Identifying behavioural predictors of small power electricity consumption in office buildings

It is widely accepted that there is a gap between design energy and real world operational energy consumption. The behaviour of occupants is often cited as an important factor influencing building energy performance. However, its consideration, both during design and operation, is overly simplistic, often assuming a direct link between attitudes and behaviour. Alternative models of decision making from psychology highlight a range of additional influential factors and emphasise that occupants do not always act in a rational manner. Developing a better understanding of occupant decision making could help inform office energy conservation campaigns as well as models of behaviour employed during the design process. This paper assesses the contribution of various behavioural constructs on small power consumption in offices. The method is based upon the Theory of Planned Behaviour (TPB) which assumes that intention is driven by three factors: attitude, subjective norms, and perceived behavioural control, but we also consider a fourth construct: habit measured through the Self- Report Habit Index (SRHI). A questionnaire was issued to 81 participants in two UK offices. Questionnaire results for each behavioural construct were correlated against each participant’s individual workstation electricity consumption. The intentional processes proposed by TPB could not account for the observed differences in occupants’ interactions with small power appliances. Instead, occupants were interacting with small power “automatically”, with habit accounting for 11% of the variation in workstation energy consumption. The implications for occupant behaviour models and employee engagement campaigns are discussed.

The air distribution index as an indicator for energy consumption and performance of ventilation systems

This paper deals with the energy consumption and the evaluation of the performance of air supply systems for a ventilated room involving high- and low-level supplies. The energy performance assessment is based on the airflow rate, which is related to the fan power consumption by achieving the same environmental quality performance for each case. Four different ventilation systems are considered: wall displacement ventilation, confluent jets ventilation, impinging jet ventilation and a high level mixing ventilation system. The ventilation performance of these systems will be examined by means of achieving the same Air Distribution Index (ADI) for different cases. The widely used high-level supplies require much more fan power than those for low-level supplies for achieving the same value of ADI. In addition, the supply velocity, hence the supply dynamic pressure, for a high-level supply is much larger than for low-level supplies. This further increases the power consumption for high-level supply systems. The paper considers these factors and attempts to provide some guidelines on the difference in the energy consumption associated with high and low level air supply systems. This will be useful information for designers and to the authors' knowledge there is a lack of information available in the literature on this area of room air distribution. The energy performance of the above-mentioned ventilation systems has been evaluated on the basis of the fan power consumed which is related to the airflow rate required to provide equivalent indoor environment. The Air Distribution Index (ADI) is used to evaluate the indoor environment produced in the room by the ventilation strategy being used. The results reveal that mixing ventilation requires the highest fan power and the confluent jets ventilation needs the lowest fan power in order to achieve nearly the same value of ADI.

Investigation into low power of a 2D Inverse Discrete CosineTransform (IDCT) in FPGAs

Design for low power in FPGA is rather limited since technology factors affecting power are either fixed or limited for FPGA families. This paper investigates opportunities for power savings of a pipelined 2D IDCT design at the architecture and logic level. We report power consumption savings of over 25% achieved in FPGA circuits obtained from clock gating implementation of optimizations made at the algorithmic level(1).

Power performance with gated clocks of a pipelined Cordic Core

This paper presents the evaluation in power consumption of gated clocks pipelined circuits with different register configurations in Virtex-based FPGA devices. Power impact of a gated clock circuitry aimed at reducing flip-flops output rate at the bit level is studied. Power performance is also given for pipeline stages based on the implementation of a double edge-triggered flip-flop. Using a pipelined Cordic Core circuit as an example, this study did not find evidence in power benefits either when gated clock at the bit-level or double-edge triggered flip-flops used when synthesized with FPGA logic resources.

A clocking technique with power savings in virtex-based pipelined designs

This paper presents the evaluation in power consumption of a clocking technique for pipelined designs. The technique shows a dynamic power consumption saving of around 30% over a conventional global clocking mechanism. The results were obtained from a series of experiments of a systolic circuit implemented in Virtex-II devices. The conversion from a global-clocked pipelined design to the proposed technique is straightforward, preserving the original datapath design. The savings can be used immediately either as a power reduction benefit or to increase the frequency of operation of a design for the same power consumption.

