Separable Filters Research Articles

Multifunctional PDMS polyHIPE filters for oil-water separation and antibacterial activity

Herein, we present the fabrication of multifunctional polydimethylsiloxane (PDMS) foams with antibacterial, hydrophilic, and underwater superoleophobic properties for the separation of oil-water mixtures and simultaneous water disinfection. The PDMS foams, prepared following the high internal phase emulsion templating method, exhibit a porous interconnected structure and were further functionalized with a polydopamine (PDA) layer and in-situ grown silver nanoparticles (Ag NPs) upon successive dipping processes in dopamine and silver nitrate solutions. We demonstrate the successful use of the developed foams as 3D filters for the gravity-driven separation of oil-water mixtures and the subsequent disinfection of the filtered water. The flow rate of oil-water mixtures is strongly correlated to the in-situ grown Ag NPs density present on the foams, in contrary to the oil rejection efficiency, which is above 99.99% in all the studied cases. In fact, the flow rate values increase with the increasing density of the in-situ formed Ag NPs starting from 1937.7 ± 580.4 L m−2 h−1 for the foam without Ag NPs and reaching 4043.0 ± 710.7 L m−2 h−1 for the foam with the highest amount of NPs. Taking the latter as an example, we prove that the foams can be used for several filtration cycles without any modification of their oil rejection efficiency. In addition to efficient oil-water separation, the foams have antibacterial properties and are able to disinfect the permeate. The simple preparation method, effective gravity-driven filtration, robust nature, and antibacterial capability make the herein engineered multifunctional foams promising for highly efficient filtration processes.

A Simplified CNN Classification Method for MI-EEG via the Electrode Pairs Signals.

A brain-computer interface (BCI) based on electroencephalography (EEG) can provide independent information exchange and control channels for the brain and the outside world. However, EEG signals come from multiple electrodes, the data of which can generate multiple features. How to select electrodes and features to improve classification performance has become an urgent problem to be solved. This paper proposes a deep convolutional neural network (CNN) structure with separated temporal and spatial filters, which selects the raw EEG signals of the electrode pairs over the motor cortex region as hybrid samples without any preprocessing or artificial feature extraction operations. In the proposed structure, a 5-layer CNN has been applied to learn EEG features, a 4-layer max pooling has been used to reduce dimensionality, and a fully-connected (FC) layer has been utilized for classification. Dropout and batch normalization are also employed to reduce the risk of overfitting. In the experiment, the 4 s EEG data of 10, 20, 60, and 100 subjects from the Physionet database are used as the data source, and the motor imaginations (MI) tasks are divided into four types: left fist, right fist, both fists, and both feet. The results indicate that the global averaged accuracy on group-level classification can reach 97.28%, the area under the receiver operating characteristic (ROC) curve stands out at 0.997, and the electrode pair with the highest accuracy on 10 subjects dataset is FC3-FC4, with 98.61%. The research results also show that this CNN classification method with minimal (2) electrode can obtain high accuracy, which is an advantage over other methods on the same database. This proposed approach provides a new idea for simplifying the design of BCI systems, and accelerates the process of clinical application.

High-Performance Image Filters via Sparse Approximations

We present a numerical optimization method to find highly efficient (sparse) approximations for convolutional image filters. Using a modified parallel tempering approach, we solve a constrained optimization that maximizes approximation quality while strictly staying within a user-prescribed performance budget. The results are multi-pass filters where each pass computes a weighted sum of bilinearly interpolated sparse image samples, exploiting hardware acceleration on the GPU. We systematically decompose the target filter into a series of sparse convolutions, trying to find good trade-offs between approximation quality and performance. Since our sparse filters are linear and translation-invariant, they do not exhibit the aliasing and temporal coherence issues that often appear in filters working on image pyramids. We show several applications, ranging from simple Gaussian or box blurs to the emulation of sophisticated Bokeh effects with user-provided masks. Our filters achieve high performance as well as high quality, often providing significant speed-up at acceptable quality even for separable filters. The optimized filters can be baked into shaders and used as a drop-in replacement for filtering tasks in image processing or rendering pipelines.

