Multi-Order Statistical Descriptors for Real-Time Face Recognition and Object Classification

We propose novel multi-order statistical descriptors which can be used for high speed object classification or face recognition from videos or image sets. We represent each gallery set with a global second-order statistic which captures correlated global variations in all feature directions as well as the common set structure. A lightweight descriptor is then constructed by efficiently compacting the second-order statistic using Cholesky decomposition. We then enrich the descriptor with the first-order statistic of the gallery set to further enhance the representation power. By projecting the descriptor into a low-dimensional discriminant subspace, we obtain further dimensionality reduction, while the discrimination power of the proposed representation is still preserved. Therefore, our method represents a complex image set by a single descriptor having significantly reduced dimensionality. We apply the proposed algorithm on image set and video-based face and periocular biometric identification, object category recognition, and hand gesture recognition. Experiments on six benchmark data sets validate that the proposed method achieves significantly better classification accuracy with lower computational complexity than the existing techniques. The proposed compact representations can be used for real-time object classification and face recognition in videos. 2013 IEEE.This work was supported by NPRP through the Qatar National Research Fund (a member of Qatar Foundation) under Grant 7-1711-1-312.Scopu

Comparative analysis of computer-vision and BLE technology based indoor navigation systems for people with visual impairments

Background: Considerable number of indoor navigation systems has been proposed to augment people with visual impairments (VI) about their surroundings. These systems leverage several technologies, such as computer-vision, Bluetooth low energy (BLE), and other techniques to estimate the position of a user in indoor areas. Computer-vision based systems use several techniques including matching pictures, classifying captured images, recognizing visual objects or visual markers. BLE based system utilizes BLE beacons attached in the indoor areas as the source of the radio frequency signal to localize the position of the user. Methods: In this paper, we examine the performance and usability of two computer-vision based systems and BLE-based system. The first system is computer-vision based system, called CamNav that uses a trained deep learning model to recognize locations, and the second system, called QRNav, that utilizes visual markers (QR codes) to determine locations. A field test with 10 blindfolded users has been conducted while using the three navigation systems. Results: The obtained results from navigation experiment and feedback from blindfolded users show that QRNav and CamNav system is more efficient than BLE based system in terms of accuracy and usability. The error occurred in BLE based application is more than 30% compared to computer vision based systems including CamNav and QRNav. Conclusions: The developed navigation systems are able to provide reliable assistance for the participants during real time experiments. Some of the participants took minimal external assistance while moving through the junctions in the corridor areas. Computer vision technology demonstrated its superiority over BLE technology in assistive systems for people with visual impairments. - 2019 The Author(s).Scopu

Designing carbon nanotube-based oil absorbing membranes from gamma irradiated and electrospun polystyrene nanocomposites

Carbon-based materials are outstanding candidates for oil spill clean-ups due to their superhydrophobicity, high surface area, chemical inertness, low density, recyclability, and selectivity. The current work deals with the fabrication of membrane oil absorbents based on carbon nanotube (CNT) reinforced polystyrene (PS) nanocomposites by electrospinning technique. The spun membranes are also irradiated with the gamma radiation to induce enough crosslinks and thus good polymer-filler interactions. The structural, morphological, and surface properties in addition to the oil/water separation efficiency were investigated by varying the concentration of CNT and the dose of γ-irradiation. Fabricated nanofiber membranes show superior hydrophobicity and selective oil absorption at 0.5 wt.% of CNT concentration. The best mechanical properties are also obtained at this particular concentration and at 15 KGy optimum γ-irradiation dosage. The gamma irradiated PS/0.5 wt.% CNT membrane also exhibits good antibacterial effects against the bacteria, Escherichia coli, in the form of bacterial inhibition rings around the membranes. The present study thus shows the environmental applicability of the fabricated PS/CNT membranes in treating oil-contaminated water

