Keyword field-free conjunctive keyword searches on encrypted data and extension for dynamic groups

We consider the following problem: a user stores encrypted documents on an untrusted server, and wishes to retrieve all documents containing some keywords without any loss of data confidentiality. Conjunctive keyword searches on encrypted data have been studied by numerous researchers over the past few years, and all existing schemes use keyword fields as compulsory information. This however is impractical for many applications. In this paper, we propose a scheme of keyword field-free conjunctive keyword searches on encrypted data, which affirmatively answers an open problem asked by Golle et al. at ACNS 2004. Furthermore, the proposed scheme is extended to the dynamic group setting. Security analysis of our constructions is given in the paper.

Lower partial moment and information entropy-based dynamic electricity purchasing strategy

In the electricity market environment, load-serving entities (LSEs) will inevitably face risks in purchasing electricity because there are a plethora of uncertainties involved. To maximize profits and minimize risks, LSEs need to develop an optimal strategy to reasonably allocate the purchased electricity amount in different electricity markets such as the spot market, bilateral contract market, and options market. Because risks originate from uncertainties, an approach is presented to address the risk evaluation problem by the combined use of the lower partial moment and information entropy (LPME). The lower partial moment is used to measure the amount and probability of the loss, whereas the information entropy is used to represent the uncertainty of the loss. Electricity purchasing is a repeated procedure; therefore, the model presented represents a dynamic strategy. Under the chance-constrained programming framework, the developed optimization model minimizes the risk of the electricity purchasing portfolio in different markets because the actual profit of the LSE concerned is not less than the specified target under a required confidence level. Then, the particle swarm optimization (PSO) algorithm is employed to solve the optimization model. Finally, a sample example is used to illustrate the basic features of the developed model and method.

Detection of dynamic primary user with cooperative spectrum sensing

In this paper we demonstrate that existing cooperative spectrum sensing formulated for static primary users cannot accurately detect dynamic primary users regardless of the information fusion method. Performance error occurs as the sensing parameters calculated by the conventional detector result in sensing performance that violates the sensing requirements. Furthermore, the error is accumulated and compounded by the number of cooperating nodes. To address this limitation, we design and implement the duty cycle detection model for the context of cooperative spectrum sensing to accurately calculate the sensing parameters that satisfy the sensing requirements. We show that longer sensing duration is required to compensate for dynamic primary user traffic.

A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

Air pollution and invisible violence

In recent years air pollution has been referred to as an ‘invisible killer’, and ‘an invisible health crisis’ (European Respiratory Society 2012). As other chapters in this collection have argued, the invisibility of crime is manifested through various lenses: lack of knowledge, lack of political and media attention, an absence of policing and regulatory focus, and an unwitting and ill-informed public. All such arguments pertain to air pollution; however, toxic emissions are also literally invisible from sight and consciousness, as are the associated consequences.

Air ion concentrations under overhead power lines

Corona discharge is responsible for the flux of small ions from overhead power lines, and is capable of modifying the ambient electrical environment, such as the air ion concentrations at ground level. Once produced, small ions quickly attach to aerosol particles in the air, producing ‘large ions’, approximately 1 nm to 1 µm in diameter. However, very few studies have measured air ion concentrations directly near high voltage transmission lines. The present study involved the simultaneously measurement of small ion concentration and net large ion concentration using air ion counters and an aerosol electrometer at four power line sites. Both positive and negative small ion concentration (<1.6nm), net large ion concentration (2nm-5μm) and particle number concentration (10nm-2μm) were measured using air ion counters and an aerosol electrometer at four power line sites. Measurements at sites 1 and 2 were conducted at both upwind and downwind sides. The results showed that total ion concentrations on the downwind side were 3-5 times higher than on the upwind side, while particle number concentrations did not show a significant difference. This result also shows that a large number of ions were emitted from the power lines at sites 1 and 2. Furthermore, both positive and negative ions were observed at different power line sites. Dominant positive ions were observed at site 1, with a concentration of 4.4 x 103 ions cm-3, which was 10 times higher than on the upwind side. Contrary to site 1, sites 2 to 4 showed negative ion emissions, with concentrations of -1.2 x 103, -460 and -410 ions cm-3, respectively. These values were higher than the background urban negative ion concentration of 400 cm-3. At site 1 and site 2, the net ion concentration and net particle charge concentration on downwind side of the lines showed same polarities. Further investigations were also conducted into the correlation between net ion concentration and net charge particle concentration 20 m downwind of the power lines at site 2. The two parameters showed a correlation coefficient of 0.72, indicating that a substantial number of ions could attach to particles and affect the particle charge status within a short distance from the source.