A Visual Tracking Method Based on an Adaptive Overlapping Correlation Filter for Robotic Real-Time Cognitive Imaging

Computer vision is a very important research direction in the cognitive computing field. Robots encounter various target-tracking problems with computer vision systems. Robust scale estimation is an important issue in tracking algorithms. Most of the available methods have difficulty addressing even reasonable changes of scale in complex videos. In this paper, we propose a visual tracking method based on robust scale estimation, which uses a discriminant correlation filter based on a time-dependent scale-space filter and an adaptive cross-correlation filter. The tracker uses separate essential filters for sample migration and scale estimation. Furthermore, the built-in scale estimation method can be introduced into other tracking algorithms. We validate the proposed method on the UAV123 dataset. The results of comparison experiments with the traditional correlation filter tracking method demonstrate that the proposed method improves the success rate and tracking accuracy while controlling the computational complexity; its success rate measured by the area under the curve is 0.638, while at a location error precision of 20%, it is 0.649.

One-step fabrication superhydrophobic sand filter for capillary-driven separation of water-in-oil emulsions

The efficient separation of water-in-oil emulsion is of significance in environment and energy filed, and it has become a world-wide challenge. Herein, we have presented a one-step, facile and low-cost approach to prepare superhydrophobic sands for efficient separation of water-in-oil emulsion. The as-prepared sand layers possessed a water contact angle higher than 151°, demonstrating their superior superhydrophobic property. Besides, the as-prepared sand layers could separate water-in-emulsions with separation efficiency up to 99.7%, which is superior to both traditional and superwettable filtration membranes. The effect of thickness of sand layer on separation performance was also investigated. The results showed that the filtration flux decreased with the increased of filtration thickness while the separation efficiency increased. The as-prepared sand layer proposed by this study is a processing candidate for separating water-in-oil emulsion in practical industry. Additionally, the as-prepared superhydrophobic sand fabrication method also provides an alternative for desert water storage.

All-polarization-maintaining, all-normal-dispersion mode-locked fiber laser with spectral filtering in a nonlinear optical loop mirror.

The spectral filtering effect is essential to dissipative dynamics in an all-normal-dispersion (ANDi) mode-locked fiber laser. In this study, we numerically and experimentally demonstrate the spectral filtering process of a nonlinear optical loop mirror (NOLM). Taking advantage of the 40/60 NOLM's spectral filtering ability, we designed a novel all-polarization-maintaining ANDi mode-locked fiber laser without using a separate spectral filter. The NOLM functions as an artificial saturable absorber and a spectral filter in an ANDi cavity. During mode locking, we observed that the NOLM decreased the spectral width of the pulse from 5.46 to 4.38 nm. The fiber laser generated 509-fs compressed pulses at the repetition rate of 13.4 MHz. Our work provides a promising novel and compact ANDi fiber laser for ultrafast photonic applications.

IAC-19-F4.1.8 The Family Portrait of the solar system: The last set of images taken by Voyager 1 and the fascinating story of how they came to be

On Valentine's Day, 1990 February 14, the Voyager-1 spacecraft executed a 60-image mosaic of portions of the Solar System, that came to be known as “The Family Portrait”. The set of observations was the 6th request by the Voyager Imaging Science Team, and Mission Planning Office. The fascinating story of why it took 8 years and 6 (ultimately 7) requests to gain approval has never been told.The Family Portrait taken by Voyager 1 remains the first, and still the only time, a spacecraft has attempted to photograph our home Solar System. Only 3 spacecraft have been capable of such an observation, Voyager 1, Voyager 2, and New Horizons. New Horizons just completed its second target body encounter in 2019 January. The observation opportunities have been few and far between in human history.The first Voyager-1 observation request consisted of a single set of 3 Wide Angle camera images of the Earth, and whatever other planetary objects occurred in the frame at the time. The Voyager Project denied the request, for many reasons. The next 3 requests followed this same observation design, with minor variations, with all disapproved. The 6th request intended to image 7 of the then 9 planets (all but Mercury and Pluto). The Voyager Project approved this request. The observation imaged 6 planets, with Mars too dim to detect. A 7th request intended to replicate the Voyager-1 observations on Voyager 2, but the Voyager Project denied this request.The Observation design consisted of slewing the cameras to Neptune, taking Narrow Angle images through 3 separate color filters plus 1 Wide Angle context image, taking a set of Wide Angle images from Neptune to Uranus, repeating the Narrow and Wide Angle images at Uranus, then stepping in turn to Saturn, Mars, Jupiter, Earth, and Venus. The observation concluded with a set of Wide-Angle context images around the Sun, with the final two images taken of the Sun itself.This paper discusses in depth the history of the 7 observation requests, the individuals involved in conceiving the various aspects of the ultimately successful observation set, the challenging spacecraft and project resource constraints, the resulting observation design and the phenomenal results. The image of Earth, the iconic Pale Blue Dot, shows us how small, tiny, and vulnerable “spaceship Earth” remains in the vast cosmos in which we live.