The Impact of office productivity cloud computing on energy consumption and greenhouse gas emissions

Cloud computing is usually regarded as being energy efficient and thus emitting less greenhouse gases (GHG) than traditional forms of computing. When the energy consumption of Microsoft’s cloud computing Office 365 (O365) and traditional Office 2010 (O2010) software suites were tested and modeled, some cloud services were found to consume more energy than the traditional form. The developed model in this research took into consideration the energy consumption at the three main stages of data transmission; data center, network, and end user device. Comparable products from each suite were selected and activities were defined for each product to represent a different computing type. Microsoft provided highly confidential data for the data center stage, while the networking and user device stages were measured directly. A new measurement and software apportionment approach was defined and utilized allowing the power consumption of cloud services to be directly measured for the user device stage. Results indicated that cloud computing is more energy efficient for Excel and Outlook which consumed less energy and emitted less GHG than the standalone counterpart. The power consumption of the cloud based Outlook (8%) and Excel (17%) was lower than their traditional counterparts. However, the power consumption of the cloud version of Word was 17% higher than its traditional equivalent. A third mixed access method was also measured for Word which emitted 5% more GHG than the traditional version. It is evident that cloud computing may not provide a unified way forward to reduce energy consumption and GHG. Direct conversion from the standalone package into the cloud provision platform can now consider energy and GHG emissions at the software development and cloud service design stage using the methods described in this research.

Detection of Parkinson’s disease tremor-onset with a frequency analysing artificial neural network

Deep Brain Stimulator devices are becoming widely used for therapeutic benefits in movement disorders such as Parkinson's disease. Prolonging the battery life span of such devices could dramatically reduce the risks and accumulative costs associated with surgical replacement. This paper demonstrates how an artificial neural network can be trained using pre-processing frequency analysis of deep brain electrode recordings to detect the onset of tremor in Parkinsonian patients. Implementing this solution into an 'intelligent' neurostimulator device will remove the need for continuous stimulation currently used, and open up the possibility of demand-driven stimulation. Such a methodology could potentially decrease the power consumption of a deep brain pulse generator.

Study of the variation of the input impedance of induction machines with frequency

The results of a study of the variation of three-phase induction machines' input impedance with frequency are proposed. A range of motors were analysed, both two-pole and four-pole, and the magnitude and phase of the input impedance were obtained over a wide frequency range of 20 Hz-1 MHz. For test results that would be useful in the prediction of the performance of induction machines during typical use, a test procedure was developed to represent closely typical three-phase stator coil connections when the induction machine is driven by a three-phase inverter. In addition, tests were performed with the motor's cases both grounded and not grounded. The results of the study show that all induction machines of the type considered exhibit a multiresonant impedance profile, where the input impedance reaches at least one maximum as the input frequency is increased. Furthermore, the test results show that the grounding of the motor's case has a significant effect on the impedance profile. Methods to exploit the input impedance profile of an induction machine to optimise machine and inverter systems are also discussed.

Space physics for graduate students: an activities-based approach

The geospace environment is controlled largely by events on the Sun, such as solar flares and coronal mass ejections, which generate significant geomagnetic and upper atmospheric disturbances. The study of this Sun-Earth system, which has become known as space weather, has both intrinsic scientific interest and practical applications. Adverse conditions in space can damage satellites and disrupt communications, navigation, and electric power grids, as well as endanger astronauts. The Center for Integrated Space Weather Modeling (CISM), a Science and Technology Center (STC) funded by the U.S. National Science Foundation (see http://www.bu.edu/cism/), is developing a suite of integrated physics-based computer models that describe the space environment from the Sun to the Earth for use in both research and operations [Hughes and Hudson, 2004, p. 1241]. To further this mission, advanced education and training programs sponsored by CISM encourage students to view space weather as a system that encompasses the Sun, the solar wind, the magnetosphere, and the ionosphere/thermosphere. This holds especially true for participants in the CISM space weather summer school [Simpson, 2004].