Inorganic Porous Materials Based Epoxy Self-Healing Coatings

The long-term stability of protective coating for metal is critically important for structural applications [1, 2]. Self-healing ability extend the service life of protective coatings leading to a significant reduction in maintenance cost for oil and gas pipe lines and structural parts in civil and construction industry. Recently, the self-healing technology based on healing agent loaded containers has been receiving attention [3, 4]. The incorporation of self- healing agent loaded containers into polymer matrix can be carried out using existing blending techniques. Hence, this technology facilitate large-scale application of self-healing materials [5]. Different micro or nano containers has been used for the storage and release of self-healing agents upon specific corrosion triggering conditions (e.g. on pH change) or upon mechanical damage [6]. Polymer capsules, polymer nanofibers, hollow glass bubbles, hollow glass fibers etc. were used by the researchers to load the healing agent inside their cavity. The inorganic particles with nano cavity offers large surface area, high pore volume and good stability favorable for the storage of the healing agents. Moreover, the usage of inorganic nanomaterials as reservoirs for healing agent can eliminate the tedious encapsulation process. The present study aims to use inorganic nanotubes and mesoporous silica as containers for healing agents in epoxy coating. The ability of Halloysite nanotubes (HNT), titanium dioxide (TiO2) nanotube and mesoporous silica to load and release the healing agents are investigated and compared their performance. Among them, Halloysite nanotubes are naturally occurring clay mineral. Meanwhile, TiO2 nanotube and mesoporous silica are synthesised in laboratory and characterised using scanning electron microscopic (SEM), transmission electron microscopic (TEM) techniques and Brunauer-Emmett-Teller (BET) surface area analysis. The morphology of the nanotubes and mesoporous silica are shown in Fig. 1 (in supporting file). In this study, the epoxy pre-polymer and hardener are used as healing agents. Containers loaded with epoxy and hardener can provide a repair system with matching chemical entity with host epoxy coating. Both epoxy encapsulated nanotubes (either Halloysite or TiO2 nanotubes) and amine immobilized mesoporous silica are incorporated into epoxy, followed by the addition of diethylenetriamine curing agent. The mixture is coated on the metal with an average thickness of 300 ?m. The controlled epoxy coatings are also prepared without nanotube and mesoporous silica. Epoxy coating loaded with encapsulated Halloysite nanotubes and immobilized mesoporous silica is abbreviated as 'EP/HNT/SiO2' and the one loaded with encapsulated TiO2 nanotubes and immobilized mesoporous silica is abbreviated as 'EP/ TiO2/SiO2'. The self-healing ability of the scratched coatings is monitored by electrochemical impedance spectroscopy (EIS) in definite time intervals for 5 days. Both EIS bode plots and tafel polarization curves are analysed to observe the self-healing ability of the coatings. For the scratched controlled epoxy coating, after an immersion time of 24 hours, the impedance curve drop to its minimum value over the entire frequency range and on further immersion period the impedance curve remains its minimum value. However, in the case of self-healing coatings, the initially declined impedance value recovers in successive days. The recovery in low frequency impedance values (at 0.01 Hz), which is a direct reflection of the recovery of corrosion resistance of the coating are evaluated. While EP/TiO2/SiO2 coating recovered 57% of its anticorrosive property, the EP/HNT/SiO2 coating recovered only 0.026%. This results suggest that the nature of the nanotubes affect the amount and rate of healing agent released into the scratched area from the tube lumen which itself affect the self-healing ability of the coating. SEM is also used to observe the healed scratches on the coatings. After 96 hours of immersion in 3.5 wt% NaCl solution, the scratches in EP/TiO2/SiO2 self-healing coatings are found to be almost covered. The results confirm the effective self-healing ability of the EP/TiO2/SiO2 coating in which the released epoxy pre-polymer from nanotube lumen get contact with the amine hardener immobilized in mesoporous silica and cross-link to cover the scratch. Acknowledgment: This abstract was made possible by PDRA grant # PDRA1-1216-13014 from the Qatar national research fund (a member of Qatar foundation).qscienc