Selective solvent filters for non-aqueous phase liquid separation from water

Injectable filters permeable to water but impermeable to non-polar solvents were developed to contain non-aqueous phase liquids (NAPL) in contaminated aquifers, hence protecting downstream receptors during NAPL remediation. Filters were produced by injecting aqueous solutions of 0.01% chitosan, hydroxyethylcellulose and quaternized hydroxyethylcellulose into sand columns, followed by rinsing with water. Polymer sorption onto silica was verified using a quartz-crystal microbalance with dissipation monitoring. Fluorescence and gas chromatography mass spectroscopy showed low ppm range concentrations of non-polar solvents (e.g., hexane and toluene) in water eluted from the filters (in the absence of emulsifiers). The contact angles between polymer-coated surfaces and hexane or toluene were > 90°, indicating surface oleophobicity. Organic, polar solvents (e.g. tetrahydrofuran and tetrachloroethylene, TCE) were not separated from water. The contact angles between polymer-coated surfaces and TCE was also > 90°. However, the contact area with polymer coated surfaces was greater for TCE than non-polar solvents, suggesting higher affinity between TCE and the surfaces. Emulsifiers can be used to facilitate NAPL extraction from aquifers. Emulsion separation efficiency depended on the emulsifier used. Emulsions were not separated with classical surfactants (e.g. Tween 20 and oleic acid) or alkaline zein solutions. Partial emulsion separation was achieved with humic acids and zein particles.

Under-oil superhydrophilic TiO2/poly(sodium vinylphosphonate) nanocomposite for the separation of water from oil

Under-water superoleophobic filters lose their water separation capability if they are contaminated with oil. In contrast, an oil contaminant in a filter that is both superoleophobic underwater and superhydrophilic underoil can be readily displaced with water. Even after contamination by oil, such a filter can self-clean in water and re-create and maintain an integral water film in the pores to enable sustained water separation. Unfortunately, there have been only a few reported examples of under-oil superhydrophilic materials. We report herein a novel under-oil superhydrophilic material consisting of TiO2 nanoparticles that are coated by an excess of a sodium salt of poly(vinylphosphonic acid) (PVPA.nNa). This nanocomposite can be applied as a coating onto various substrates such as glass plate, glass wool, cotton ball, and stainless-steel metal mesh for permanent self-cleaning and hexadecane collection. More interestingly, a coated cotton ball could be affixed to the bottom end of a standing tube and allows the selective permeation of water from a stirred water/hexadecane mixture. Unfortunately, a coated metal mesh with larger pores and thus much higher water flux could not achieve the separation most likely because the weakness of the water film in the mesh pores induces a negative value of Laplace pressure. We achieve this separation for the coated metal mesh by attaching a thin electrospun superhydrophobic mat onto its lower side to thus yield a Janus filter. Our assumption is that the unidirectional upward water-pulling force of the Janus filter in this case helps to stabilize the water film in the metal mesh. Due to the facile synthesis of TiO2-PVPA·nNa and the demonstrated applications of the TiO2-PVPA·nNa coating, this study should inspire further research in high-flux filters for water separation from oil.

