Common-sense knowledge for a computer vision system for human action recognition

This work presents a novel approach for human action recognition based on the combination of computer vision techniques and common-sense knowledge and reasoning capabilities. The emphasis of this work is on how common sense has to be leveraged to a vision-based human action recognition so that nonsensical errors can be amended at the understanding stage. The proposed framework is to be deployed in a realistic environment in which humans behave rationally, that is, motivated by an aim or a reason. © 2012 Springer-Verlag.

Introducing Automated Management Through Iteratively Increased Automation and Indicators

Introducing automation into a managed environment includes significant initial overhead and abstraction, creating a disconnect between the administrator and the system. In order to facilitate the transition to automated management, this paper proposes an approach whereby automation increases gradually, gathering data from the task deployment process. This stored data is analysed to determine the task outcome status and can then be used for comparison against future deployments of the same task and alerting the administrator to deviations from the expected outcome. Using a machinelearning
approach, the automation tool can learn from the administrator's reaction to task failures and eventually react to faults autonomously.

Prefetching and Cache Management using Task Lifetimes

Task-based dataflow programming models and runtimes emerge as promising candidates for programming multicore and manycore architectures. These programming models analyze dynamically task dependencies at runtime and schedule independent tasks concurrently to the processing elements. In such models, cache locality, which is critical for performance, becomes more challenging in the presence of fine-grain tasks, and in architectures with many simple cores.

This paper presents a combined hardware-software approach to improve cache locality and offer better performance is terms of execution time and energy in the memory system. We propose the explicit bulk prefetcher (EBP) and epoch-based cache management (ECM) to help runtimes prefetch task data and guide the replacement decisions in caches. The runtimem software can use this hardware support to expose its internal knowledge about the tasks to the architecture and achieve more efficient task-based execution. Our combined scheme outperforms HW-only prefetchers and state-of-the-art replacement policies, improves performance by an average of 17%, generates on average 26% fewer L2 misses, and consumes on average 28% less energy in the components of the memory system.

Human resource management practices in the multinational company: A test of system, societal, and dominance effects

Does the use of HRM practices by multinational companies (MNCs) reflect their national origins or are practices similar regardless of context? To the extent that practices are similar, is there any evidence of global best standards? The authors use the system, societal, and dominance framework to address these questions through analysis of 1,100 MNC subsidiaries in Canada, Ireland, Spain, and the United Kingdom. They argue that this framework offers a richer account than alternatives such as varieties of capitalism. The study moves beyond previous research by differentiating between system effects at the global level and dominance effects arising from the diffusion of practices from a dominant economy. It shows that both effects are present, as are some differences at the societal level. Results suggest that MNCs configure their HRM practices in response to all three forces rather than to some uniform global best practices or to their national institutional contexts.

Dynamic Buffer Management for Multimedia Services in Beyond 3G Wireless Networks

This paper investigates a dynamic buffer man-agement scheme for QoS control of multimedia services in be-yond 3G wireless systems. The scheme is studied in the context of the state-of-the-art 3.5G system i.e. the High Speed Downlink Packet Access (HSDPA) which enhances 3G UMTS to support high-speed packet switched services. Unlike earlier systems, UMTS-evolved systems from HSDPA and beyond incorporate mechanisms such as packet scheduling and HARQ in the base station necessitating data buffering at the air interface. This introduces a potential bottleneck to end-to-end communication. Hence, buffer management at the air interface is crucial for end-to-end QoS support of multimedia services with multi-plexed parallel diverse flows such as video and data in the same end-user session. The dynamic buffer management scheme for HSDPA multimedia sessions with aggregated real-time and non real-time flows is investigated via extensive HSDPA simulations. The impact of the scheme on end-to-end traffic performance is evaluated with an example multimedia session comprising a real-time streaming flow concurrent with TCP-based non real-time flow. Results demonstrate that the scheme can guar-antee the end-to-end QoS of the real-time streaming flow, whilst simultaneously protecting the non real-time flow from starva-tion resulting in improved end-to-end throughput performance