Desalination of seawater using solar, ambient energy and waste heat from air conditioning

Desalination is considered one of the most suitable areas for the utilization of solar energy, as there are many places in the world where abundant supply of solar energy is available and also there is a great demand for fresh water. An integrated solar heat pump desalination system has been developed at the National University of Singapore. The system also offers the opportunity of water heating and drying utilizing solar, ambient energy and waste heat from air conditioning system, which is conventionally dumped into the environment causing global warming. Desalination is carried out by making use of a single effect of Multi-Effect Distillation (MED) system. Within the desalination chamber, both fl ashing and evaporation of saline water take place. The maximum Coefficient of Performance (COP) of the heat pump system was around 5.8. In the integrated system, the maximum fresh water production rate was 9.6 l h−1 and a Performance Ratio (PR) of 1.2. For only desalination, the system has the potential to produce a maximum of 30 l h−1 of fresh water.

Water heating and dehumidification with heat pump utilizing solar, ambient and waste heat

The low temperature operation of a heat pump makes it an excellent match for the use of solar energy. At the National University of Singapore, a solar assisted heat pump system has been designed, fabricated and installed to provide water heating and drying. The system also utilizes the air con waste heat, which would normally be released to atmosphere adding to global warming. Experimental results show that the twophase unglazed solar evaporator-collector, instead of losing energy to the ambient, gained a significant amount due to low operating temperature of the collector. As a result, the collector efficiency attains a value greater than 1, when conventional collector equations are used. With this evaporator-collector, the system can be operated even in the absence of solar irradiation. The waste heat was collected from an air-con system, which maintained a room at 20-22 oC. In the condenser side, water at 60 oC was produced at a rate of 3 liter/minute and the drying capacity was 2.2kg/hour. Maximum COP of the system was found to be about 5.5.

Nano and ultrafine particle number concentrations in different environments : application towards air quality regulations

Particle number concentrations vary significantly with environment and, in this study, we attempt to assess the significance of these differences. Towards this aim, we reviewed 85 papers that have reported particle number concentrations levels at 126 sites covering different environments. We grouped the results into eight categories according to measurement location including: road tunnel, on-road, road-side, street canyon, urban, urban background, rural, and clean background. From these reports, the overall median number concentration for each of the eight site categories was calculated. The eight location categories may be classified into four distinct groups. The mean median particle number locations for these four types were found to be statistically different from each other. Rural and clean background sites had the lowest concentrations of about 3x103 cm-3. Urban and urban background sites showed concentrations that were three times higher (9x103 cm-3). The mean concentration for the street canyon, roadside and on-road measurement sites was 4.6x104 cm-3, while the highest concentrations were observed in the road tunnels (8.6x104 cm-3). This variation is important when assessing human exposure-response for which there is very little data available, making it difficult to develop health guidelines, a basis for national regulations. Our analyses shows that the current levels in environments affected by vehicle emissions are 3 to 28 times higher than in the natural environments. At present, there is no threshold level in response to exposure to ultrafine particles. Therefore, future control and management strategies should target a decrease of these particles in urban environments by more than one order of magnitude to bring them down to the natural background. At present there is a long way to go to achieve this.

A fluorenone based low band gap solution processable copolymer for air stable and high mobility organic field effect transistors

A fluorenone based alternating copolymer (PFN-DPPF) with a furan based fused aromatic moiety has been designed and synthesized. PFN-DPPF exhibits a small band gap with a lower HOMO value. Testing this polymer semiconductor as the active layer in organic thin-film transistors results in hole mobilities as high as 0.15 cm2 V-1 s-1 in air.

