Cost-Efficient Decimal Adder Design in Quantum-dot Cellular Automata

Applications that cannot tolerate the loss of accuracy that results from binary arithmetic demand hardware decimal arithmetic designs. Binary arithmetic in Quantum-dot cellular automata (QCA) technology has been extensively investigated in recent years. However, only limited attention has been paid to QCA decimal arithmetic. In this paper, two cost-efficient binary-coded decimal (BCD) adders are presented. One is based on the carry flow adder (CFA) using a conventional correction method. The other uses the carry look ahead (CLA) algorithm which is the first QCA CLA decimal adder proposed to date. Compared with previous designs, both decimal adders achieve better performance in terms of latency and overall cost. The proposed CFA-based BCD adder has the smallest area with the least number of cells. The proposed CLA-based BCD adder is the fastest with an increase in speed of over 60% when compared with the previous fastest decimal QCA adder. It also has the lowest overall cost with a reduction of over 90% when compared with the previous most cost-efficient design.

Empowering Human Services Organizations to Embrace Evidence-informed Practice: International Best Practices

Human service organizations are increasingly using knowledge as a mechanism for implementing change. Knowledge emerging from many sources that may include academic publications, grey literature, and service user and practitioner wisdom contributes toward informing best practice. The question is: how do we harness this knowledge to make practice more effective? This paper synthesizes the lessons learned from eight international organizations that have made a commitment to knowledge mobilization as an important priority in their mission and operation. The paper provides a conceptual model, tools and resources to help human services organizations create strategies for building, enhancing or sustaining their knowledge mobilization efforts. The paper describes a flexible blueprint for human service organizations to leverage knowledge mobilization efforts at all levels of service delivery.

Non-parametric bill of quantities estimation of concrete road bridges' superstructure: an artificial neural networks approach

Bridge construction responds to the need for environmentally friendly design of motorways and facilitates the passage through sensitive natural areas and the bypassing of urban areas. However, according to numerous research studies, bridge construction presents substantial budget overruns. Therefore, it is necessary early in the planning process for the decision makers to have reliable estimates of the final cost based on previously constructed projects. At the same time, the current European financial crisis reduces the available capital for investments and financial institutions are even less willing to finance transportation infrastructure. Consequently, it is even more necessary today to estimate the budget of high-cost construction projects -such as road bridges- with reasonable accuracy, in order for the state funds to be invested with lower risk and the projects to be designed with the highest possible efficiency. In this paper, a Bill-of-Quantities (BoQ) estimation tool for road bridges is developed in order to support the decisions made at the preliminary planning and design stages of highways. Specifically, a Feed-Forward Artificial Neural Network (ANN) with a hidden layer of 10 neurons is trained to predict the superstructure material quantities (concrete, pre-stressed steel and reinforcing steel) using the width of the deck, the adjusted length of span or cantilever and the type of the bridge as input variables. The training dataset includes actual data from 68 recently constructed concrete motorway bridges in Greece. According to the relevant metrics, the developed model captures very well the complex interrelations in the dataset and demonstrates strong generalisation capability. Furthermore, it outperforms the linear regression models developed for the same dataset. Therefore, the proposed cost estimation model stands as a useful and reliable tool for the construction industry as it enables planners to reach informed decisions for technical and economic planning of concrete bridge projects from their early implementation stages.

Memory Cost Analysis for OpenFlow Multiple Table Lookup

Multiple Table Lookup architectures in Software Defined Networking (SDN) open the door for exciting new network applications. The development of the OpenFlow protocol supported the SDN paradigm. However, the first version of the OpenFlow protocol specified a single table lookup model with the associated constraints in flow entry numbers and search capabilities. With the introduction of multiple table lookup in OpenFlow v1.1, flexible and efficient search to support SDN application innovation became possible. However, implementation of multiple table lookup in hardware to meet high performance requirements is non-trivial. One possible approach involves the use of multi-dimensional lookup algorithms. A high lookup performance can be achieved by using embedded memory for flow entry storage. A detailed study of OpenFlow flow filters for multi-dimensional lookup is presented in this paper. Based on a proposed multiple table lookup architecture, the memory consumption and update performance using parallel single field searches are evaluated. The results demonstrate an efficient multi-table lookup implementation with minimum memory usage.

Sharing services, saving money? Five risks to cost saving when organizations share administrative services

Shared services are a popular reform for governments under financial pressure. The hope is to reduce overheads and increase efficiency by providing support services like HR, finance and procurement once to multiple agencies. Drawing on insights from organization theory and political science, we identify five risks that shared services won’t live up to current expectations. We illustrate each with empirical evidence from the UK, Ireland and further afield, and conclude with suggestions on how to manage these risks.