A clocking technique for FPGA pipelined designs

This paper presents a clocking pipeline technique referred to as a single-pulse pipeline (PP-Pipeline) and applies it to the problem of mapping pipelined circuits to a Field Programmable Gate Array (FPGA). A PP-pipeline replicates the operation of asynchronous micropipelined control mechanisms using synchronous-orientated logic resources commonly found in FPGA devices. Consequently, circuits with an asynchronous-like pipeline operation can be efficiently synthesized using a synchronous design methodology. The technique can be extended to include data-completion circuitry to take advantage of variable data-completion processing time in synchronous pipelined designs. It is also shown that the PP-pipeline reduces the clock tree power consumption of pipelined circuits. These potential applications are demonstrated by post-synthesis simulation of FPGA circuits. (C) 2004 Elsevier B.V. All rights reserved.

Image restoration for a rectangular poor-pixels detector

This paper presents a unique two-stage image restoration framework especially for further application of a novel rectangular poor-pixels detector, which, with properties of miniature size, light weight and low power consumption, has great value in the micro vision system. To meet the demand of fast processing, only a few measured images shifted up to subpixel level are needed to join the fusion operation, fewer than those required in traditional approaches. By maximum likelihood estimation with a least squares method, a preliminary restored image is linearly interpolated. After noise removal via Canny operator based level set evolution, the final high-quality restored image is achieved. Experimental results demonstrate effectiveness of the proposed framework. It is a sensible step towards subsequent image understanding and object identification.

Methodology To model the energy and greenhouse gas emissions of electronic software distributions

A new electronic software distribution (ESD) life cycle analysis (LCA)methodology and model structure were constructed to calculate energy consumption and greenhouse gas (GHG) emissions. In order to counteract the use of high level, top-down modeling efforts, and to increase result accuracy, a focus upon device details and data routes was taken. In order to compare ESD to a relevant physical distribution alternative,physical model boundaries and variables were described. The methodology was compiled from the analysis and operational data of a major online store which provides ESD and physical distribution options. The ESD method included the calculation of power consumption of data center server and networking devices. An in-depth method to calculate server efficiency and utilization was also included to account for virtualization and server efficiency features. Internet transfer power consumption was analyzed taking into account the number of data hops and networking devices used. The power consumed by online browsing and downloading was also factored into the model. The embedded CO2e of server and networking devices was proportioned to each ESD process. Three U.K.-based ESD scenarios were analyzed using the model which revealed potential CO2e savings of 83% when ESD was used over physical distribution. Results also highlighted the importance of server efficiency and utilization methods.

Scaling up data mining techniques to large datasets using parallel and distributed processing

Advances in hardware and software technology enable us to collect, store and distribute large quantities of data on a very large scale. Automatically discovering and extracting hidden knowledge in the form of patterns from these large data volumes is known as data mining. Data mining technology is not only a part of business intelligence, but is also used in many other application areas such as research, marketing and financial analytics. For example medical scientists can use patterns extracted from historic patient data in order to determine if a new patient is likely to respond positively to a particular treatment or not; marketing analysts can use extracted patterns from customer data for future advertisement campaigns; finance experts have an interest in patterns that forecast the development of certain stock market shares for investment recommendations. However, extracting knowledge in the form of patterns from massive data volumes imposes a number of computational challenges in terms of processing time, memory, bandwidth and power consumption. These challenges have led to the development of parallel and distributed data analysis approaches and the utilisation of Grid and Cloud computing. This chapter gives an overview of parallel and distributed computing approaches and how they can be used to scale up data mining to large datasets.

TCL/TK for EDA tools

Tcl/Tk scripting language has become the de-facto standard for EDA tools. This paper explains how to start working with Tcl/Tk using simple examples. Two complete applications are presented to show in more detail the capabilities of the language. In one script average power consumption of a digital system is automated. A second script creates a virtual display driven by the simulation of a graphic card.