Genetic optimization of plasmonic metamaterial absorber towards dual-band infrared imaging polarimetry

Mid-infrared imaging detectors are essential tools for many applications because they can visualize the objects in the dark via thermal radiation. However, these detectors have to pair with separate spectral and polarization filters to select the target spectral bands and polarization states, resulting in complicated and bulky imaging systems. One way to mitigate the need for separate spectral filters and polarizers is to use metamaterial absorbers, which are arrays of optical resonators with sub-wavelength dimensions and spacing, to tailor the responses of the detector pixels. Here we report an intelligent program based on the genetic algorithm that automates the design and optimization of a metal-insulator-metal based metamaterial absorber with multi-sized nanostrip antennas as the top layer. The program starts from a randomly generated pattern of the top antenna layer, and it iteratively approaches the optimized designs of two polarization selective MIM absorbers with wideband high absorption in the specified 3-5 (MWIR) band and 8-12 µm (LWIR) band. The measured absorption spectra of the two optimized designs agree well with the simulated results. The influences of the incident angle of light, the finite size of detector pixels, and the air gap between the neighboring pixels on the spectral absorption are numerically evaluated.

Direct Position Determination of Moving Sources Based on Delay and Doppler

In this paper, we address the problem of direct position determination (DPD) for moving sources. Different from traditional two-step localization methods where the intermediate time difference of arrival (TDOA) and frequency difference of arrival (FDOA) parameters are estimated and used for the subsequent moving source localization, in this paper the locations and velocities of moving sources are estimated directly from the received signals. To address the difficulty of estimating the high-dimensional unknown parameters simultaneously, a new multiple particle filter based DPD method is proposed, where the position and velocity are updated alternately using separate local particle filters. The proposed method requires smaller particle numbers compared to the classic particle filters, and its convergence is proved both theoretically and numerically. Moreover, the Cramer Rao lower bound for the considered moving source DPD is developed. Simulation results corroborate the effectiveness of the proposed method in terms of computational efficiency and estimation accuracy.

Singular point region enhancement of fingerprint image based on symmetric phase consistency

Aiming at the problem that Separable Gabor filter can destroy the ridge structure of fingerprint adjacent singular points, and the effect of directional Fourier filter in repairing fingerprint ridges is not obvious, a method for singular point region

Laboratory Assessment of Water Permeability Loss of Geotextiles Due to Their Installation in Pervious Pavements

During the last decades, the importance of sustainable development in society has increased considerably. Sustainable Urban Drainage Systems (SUDS) are a group of techniques that aim to improve the management of rain and run-off water while reducing their pollution. Many of these systems incorporate geotextiles in their structures, which act as a layer separation and water filter. Some authors defend the idea that by simply being installed, geotextiles partially or totally lose their separation and filtering capacities. This study proposes a testing methodology that can reproduce this effect and obtain a reduction factor for the water permeability of the material after its installation, which is defined here as the ‘new condition factor’. The procedure simulated the real installation conditions in the laboratory by causing the specimen to undergo both mechanical and hydraulic damage and subsequently measuring the loss of water permeability that it provoked on the geotextile. Two different nonwoven geotextiles were tested in order to validate the procedure and to obtain initial results that could confirm the need for the new condition factor in the design of pervious pavements with geotextiles. Analysis of variance (ANOVA) was used to determine the statistical significance of the test variables.

Super-hydrophilic/oleophobic chitosan/acrylamide hydrogel: an efficient water/oil separation filter

Oil spills are one of the most serious problems which have a negative effect on our environment especially on the marine ecosystem. Thus, water/oil separation is considered as an important process to eliminate the oily pollutants. In the current study, a super-hydrophilic and super-oleophobic filter was prepared by in situ synthesis of chitosan/acrylamide hydrogel on the cotton fabric as a substrate. Different concentrations of chitosan and acrylamide monomers, cross-linking agent (MBA), and thermal initiator (APS) were tested by the Design Expert 7.0.0 Central Composite (CCD) software and the water absorption capacity of hydrogels were evaluated by a tea-bag method. The optimum concentration of MBA and APS was measured 0.03 g and 0.1 g, respectively. The optimal hydrogel-based filter was characterized by FTIR and SEM tests. The results confirm the successful synthesis of chitosan/acrylamide hydrogel with a porous structure on the cotton fabric. In addition, according to the results of the swelling study, the optimal synthesized hydrogel has high water retention capacity with a great stability in the seawater-simulated medium. Moreover, contact angle measurement and water/oil separation test demonstrate the super-hydrophilic/oleophobic behavior and high efficiency and durability of filter for water/oil separation.