CoWiSMoN: A Framework for Cognitive Wireless Sensor Mobile Network System for Emergency Rescue Management

One of the crucial aspects of disaster management of emergency situations is the early assessment of needs and damages. In most disaster situations, higher fatality and increased casualty results from lack of access to timely available emergency services rather than the initial disaster itself. This is usually caused by lack of access to the affected area in order to properly assess the situation for relevant and urgent measures. Cognitive wireless sensor networks provide an opportunity to overcome this situation especially through interconnection via mobile systems. This paper presents a cognitive wireless sensor mobile networks-based framework (CoWiSMoN), designed to offer real-time emergency services to victims and rescue personnel in event of disasters. Critical issues underlying the implementation of such a system are discussed and analyzed.

Management in distributed systems: A semi-formal approach

The reverse engineering of a skeleton based programming environment and redesign to distribute management activities of the system and thereby remove a potential single point of failure is considered. The Ore notation is used to facilitate abstraction of the design and analysis of its properties. It is argued that Ore is particularly suited to this role as this type of management is essentially an orchestration activity. The Ore specification of the original version of the system is modified via a series of semi-formally justified derivation steps to obtain a specification of the decentralized management version which is then used as a basis for its implementation. Analysis of the two specifications allows qualitative prediction of the expected performance of the derived version with respect to the original, and this prediction is borne out in practice.

A RAG System for the Management Forensic and Archaeological Searches of Burial Grounds

Burial grounds are commonly surveyed and searched by both police/humanitarian search teams and archaeologists.
One aspect of an efficient search is to establish areas free of recent internments to allow the concentration of assets in suspect
terrain. While 100% surety in locating remains can never be achieved, the deployment of a red, amber green (RAG) system for
assessment has proven invaluable to our surveys. The RAG system is based on a desktop study (including burial ground
records), visual inspection (mounding, collapses) and use of geophysics (in this case, ground penetrating radar or GPR) for a
multi-proxy assessment that provides search authorities an assessment of the state of inhumations and a level of legal backup
for decisions they make on excavation or not (‘exit strategy’). The system is flexible and will be built upon as research
continues.

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.

Hierarchical energy management system for multi-source multi-product microgrids

This paper proposes a hierarchical energy management system for multi-source multi-product (MSMP) microgrids. Traditional energy hub based scheduling method is combined with a hierarchical control structure to incorporate transient characteristics of natural gas flow and dynamics of energy converters in microgrids. The hierarchical EMS includes a supervisory control layer, an optimizing control layer, and an execution control layer. In order to efficiently accommodate the systems multi time-scale characteristics, the optimizing control layer is decomposed into three sub-layers: slow, medium and fast. Thermal, gas and electrical management systems are integrated into the slow, medium, and fast control layer, respectively. Compared with wind energy, solar energy is easier to integrate and more suitable for the microgrid environment, therefore, potential impacts of the hierarchical EMS on MSMP microgrids is investigated based on a building energy system integrating photovoltaic and microturbines. Numerical studies indicate that by using a hierarchical EMS, MSMP microgrids can be economically operated. Also, interactions among thermal, gas, and electrical system can be effectively managed.

Per-Flow State Management Technique for High-Speed Networks

Flow processing is a fundamental element of stateful traffic classification and it has been recognized as an essential factor for delivering today’s application-aware network operations and security services. The basic function within a flow processing engine is to search and maintain a flow table, create new flow entries if no entry matches and associate each entry with flow states and actions for future queries. Network state information on a per-flow basis must be managed in an efficient way to enable Ethernet frame transmissions at 40 Gbit/s (Gbps) and 100 Gbps in the near future. This paper presents a hardware solution of flow state management for implementing large-scale flow tables on popular computer memories using DDR3 SDRAMs. Working with a dedicated flow lookup table at over 90 million lookups per second, the proposed system is able to manage 512-bit state information at run time.