Barriers to Subcontracted Labor Productivity in Urban Development Projects: An On-site Project Management Perspective

Considering the confined and complex nature of urban construction projects, labor productivity is one of the key factors attributing to project success. With the proliferation of sub-contracted labor, there is a necessity to consider the ramifications of this practice to the sector. This research aims to outline how project managers can optimise productivity levels of sub-contracted labor in urban construction projects, by addressing the barriers that most restrict these efficiency levels. A qualitative research approach is employed, incorporating semi-structured interviews based on three case studies from an urban context. The results are scrutinised using mind mapping software and accompanying analytical techniques. The findings from this research indicate that the effective on-site management of sub-contracted labor has a significant impact on the degree of success of an urban development project. The two core barriers to sub-contracted labor productivity are; 1) ineffective supervision of sub-contracted labor, and 2) lack of skilled sub-contracted labor. The implication of this research is that on-site project management play an integral role in the level of productivity achieved by sub-contracted labor in urban development projects. Therefore, on-site management situated in urban, confined construction sites, are encouraged to take heed of the findings herein and address the barriers documented. The value of this research is obtained through consideration of the critical factors; construction management professionals can mitigate such barriers, in order to optimise subcontracted labor productivity on-site.

The Day After Tomorrow: Transition Management, Spatial Planning & the Low Carbon Economy

Many of the societal challenges that current spatial planning practice claims to be addressing (climate change, peak oil, obesity, aging society etc) encompass issues and timescales that lie beyond the traditional scope planning policy (Campbell 2006). The example of achieving a low carbon economy typifies this in that it demands a process of society-wide transition, involving steering a wide range of factors (markets, infrastructure, governance, individual behaviour etc). Such a process offers a challenge to traditional approaches to planning as they cannot be guided by a fixed blueprint, given the timescales involved (up to 50 years) and an enhanced level of uncertainty, social resistance, lack of control over implementation and a danger of ‘policy lock in’ (Kemp et al 2007). One approach to responding to these challenges is the concept of transition management which has emerged from studies of science, technology and innovation (Geels 2002, Markard et al 2012). Although not without criticism, this perspective attempts to uncertainty and complexity encompassing long term visions that integrates multi-level, multi-actor and multi-domain perspectives (Rotmans et al 2001).
 
Given its origins, research on transition management has tended to neglect spatial contexts (Coenen et al 2012) and, related to this, it’s relationship with spatial planning is poorly understood. Using the example of the low carbon transition, this paper will review the relationships between the concepts, methodologies and goals of transition management and spatial planning to explore whether a closer integration of the two fields offers benefits to achieving the long term challenges facing society.
 

HpMC: An Energy- Aware Management System for Multi-Level Memory Architectures

DRAM technology faces density and power challenges to increase capacity because of limitations of physical cell design. To overcome these limitations, system designers are exploring alternative solutions that combine DRAM and emerging NVRAM technologies. Previous work on heterogeneous memories focuses, mainly, on two system designs: PCache, a hierarchical, inclusive memory system, and HRank, a flat, non-inclusive memory system. We demonstrate that neither of these designs can universally achieve high performance and energy efficiency across a suite of HPC workloads. In this work, we investigate the impact of a number of multilevel memory designs on the performance, power, and energy consumption of applications. To achieve this goal and overcome the limited number of available tools to study heterogeneous memories, we created HMsim, an infrastructure that enables n-level, heterogeneous memory studies by leveraging existing memory simulators. We, then, propose HpMC, a new memory controller design that combines the best aspects of existing management policies to improve performance and energy. Our energy-aware memory management system dynamically switches between PCache and HRank based on the temporal locality of applications. Our results show that HpMC reduces energy consumption from 13% to 45% compared to PCache and HRank, while providing the same bandwidth and higher capacity than a conventional DRAM system.

Evolving techniques for characterising and monitoring the stability of infrastructure slopes

Landslides and debris flows, commonly triggered by rainfall, pose a geotechnical risk causing disruption to transport routes and incur significant financial expenditure. With infrastructure maintenance budgets becoming ever more constrained, this paper provides an overview of some of the developing methods being implemented by Queen’s University, Belfast in collaboration with the Department for Regional Development to monitor the stability of two distinctly different infrastructure slopes in Northern Ireland. In addition to the traditional, intrusive ground investigative and laboratory testing methods, aerial LiDAR, terrestrial LiDAR, geophysical techniques and differential Global Positioning Systems have been used to monitor slope stability. Finally, a comparison between terrestrial LiDAR, pore water pressure and soil moisture deficit (SMD) is presented to outline the processes for a more informed management regime and to highlight the season relationship between landslide activity and the aforementioned parameters.