Cost-effective Indoor Localization for Autonomous Robots using Kinect and WiFi Sensors

Indoor localization has been considered to be the most fundamental problem when it comes to providing a robot with autonomous capabilities. Although many algorithms and sensors have been proposed, none have proven to work perfectly under all situations. Also, in order to improve the localization quality, some approaches use expensive devices either mounted on the robots or attached to the environment that don't naturally belong to human environments. This paper presents a novel approach that combines the benefits of two localization techniques, WiFi and Kinect, into a single algorithm using low-cost sensors. It uses separate Particle Filters (PFs). The WiFi PF gives the global location of the robot using signals of Access Point devices from different parts of the environment while it bounds particles of the Kinect PF, which determines the robot's pose locally. Our algorithm also tackles the Initialization/Kidnapped Robot Problem by detecting divergence on WiFi signals, which starts a localization recovering process. Furthermore, new methods for WiFi mapping and localization are introduced.

SEMI-INDUSTRIAL TECHNOLOGY FOR SYNTHESIS OF TETRACYANOETHYLENE

The goal of our work is to develop a synthesis of tetracyanoethylene suitable for scaling and to design a technological scheme of the process based on it. To achieve this goal, a tetracyanoethylene synthesis method was originally developed, which consists of the following stages: obtaining sodium cyanodithioformate based on carbon disulfide and sodium cyanide using N, N-dimethylformamide as a solvent; obtaining tetracyano-1,4-dithiine by treating sodium cyanodithioformate with chlorine; obtaining tetracyanoethylene from tetracyano-1,4-dithiine by sequential interaction with sodium cyanide and chlorine. The developed method was tested in the laboratory, where it showed its suitability. Therefore, further on the base of this method, a technological scheme of the process was designed. A description of the scheme and the necessary sequence of operations are compiled. The interaction takes place in the reactors R-1, R-2, R-3. Pumps N-1–4 provided the pumping the reaction mass. Also, in the technological scheme there is an F-1 Nutsche filter for separation of the suspension. To isolate and purify the obtained tetracyanoethylene, an I-1 vacuum evaporator and a SA-1 sublimation apparatus are used. The necessary equipment was selected for the technological scheme: Р-1 reactor made of Teflon with a volume of 200 l with a stirrer and a jacket; two reactors Р-2 and Р-3 made of glass with a volume of 200 l with a stirrer and a jacket; Ф-1 Nutsche filter made of thick-walled polypropylene pipes; sublimation apparatus CA-1 continuous. The selection of the main and auxiliary equipment was carried out on the base of the chemical and physico-chemical characteristics of the reagents, technological conditions and the characteristics of the process. This method of obtaining compares favorably with the use of simple and cheap raw materials common in the chemical industry and the use of standard processing equipment.

JSI-GAN: GAN-Based Joint Super-Resolution and Inverse Tone-Mapping with Pixel-Wise Task-Specific Filters for UHD HDR Video

Joint learning of super-resolution (SR) and inverse tone-mapping (ITM) has been explored recently, to convert legacy low resolution (LR) standard dynamic range (SDR) videos to high resolution (HR) high dynamic range (HDR) videos for the growing need of UHD HDR TV/broadcasting applications. However, previous CNN-based methods directly reconstruct the HR HDR frames from LR SDR frames, and are only trained with a simple L2 loss. In this paper, we take a divide-and-conquer approach in designing a novel GAN-based joint SR-ITM network, called JSI-GAN, which is composed of three task-specific subnets: an image reconstruction subnet, a detail restoration (DR) subnet and a local contrast enhancement (LCE) subnet. We delicately design these subnets so that they are appropriately trained for the intended purpose, learning a pair of pixel-wise 1D separable filters via the DR subnet for detail restoration and a pixel-wise 2D local filter by the LCE subnet for contrast enhancement. Moreover, to train the JSI-GAN effectively, we propose a novel detail GAN loss alongside the conventional GAN loss, which helps enhancing both local details and contrasts to reconstruct high quality HR HDR results. When all subnets are jointly trained well, the predicted HR HDR results of higher quality are obtained with at least 0.41 dB gain in PSNR over those generated by the previous methods. The official Tensorflow code is available at https://github.com/JihyongOh/JSI-GAN.

