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A method of defining the filtration efficiency of filter media has been devised, in which the transmission factor at a specified size is measured instead of the effective cut‐off size. The new measure is more sensitive and provides a more useful fiure than the old measure of effective cut‐off size. An additional test is proposed to measure the efficiency of removal of particles of smaller sizes; this test requires the derivation of the transmission curve, which is defined. No change is proposed in the method of measurement of flow efficiency in terms of flow constant. It is suggested that the specification of a fine particle filter medium should include the following clauses: (a) A statement of the maximum acceptable transmission factor at a given size (cither 5 microns or 10 microns). (b) A statement of the maximum acceptable transmission factors at various smaller sizes. (c) A statement of the minimum acceptable flow constant. Experimental techniques, including the method of preparing the artificial contaminants, are described. Results are presented on nine materials and a comparison is made for five of these materials between transmission factors at 5 microns and 10 microns and effective cut‐off sizes. The dependence of transmission factor and flow constant on thickness of filter medium is discussed.

The purpose of this paper is to focus on applications related to the hyperthermia treatment of cancer, with heating imposed either by a laser in the near-infrared range or by radiofrequency waves. The particle filter algorithms are compared in terms of computational time and solution accuracy.

The authors extend the analyses performed in their previous works to compare three different algorithms of the particle filter, as applied to the hyperthermia treatment of cancer. The particle filters examined here are the sampling importance resampling (SIR) algorithm, the auxiliary sampling importance resampling (ASIR) algorithm and Liu & West’s algorithm.

Liu & West’s algorithm resulted in the largest computational times. On the other hand, this filter was shown to be capable of dealing with very large uncertainties. In fact, besides the uncertainties in the model parameters, Gaussian noises, similar to those used for the SIR and ASIR filters, were added to the evolution models for the application of Liu & West’s filter. For the three filters, the estimated temperatures were in excellent agreement with the exact ones.

This work may help medical doctors in the future to prescribe treatment protocols and also opens the possibility of devising control strategies for the hyperthermia treatment of cancer.

The natural solution to couple the uncertain results from numerical simulations with the measurements that contain uncertainties, aiming at the better prediction of the temperature field of the tissues inside the body, is to formulate the problem in terms of state estimation, as performed in this work.

In this analysis or the action of fine particle filters and the discussion of methods of test, the following principal conclusions are reached:

The purpose of this paper is to present an improved particle filter-based attitude estimator for a quadrotor unmanned aerial vehicle (UAV) that addresses the degeneracy issues.

Control of a quadrotor is not sufficient enough without an estimator to eliminate the noise from low-cost sensors. In this work, particle filter-based attitude estimator is proposed and used for nonlinear quadrotor dynamics. But, since recursive Bayesian estimation steps may rise degeneracy issues, the proposed scheme is improved with four different and widely used resampling algorithms.

Robustness of the proposed schemes is tested under various scenarios that include different levels of uncertainty and different particle sizes. Statistical analyses are conducted to assess the error performance of the schemes. According to the statistical analysis, the proposed estimators are capable of reducing sensor noise up to 5x, increasing signal to noise ratio up to 2.5x and reducing the uncertainty bounds up to 36x with root mean square value of as low as 0.0024, mean absolute error value of 0.036, respectively.

To the best of the authors’ knowledge, the originality of this paper is to propose a robust particle filter-based attitude estimator to eliminate the low-cost sensor errors of quadrotor UAVs.

Cleanrooms are highly controlled enclosed rooms where air quality is monitored and ensured to have less contamination according to standard cleanliness level. Air filters are used to optimize indoor air quality and remove air pollutants. Filter media and filtering system are decided as per requirement. Depth filter media are mostly used in cleanroom filtrations. This paper aims to present a comprehensive review of the evolution of cleanroom filter media. It evaluates the advantages and disadvantages of air filter media. It is also studied which air filters have additional properties such as anti-microbial properties, anti-odour properties and chemical absorbent. Development and innovation of air filters and filtration techniques are necessary to improve the performance via the synergistic effect and it can be a possible avenue of future research.

This paper aims to drive the future of air filter research and development in achieving high-performance filtration with high filtration efficiency, low operational cost and high durability. Air pollutants are classified into three types: suspended particles, volatile organic pollutants and microorganisms. Technologies involved in purification are filtration, water washing purification, electrostatic precipitation and anion technology. They purify the air by running it through a filter medium that traps dust, hair, pet fur and debris. As air passes through the filter media, they function as a sieve, capturing particles. The fibres in the filter medium provide a winding path for airflow. There are different types of air filters such as the high-efficiency particulate air filter, fibreglass air filter and ultra-low particulate air filter.

Emerging filtration technologies and filters such as nanofibres, filters with polytetrafluoroethylene membrane are likely to become prevalent over the coming years globally. The introduction of indoor air filtration with thermal comfort can be a possible avenue of future research along with expanding indoor environment monitoring and improving air quality predictions. New air filters and filtration technologies having better performance with low cost and high durability must be developed which can restrict multiple types of pollutants at the same time.

The systematic literature review approach used in this paper highlights the emerging trends and issues in cleanroom filtration in a structured and thematic manner, enabling future work to progress as it will continue to develop and evolve.

The purpose of this work was to study the influence of particles and fiber material properties on the deposition efficiency. Collection of aerosol particles in the particular steps of their production, and purification of the air at the workplace and the atmospheric environment requires the efficient method of separation of particulate matter from the carrier gas. There are many papers published in the past years in which the deposition of particles on fibrous collectors is considered. Most of them assume that collisions between particles and collector surfaces are 100% effective.