A Scheme Design of Cloud + End Technology in Demand Side Management

Demand Side Management (DSM) plays an important role in Smart Grid. It has large scale access points, massive users, heterogeneous infrastructure and dispersive participants. Moreover, cloud computing which is a service model is characterized by resource on-demand, high reliability and large scale integration and so on and the game theory is a useful tool to the dynamic economic phenomena. In this study, a scheme design of cloud + end technology is proposed to solve technical and economic problems of the DSM. The architecture of cloud + end is designed to solve technical problems in the DSM. In particular, a construct model of cloud + end is presented to solve economic problems in the DSM based on game theories. The proposed method is tested on a DSM cloud + end public service system construction in a city of southern China. The results demonstrate the feasibility of these integrated solutions which can provide a reference for the popularization and application of the DSM in china.

A Configurable Packet Classification Architecture for Software-Defined Networking

Network management tools must be able to monitor and analyze traffic flowing through network systems. According to the OpenFlow protocol applied in Software-Defined Networking (SDN), packets are classified into flows that are searched in flow tables. Further actions, such as packet forwarding, modification, and redirection to a group table, are made in the flow table with respect to the search results. A novel hardware solution for SDN-enabled packet classification is presented in this paper. The proposed scheme is focused on a label-based search method, achieving high flexibility in memory usage. The implemented hardware architecture provides optimal lookup performance by configuring the search algorithm and by performing fast incremental update as programmed the software controller.

LS-ADT: Lightweight and Scalable Anomaly Detection for Cloud Datacentres

Cloud data centres are implemented as large-scale clusters with demanding requirements for service performance, availability and cost of operation. As a result of scale and complexity, data centres typically exhibit large numbers of system anomalies resulting from operator error, resource over/under provisioning, hardware or software failures and security issus anomalies are inherently difficult to identify and resolve promptly via human inspection. Therefore, it is vital in a cloud system to have automatic system monitoring that detects potential anomalies and identifies their source. In this paper we present a lightweight anomaly detection tool for Cloud data centres which combines extended log analysis and rigorous correlation of system metrics, implemented by an efficient correlation algorithm which does not require training or complex infrastructure set up. The LADT algorithm is based on the premise that there is a strong correlation between node level and VM level metrics in a cloud system. This correlation will drop significantly in the event of any performance anomaly at the node-level and a continuous drop in the correlation can indicate the presence of a true anomaly in the node. The log analysis of LADT assists in determining whether the correlation drop could be caused by naturally occurring cloud management activity such as VM migration, creation, suspension, termination or resizing. In this way, any potential anomaly alerts are reasoned about to prevent false positives that could be caused by the cloud operator’s activity. We demonstrate LADT with log analysis in a Cloud environment to show how the log analysis is combined with the correlation of systems metrics to achieve accurate anomaly detection.

Project Management within an Urban Site Context: Issues considering External Stakeholders

Large construction projects create numerous hazards, making it one of the most dangerous industries in which to work. This element of risk increases in urban areas and can have a negative impact on the external stakeholders associated with the project, along with their surrounding environments. The aim of this paper is to identify and document, in an urban context, the numerous issues encountered by on-site project managers from external stakeholders and how they affect a construction project. In addressing this aim, the core objective is to identify what issues are involved in the management of these stakeholders. In order to meet this requirement, a qualitative methodology encompassing an informative literature review followed by five individual case study interviews. The data gathered is assessed qualitatively using mind mapping software. A number of issues are identified which have an impact on the external stakeholders involved, and also how they affected proceedings on site. Collectively the most commonly occurring issues are environmental, legal, health and safety and communication issues. These ranged from road closures and traffic disruption to noise, dust and vibrations from site works. It is anticipated that the results of this study will assist and aid project managers in identifying issues considering external stakeholders, particularly on urban construction projects. A wide range of issues can develop depending on the complexity and nature of each project, but this research will illustrate and reinforce to project managers, that identifying issues early, effective communication and appropriate liaising can be used to manage the issues considering external stakeholders.