Superhydrophobic–superoleophilic copper–graphite/styrene–butadiene–styrene based cotton filter for efficient separation of oil derivatives from aqueous mixtures

A superhydrophobic/superoleophilic cotton fabric composed of copper–graphite/styrene–butadiene–styrene (Cu–G/SBS) nanocomposites on the cellulose fibers has been fabricated and used as a filter for separation of gas condensates and oily solvents from aqueous mixture. First, hierarchical flower-like Cu–G nanocomposites were prepared by controlling the reduction reaction parameters such as type of reducing agent, surfactant, reaction time and weight ratio of copper to graphite. Thereafter, the coating composition of Cu–G and SBS mixtures were applied on the surface of cotton fabric by a facile dip-coating approach. Contact angle analysis of modified cotton fabric by Cu–G–SBS composites exhibited water contact angle and oil contact angle about 152° and 0°, respectively. When the superhydrophobic/superoleophilic cotton fabric was employed as a filter to separate oily solvent from water and high separation efficiency above 94% with good recyclability and stability was obtained. The result suggests that as-fabricated cotton fabric filter can be used for efficient oil/water separation in industrial applications.

A Novel Method for Removing Baseline Drifts in Multivariate Chemical Sensor

This article proposes a sensor signal processing method for removing baseline drifts in multimodal chemical sensors. Sensitivity and baseline drift are the primary reasons for inaccurate readings from low-cost sensors. The prediction errors from the state-of-the-art multivariate regression algorithms have been high due to the drifts. The response of a sensor is modeled as an autoregressive (AR) process associated with an observation zero-mean Gaussian noise. The parameters of the state-space model are learned using the calibration data. The variance of the Gaussian noise is estimated using an adaptive online method. The AR process equation and the observation equation are used to construct the adaptive Kalman filter. Each sensor response is passed through a separate Kalman filter, and then, a regression technique is used to predict the sensor response. The proposed model is applied to a standard air quality data set to demonstrate its efficacy in removing drifts in sensors.

Inside gel electromembrane extraction: A novel green methodology for the extraction of morphine and codeine from human biological fluids

In this work, a new mode of gel-electromembrane extraction (G-EME), called “inside” gel-EME (IG-EME) is proposed for the extraction of morphine and codeine as model basic drugs from complex biological samples. Here, an aqueous media that was captured inside the agarose gel membrane, acted as both gel membrane and the acceptor phase (AP) at the same time. In this regard, the membrane served as the separation filter (membrane) and supported liquid acceptor phase (SLAP) as well. With this new development, unwanted changes of the AP volume during the extraction, which is a common issue in the G-EME (due to electroendosmosis (EEO) phenomenon), was addressed properly. Briefly, the setup involved insertion of negative electrode inside the gel membrane and positive electrode into the donor phase (DP). Following that, the IG-EME was easily performed using optimal conditions (pH of the DP: 6.0; membrane composition (agarose concentration: 1% (w/v) in aqueous media with pH 3.0, and 15 mm thickness); voltage: 25 V; and extraction time: 30 min). After extraction, the agarose gel was withdrawn and centrifuged for 5 min with 12000 rpm, to disrupt its framework to release the “trapped aqueous AP” apart from the gel structure. The separated AP was finally injected into the HPLC-UV for the analysis. The limits of detection (LODs) and recoveries in this proposed method were obtained 1.5 ng mL−1 and 67.7 %–73.8 %, respectively. The system feasibility was examined by the quantification of model drugs in the real plasma and urine samples.