A comparison of energy use in conventional and integrated arable farming systems in the UK

The LINK Integrated Farming Systems (LINK-IFS) Project (1992-1997) was setup to compare conventional and integrated arable farming systems (IAFS), concentrating on practical feasibility and economic viability, but also taking into account the level of inputs used and environmental impact. As part of this, an examination into energy use within the two systems was also undertaken. This paper presents the results from that analysis. The data used is from the six sites within the LINK-IFS Project, spread through the arable production areas of England and from the one site in Scotland, covering the 5 years of the project. The comparison of the energy used is based on the equipment and inputs used to produce I kg of each crop within the conventional and integrated rotations, and thereby the overall energy used for each system. The results suggest that, in terms of total energy used, the integrated system appears to be the most efficient. However, in terms of energy efficiency, energy use per kilogram of output, the results are less conclusive. (C) 2003 Elsevier Science B.V. All rights reserved.

Efficient fuzzy control of a rotary inverted pendulum based on LQR mapping

This paper develops fuzzy methods for control of the rotary inverted pendulum, an underactuated mechanical system. Two control laws are presented, one for swing up and another for the stabilization. The pendulum is swung up from the vertical down stable position to the upward unstable position in a controlled trajectory. The rules for the swing up are heuristically written such that each swing results in greater energy build up. The stabilization is achieved by mapping a stabilizing LQR control law to two fuzzy inference engines, which reduces the computational load compared with using a single fuzzy inference engine. The robustness of the balancing control is tested by attaching a bottle of water at the tip of the pendulum.

A model of intelligent building energy management for the indoor environment

People's interaction with the indoor environment plays a significant role in energy consumption in buildings. Mismatching and delaying occupants' feedback on the indoor environment to the building energy management system is the major barrier to the efficient energy management of buildings. There is an increasing trend towards the application of digital technology to support control systems in order to achieve energy efficiency in buildings. This article introduces a holistic, integrated, building energy management model called `smart sensor, optimum decision and intelligent control' (SMODIC). The model takes into account occupants' responses to the indoor environments in the control system. The model of optimal decision-making based on multiple criteria of indoor environments has been integrated into the whole system. The SMODIC model combines information technology and people centric concepts to achieve energy savings in buildings.

Improving the efficiency of energy utilization in cattle

The efficiency of energy utilisation in cattle is a determinant of the profitability of milk and beef production, as well as their environmental impact. At an animal level, meat and milk production by ruminants is less efficient than pig and poultry production, in part due to lower digestibility of forages compared with grains. However, when compared on the basis of human-edible inputs, the ruminant has a clear efficiency advantage. There has been recent interest in feed conversion efficiency (FCE) in dairy cattle and residual feed intake, an indicator of FCE, in beef cattle. Variation between animals in FCE may have genetic components, allowing selection for animals with greater efficiency and reduced environmental impact. A major source of variation in FCE is feed digestibility, and thus approaches that improve digestibility should improve FCE if rumen function is not disrupted. Methane represents a substantial loss of digestible energy from rations. Major determinants of methane emission are the amount of feed consumed and the proportions of forage and concentrates fed. In addition, feeding fat has long been known to reduce methane emission. A myriad of other supplements and additives are currently being investigated as mitigators of methane emission, but in many cases compounds effective in sheep are ineffective in lactating dairy cows. Ultimately, the adoption of ‘best practice’ in diet formulation and management may be the most effective option for reducing methane. In assessing the efficiency of energy use for milk and meat production by cattle, and their environmental impact, it is imperative that comparisons be made at a systems level, and that the wider social and economic implications of mitigation policy are considered.

Graph-based algorithms for comparison and prediction of household-level energy use profiles

We present an efficient graph-based algorithm for quantifying the similarity of household-level energy use profiles, using a notion of similarity that allows for small time–shifts when comparing profiles. Experimental results on a real smart meter data set demonstrate that in cases of practical interest our technique is far faster than the existing method for computing the same similarity measure. Having a fast algorithm for measuring profile similarity improves the efficiency of tasks such as clustering of customers and cross-validation of forecasting methods using historical data. Furthermore, we apply a generalisation of our algorithm to produce substantially better household-level energy use forecasts from historical smart meter data.