Decomposition analysis of air pollution abatement in China: empirical study for ten industrial sectors from 1998 to 2009

This study analyzes the management of air pollutant substance in Chinese industrial sectors from 1998 to 2009. Decomposition analysis applying the logarithmic mean divisia index is used to analyze changes in emissions of air pollutants with a focus on the following five factors: coal pollution intensity (CPI), end-of-pipe treatment (EOP), the energy mix (EM), productive efficiency change (EFF), and production scale changes (PSC). Three pollutants are the main focus of this study: sulfur dioxide (SO2), dust, and soot. The novelty of this paper is focusing on the impact of the elimination policy on air pollution management in China by type of industry using the scale merit effect for pollution abatement technology change. First, the increase in SO2 emissions from Chinese industrial sectors because of the increase in the production scale is demonstrated. However, the EOP equipment that induced this change and improvements in energy efficiency has prevented an increase in SO2 emissions that is commensurate with the increase in production. Second, soot emissions were successfully reduced and controlled in all industries except the steel industry between 1998 and 2009, even though the production scale expanded for these industries. This reduction was achieved through improvements in EOP technology and in energy efficiency. Dust emissions decreased by nearly 65% between 1998 and 2009 in the Chinese industrial sectors. This successful reduction in emissions was achieved by implementing EOP technology and pollution prevention activities during the production processes, especially in the cement industry. Finally, pollution prevention in the cement industry is shown to result from production technology development rather than scale merit. © 2013 Elsevier Ltd. All rights reserved.

Modal choice between air and rail : a social efficiency benchmarking analysis that considers CO2 emissions

The problem of modal choice between rail and air arises as public awareness of carbon dioxide (CO2) emissions by the transportation sector rises. In this paper, we answer this question quantitatively by performing an efficiency benchmarking analysis that takes into account life-cycle CO2 emission due to transport service provision. The paper employs nonparametric efficiency estimation methods, namely a slacks-based inefficiency measure, as well as a more conventional directional distance function approach. We apply them to a panel data set for three major railway companies and the aviation sector in Japan for the period from 1999 to 2007. Results shows that, contrary to the common argument, air transport can still be more socially efficient than rail transport, even when the environmental load due to CO2 emission is incorporated. This is due to the aviation sector's extremely low user cost, measured in terms of in-vehicle time. In other words, aviation is a necessary transportation mode for those with a very high willingness to pay for their time.

An experimental approach to air gap optimisation for a correction-less small field diode

Aim A recent Monte Carlo based study has shown that it is possible to design a diode that measures small field output factors equivalent to that in water. This is accomplished by placing an appropriate sized air gap above the silicon chip (1) with experimental results subsequently confirming that a particular Monte Carlo design was accurate (2). The aim of this work was to test if a new correction-less diode could be designed using an entirely experimental methodology. Method: All measurements were performed on a Varian iX at a depth of 5 cm, SSD of 95 cm and field sizes of 5, 6, 8, 10, 20 and 30 mm. Firstly, the experimental transfer of kq,clin,kq,msr from a commonly used diode detector (IBA, stereotactic field diode (SFD)) to another diode detector (Sun Nuclear, unshielded diode, (EDGEe)) was tested. These results were compared to Monte Carlo calculated values of the EDGEe. Secondly, the air gap above the EDGEe silicon chip was optimised empirically. Nine different air gap “tops” were placed above the EDGEe (air depth = 0.3, 0.6, 0.9 mm; air width = 3.06, 4.59, 6.13 mm). The sensitivity of the EDGEe was plotted as a function of air gap thickness for the field sizes measured. Results: The transfer of kq,clin,kq,msr from the SFD to the EDGEe was correct to within the simulation and measurement uncertainties. The EDGEe detector can be made “correction-less” for field sizes of 5 and 6 mm, but was ∼2% from being “correction-less” at field sizes of 8 and 10 mm. Conclusion Different materials will perturb small fields in different ways. A detector is only “correction-less” if all these perturbations happen to cancel out. Designing a “correction-less” diode is a complicated process, thus it is reasonable to expect that Monte Carlo simulations should play an important role.

Dancing through the Air (parts one and 2) - Spirit of Akasha

Recording for ARIA nominated Film Soundtrack for Spirit of Akasha. Recorded, Mixed, and Co-produced by Phil Graham. Published by Warner Music Australia

A national satellite-based land-use regression model for air pollution exposure assessment in Australia

Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.