For the purpose of this work, the lattice Boltzmann model was used to describe fluid dynamics, whereas the solid particles motion was modeled by the Brownian dynamics. The interactions between particles and surfaces were modeled using an energy-balanced oscillatory model.

The results show significant impact of material properties on filter performance.

Obtained results may provide useful information for the proper design of a filtration process and the production of filters with long service life.

In addition, the results presented in this work show that some assumptions of the classical filtration theory lead to an overestimation of deposition efficiency.

The purpose of this paper is to present a scan matching simultaneous localization and mapping (SLAM) algorithm based on particle filter to generate the grid map online. It mainly focuses on reducing the memory consumption and alleviating the loop closure problem.

The proposed method alleviates the loop closure problem by improving the accuracy of the robot’s pose. First, two improvements were applied to enhance the accuracy of the hill climbing scan matching. Second, a particle filter was used to maintain the diversity of the robot’s pose and then to supply potential seeds to the hill climbing scan matching to ensure that the best match point was the global optimum. The proposed method reduces the memory consumption by maintaining only a single grid map.

Simulation and experimental results have proved that this method can build a consistent map of a complex environment. Meanwhile, it reduced the memory consumption and alleviates the loop closure problem.

In this paper, a new SLAM algorithm has been proposed. It can reduce the memory consumption and alleviate the loop closure problem without lowering the accuracy of the generated grid map.

EC-135P2+ helicopters operated by Polish Medical Air Rescue are highly exposed to environmental particles entering engines when performing helicopter emergency medical services. This paper aims to assess the effectiveness of inlet barrier filters installed to protect the engines, including their impact on maintenance.

The organisation adopted a comprehensive set of measures to predict and limit the impact of dust ingestion including visual inspections, health management and engine trend monitoring based on ground power checks’ (GPC) results. Three alternative particle separation solutions were considered. Finally, helicopter inlets were modified to allow the selected filter system to be installed, which reduced the number of particles ingested by the engine and prevented from premature overhauls.

The analyses carried out enabled not only the selection of the optimal filtration solution and its seamless implementation into the fleet but also confirmed its efficiency. After installing the filters, engines’ lifetime is extended from 500 to 4,500 flight hours while operating costs and the number of maintenance tasks was reduced significantly.

Lessons learned from operational experience show that a well-matched particle separation system can mitigate accelerated engine deterioration even if the platform is continuously exposed to environmental particles. The remaining useful life of engines can be predicted using performance models and data from GPC.

The aim of this study is to determine the variation of the different oil analysis instruments in terms of standard deviation and CV‐values, when measuring samples of fully formulated hydraulic and gear oils taken from working systems.

In this investigation two different spectrometric techniques, ICP‐OES and RDE‐OES, have been studied to determine the instruments' precision of measurement and ability to measure the absolute level of contamination.

The ICP has better precision of measurement of the two instruments, but cannot predict the absolute values of contamination when oil samples are only treated by organic solvent dilution if the samples include large or dense particles. It is therefore not too good, with the sample pre‐treatment method used, at detecting wear processes that produce dense/large particles, such as pitting failure. For instance, microwave‐assisted acid digestion could be used for sample pre‐treating to obtain accurate results in that case. It should, however, be able to detect wear mechanisms that produce small particles such as abrasive wear in any case: the ICP has a repeatability value of r=3 per cent and a reproducibility value of R=12 per cent for contamination levels of between 50‐400 PPM and r=0.6 PPM and R=2 PPM, respectively, at values below 50 PPM; the RDE cannot predict the absolute value of contamination if this includes large or dense particles if proper sample pre‐treatment is not used. It is therefore not good at detecting wear mechanisms that produce dense/large particles (if the oil samples are not pre‐treated properly) such as pitting but should be able to detect abrasive wear and similar processes that produce small particles in any case; the RDE's precision of measurement is not as good as the ICP, with a reproducibility variation of R=r=25 per cent for contamination levels between 20‐500 PPM and R=r=6 PPM for contamination level below 20 PPM.

Measuring only on fully formulated oils from hydraulic and gear systems.

The study will be of significant support regarding industrial interpretation of measurement results from the most common oil particle measurement methods.

No other similar studies are known.

The purpose of this paper is to estimate the contact-consistent object poses during contact-rich manipulation tasks based only on visual sensors.

The method follows a four-step procedure. Initially, the raw object poses are retrieved using the available object pose estimation method and filtered using Kalman filter with nominal model; second, a group of particles are randomly generated for each pose and evaluated the corresponding object contact state using the contact simulation software. A probability guided particle averaging method is proposed to balance the accuracy and safety issues; third, the independently estimated contact states are fused in a hidden Markov model to remove the abnormal contact state observations; finally, the object poses are refined by averaging the contact state consistent particles.

The experiments are performed to evaluate the effectiveness of the proposed methods. The results show that the method can achieve smooth and accurate pose estimation results and the estimated contact states are consistent with ground truth.

This paper proposes a method to obtain contact-consistent poses and contact states of objects using only visual sensors. The method tries to recover the true contact state from inaccurate visual information by fusing contact simulations results and contact consistency assumptions. The method can be used to extract pose and contact information from object manipulation tasks by just observing the demonstration, which can provide a new way for the robot to learn complex manipulation tasks.