GSHMC: an efficient method for molecular simulation

The hybrid Monte Carlo (HMC) method is a popular and rigorous method for sampling from a canonical ensemble. The HMC method is based on classical molecular dynamics simulations combined with a Metropolis acceptance criterion and a momentum resampling step. While the HMC method completely resamples the momentum after each Monte Carlo step, the generalized hybrid Monte Carlo (GHMC) method can be implemented with a partial momentum refreshment step. This property seems desirable for keeping some of the dynamic information throughout the sampling process similar to stochastic Langevin and Brownian dynamics simulations. It is, however, ultimate to the success of the GHMC method that the rejection rate in the molecular dynamics part is kept at a minimum. Otherwise an undesirable Zitterbewegung in the Monte Carlo samples is observed. In this paper, we describe a method to achieve very low rejection rates by using a modified energy, which is preserved to high-order along molecular dynamics trajectories. The modified energy is based on backward error results for symplectic time-stepping methods. The proposed generalized shadow hybrid Monte Carlo (GSHMC) method is applicable to NVT as well as NPT ensemble simulations.

Reliability comparison of transmit/receive diversity and error control coding in low-power medium access control protocols

Low-power medium access control (MAC) protocols used for communication of energy constraint wireless embedded devices do not cope well with situations where transmission channels are highly erroneous. Existing MAC protocols discard corrupted messages which lead to costly retransmissions. To improve transmission performance, it is possible to include an error correction scheme and transmit/receive diversity. It is possible to add redundant information to transmitted packets in order to recover data from corrupted packets. It is also possible to make use of transmit/receive diversity via multiple antennas to improve error resiliency of transmissions. Both schemes may be used in conjunction to further improve the performance. In this study, the authors show how an error correction scheme and transmit/receive diversity can be integrated in low-power MAC protocols. Furthermore, the authors investigate the achievable performance gains of both methods. This is important as both methods have associated costs (processing requirements; additional antennas and power) and for a given communication situation it must be decided which methods should be employed. The authors’ results show that, in many practical situations, error control coding outperforms transmission diversity; however, if very high reliability is required, it is useful to employ both schemes together.

Improving transmission reliability of low-power medium access control protocols using average diversity combining

Embedded computer systems equipped with wireless communication transceivers are nowadays used in a vast number of application scenarios. Energy consumption is important in many of these scenarios, as systems are battery operated and long maintenance-free operation is required. To achieve this goal, embedded systems employ low-power communication transceivers and protocols. However, currently used protocols cannot operate efficiently when communication channels are highly erroneous. In this study, we show how average diversity combining (ADC) can be used in state-of-the-art low-power communication protocols. This novel approach improves transmission reliability and in consequence energy consumption and transmission latency in the presence of erroneous channels. Using a testbed, we show that highly erroneous channels are indeed a common occurrence in situations, where low-power systems are used and we demonstrate that ADC improves low-power communication dramatically.

Mode-specificity and transition state-specific energy redistribution in the chemisorption of CH4 on Ni{100}

We have investigated methane (CH4) dissociative chemisorption on the Ni{100} surface by first-principles molecular dynamics (MD) simulations. Our results show that this reaction is mode-specific, with the n1 state being the most strongly coupled to efficient energy flow into the reaction coordinate when the molecule reaches the transition state. By performing MD simulations for two different transition state (TS) structures we provide evidence of TS structure-specific energy redistribution in methane chemisorption. Our results are compared with recently reported state-resolved measurement of methane adsorption probability on nickel surfaces, and we find that a strong correlation exists between the highest vibrational efficacy measured on Ni{100} for the n1 state and the calculated highest fractional vibrational energy content in this mode.

Emergy-based sustainability assessment of different energy options for green buildings

It is necessary to minimize the environmental impact and utilize natural resources in a sustainable and efficient manner in the early design stage of developing an environmentally-conscious design for a heating, ventilating and air-conditioning system. Energy supply options play a significant role in the total environmental load of heating, ventilating and air-conditioning systems. To assess the environmental impact of different energy options, a new method based on Emergy Analysis is proposed. Emergy Accounting, was first developed and widely used in the area of ecological engineering, but this is the first time it has been used in building service engineering. The environmental impacts due to the energy options are divided into four categories under the Emergy Framework: the depletion of natural resources, the greenhouse effect (carbon dioxide equivalents), the chemical rain effect (sulphur dioxide equivalents), and anthropogenic heat release. The depletion of non-renewable natural resources is indicated by the Environmental Load Ratio, and the environmental carrying capacity is developed to represent the environmental service to dilute the pollutants and anthropogenic heat released. This Emergy evaluation method provides a new way to integrate different environmental impacts under the same framework and thus facilitates better system choices. A case study of six different kinds of energy options consisting of renewable and non-renewable energy was performed by using Emergy Theory, and thus their relative environmental impacts were compared. The results show that the method of electricity generation in energy sources, especially for electricity-powered systems, is the most important factor to determine their overall environmental performance. The direct-fired lithium-bromide absorption type consumes more non-renewable energy, and contributes more to the urban heat island effect compared with other options having the same electricity supply. Using Emergy Analysis, designers and clients can make better-informed, environmentally-conscious selections of heating, ventilating and air-conditioning systems.

