud computing experts (including vendors, software providers, and legal and business representatives). The proposed label contains 81 information components, covering the cloud service provider (e.g. physical location, legal jurisdiction), the cloud service itself (e.g. data location, security, backup, certification), and a historical service-level summary (e.g. uptime data, support response times). The potential benefits of such a label to encourage trustworthiness perceptions and trust behaviors in the cloud computing environment are explored. Limitations of the study are highlighted, and further research studies are suggested to test the concept of the label and to refine the components of the label itself.     

Using column generation to solve parallel machine scheduling problems with minmax objective functions

In this paper we consider the parallel machine scheduling problem of minimizing an objective function of the minmax type, like maximum lateness, subject to release dates, deadlines, and/or generalized precedence constraints. We use a destructive strategy to compute a lower bound. Here we test the feasibility of a decision problem by applying column generation to compute a bound on the number of machines that we need to feasibly accommodate all jobs. After having derived the lower bound, we try to find a matching upper bound by identifying a feasible schedule with objective function value equal to this lower bound. Our computational results show that our lower bound is so strong that this is almost always possible. We are able to solve problems with up to 160 jobs and 10 machines in 10 minutes on average.     

Validation of plant part measurements using a 3D reconstruction method suitable for high-throughput seedling phenotyping

In plant phenotyping, there is a demand for high-throughput, non-destructive systems that can accurately analyse various plant traits by measuring features such as plant volume, leaf area, and stem length. Existing vision-based systems either focus on speed using 2D imaging, which is consequently inaccurate, or on accuracy using time-consuming 3D methods. In this paper, we present a computer-vision system for seedling phenotyping that combines best of both approaches by utilizing a fast three-dimensional (3D) reconstruction method. We developed image processing methods for the identification and segmentation of plant organs (stem and leaf) from the 3D plant model. Various measurements of plant features such as plant volume, leaf area, and stem length are estimated based on these plant segments. We evaluate the accuracy of our system by comparing the measurements of our methods with ground truth measurements obtained destructively by hand. The results indicate that the proposed system is very promising.     

A conservative pressure-correction method for flow at all speeds

A new fully conservative Mach-uniform staggered scheme is discussed. With this scheme one can compute flow with a Mach number ranging from the incompressible limit M↓0 up to supersonic flow M>1, with nearly uniform efficiency and accuracy. Earlier methods are based on a nonconservative discretisation of the energy equation. This results in small discrepancies in the computed shock speed for the Euler equations. The new method has similar Mach-uniform properties as the earlier methods, but is found to converge to the correct weak solution.