Economic experiments used for the evaluation of building users’ energy-saving behavior

Different treatments that could be implemented in the home environ-ment are evaluated with the objective of reaching a more rational and efficient use of energy. We consider that a detailed knowledge of energy-consuming behaviour is paramount for the development and implementation of new technologies, services and even policies that could result in more rational energy use. The proposed evaluation methodology is based on the development of economic experiments implemented in an experimental economics laboratory, where the behaviour of individuals when making decisions related to energy use in the domestic environment can be tested.

Equations to predict methane emissions from cows fed at maintenance energy level in pasture-based systems

Ruminant production is a vital part of food industry but it raises environmental concerns, partly due to the associated methane outputs. Efficient methane mitigation and estimation of emissions from ruminants requires accurate prediction tools. Equations recommended by international organizations or scientific studies have been developed with animals fed conserved forages and concentrates and may be used with caution for grazing cattle. The aim of the current study was to develop prediction equations with animals fed fresh grass in order to be more suitable to pasture-based systems and for animals at lower feeding levels. A study with 25 nonpregnant nonlactating cows fed solely fresh-cut grass at maintenance energy level was performed over two consecutive grazing seasons. Grass of broad feeding quality, due to contrasting harvest dates, maturity, fertilisation and grass varieties, from eight swards was offered. Cows were offered the experimental diets for at least 2 weeks before housed in calorimetric chambers over 3 consecutive days with feed intake measurements and total urine and faeces collections performed daily. Methane emissions were measured over the last 2 days. Prediction models were developed from 100 3-day averaged records. Internal validation of these equations, and those recommended in literature, was performed. The existing in greenhouse gas inventories models under-estimated methane emissions from animals fed fresh-cut grass at maintenance while the new models, using the same predictors, improved prediction accuracy. Error in methane outputs prediction was decreased when grass nutrient, metabolisable energy and digestible organic matter concentrations were added as predictors to equations already containing dry matter or energy intakes, possibly because they explain feed digestibility and the type of energy-supplying nutrients more efficiently. Predictions based on readily available farm-level data, such as liveweight and grass nutrient concentrations were also generated and performed satisfactorily. New models may be recommended for predictions of methane emissions from grazing cattle at maintenance or low feeding levels.

Bio-inspired ant colony optimization based clustering algorithm with mobile sinks for applications in consumer home automation networks

With the fast development of wireless communications, ZigBee and semiconductor devices, home automation networks have recently become very popular. Since typical consumer products deployed in home automation networks are often powered by tiny and limited batteries, one of the most challenging research issues is concerning energy reduction and the balancing of energy consumption across the network in order to prolong the home network lifetime for consumer devices. The introduction of clustering and sink mobility techniques into home automation networks have been shown to be an efficient way to improve the network performance and have received significant research attention. Taking inspiration from nature, this paper proposes an Ant Colony Optimization (ACO) based clustering algorithm specifically with mobile sink support for home automation networks. In this work, the network is divided into several clusters and cluster heads are selected within each cluster. Then, a mobile sink communicates with each cluster head to collect data directly through short range communications. The ACO algorithm has been utilized in this work in order to find the optimal mobility trajectory for the mobile sink. Extensive simulation results from this research show that the proposed algorithm significantly improves home network performance when using mobile sinks in terms of energy consumption and network lifetime as compared to other routing algorithms currently deployed for home automation networks.

Efficient biometric and password based mutual authentication for consumer USB mass storage devices

A Universal Serial Bus (USB) Mass Storage Device (MSD), often termed a USB flash drive, is ubiquitously used to store important information in unencrypted binary format. This low cost consumer device is incredibly popular due to its size, large storage capacity and relatively high transfer speed. However, if the device is lost or stolen an unauthorized person can easily retrieve all the information. Therefore, it is advantageous in many applications to provide security protection so that only authorized users can access the stored information. In order to provide security protection for a USB MSD, this paper proposes a session key agreement protocol after secure user authentication. The main aim of this protocol is to establish session key negotiation through which all the information retrieved, stored and transferred to the USB MSD is encrypted. This paper not only contributes an efficient protocol, but also does not suffer from the forgery attack and the password guessing attack as compared to other protocols in the literature. This paper analyses the security of the proposed protocol through a formal analysis which proves that the information is stored confidentially and is protected offering strong resilience to relevant security attacks. The computational cost and communication cost of the proposed scheme is analyzed and compared to related work to show that the proposed scheme has an improved tradeoff for computational cost, communication cost and security.