Antimicrobial Modification of LDPE Using Non-thermal Plasma

Low-density polyethylene (LDPE) represents polymer having good chemical and physical characteristics for which it is widely used in many applications, such as biomedical and food packaging industry. This polymer excels by good transparency, flexibility, low weight and cost which makes it suitable material compared to non-polymer packaging materials. However, its hydrophobicity cause many limitations for antimicrobial activity which can result in absence of some characteristics required in food packaging applications. For that purpose, some researches have done experiments to modify the polymer surface to increase the surface free energy (hydrophilicity). This can be done by introducing some polar functional groups into the LDPE surface which will permit an increment of its surface free energy and so its wettability or adhesion without any disruption in its bulk properties [1]. One of the most preferable modification techniques is known as non-thermal radio-frequency discharge plasma, and it is preferred technique due to the ability to modify only thin surface layer leading to noticable improvement of the surface properties [2].Moreover, it represents environmentally friendly technique since it does not require the use of any hazardous chemicals or dangerous radiations and therefore non-thermal plasma is highly recommended for food packaging applications [1]. In addition, the surface modification of LDPE can lead to the enhancement of the antimicrobial activity, which was the main purpose of this research. Food packaging materials requires preventing any growth of bacteria, fungal, or any other microbial organisms for health and food safety. Some approved preservatives are commonly used directly in foods to preserve them form microorganisms growth and spoilage. Nowadays, some innovative ways are applied to graft acrylic acid on polymers surfaces [3] for biomedical applications to create an effective layer for an immobilization of antibacterial agents and this results in bacteria prevention on the LDPE surface. In this research, we focused on grafting of sorbic acid as one of the most commonly used preservatives in food and beverage for being safe, and effective in bacteria inhibition (whether pathogenic strains or spoilage kinds), molds, and yeasts [4]. It is also used in cosmetic industries since it has good compatibility with skin and it is easily usable [5]. For the potential enhancement of the antimicrobial efficiency, chitosan representing antimicrobial agent was used for the immobilization on sorbic acid created layer. Chitosan (a derivative of chitin polysaccharide) was chosen as a natural occurring antimicrobial agent (from crabs shrimps, and other sea shells [5]) that has strong and effective antimicrobial activity along with its nontoxicity, biofunctionality, biodegradability, and biocompatibility [6]. In this study, the LDPE surface was modified by several modification steps. The first step involved the modification of the LDPE surface by non-thermal radio-frequency discharge plasma as a radical graft initiator for the subsequently polymerization of sorbic acid containing double bonds. In the next step, grafting of sorbic acid was carried out immediately after plasma treatment allowing the interaction of plasma created radicals on LDPE surface with sorbic acid. Final step was focused on the immobilization of chitosan on grafted sorbic acid platform. Each modification step was analyzed by different analytical techniques and methods to obtain detailed information about the modification process. The surface parameters changes after modification of the LDPE surface, such as surface free energy (contact angles measurements), graft yield (gravimetric measurements) surface morphology (scanning electron microscopy and atomic force microscopy) and chemistry (Fourier transform infrared spectroscopy with attenuated total reflectance) were obtained allowing understanding the modification process.Qscienc

End-to-end image steganography using deep convolutional autoencoders

Image steganography is used to hide a secret image inside a cover image in plain sight. Traditionally, the secret data is converted into binary bits and the cover image is manipulated statistically to embed the secret binary bits. Overloading the cover image may lead to distortions and the secret information may become visible. Hence the hiding capacity of the traditional methods are limited. In this paper, a light-weight yet simple deep convolutional autoencoder architecture is proposed to embed a secret image inside a cover image as well as to extract the embedded secret image from the stego image. The proposed method is evaluated using three datasets - COCO, CelebA and ImageNet. Peak Signal-to-Noise Ratio, hiding capacity and imperceptibility results on the test set are used to measure the performance. The proposed method has been evaluated using various images including Lena, airplane, baboon and peppers and compared against other traditional image steganography methods. The experimental results have demonstrated that the proposed method has higher hiding capacity, security and robustness, and imperceptibility performances than other deep learning image steganography methods

Bidirectional Parallel Capacitive Data Links: Modeling and Experimental Results

We present, in this paper, a bidirectional capacitive data link. Enhancement of the spatial pulse position modulation used on the downlink is introduced, and a load-shift keying modulation is implemented for the uplink. Different grounds on the transmitter and the receiver are discussed, and a compatible solution is proposed. A human skin electrical model is extracted using the agilent impedance analyzer 4294A while doing in vivo measurements on cheek skin and then applying curve fitting to the data between 2 and 20 MHz. Multiple geometries for the link are analyzed, and a 5-mm × 5-mm plate size is used for the design of the transceiver. The signal-to-noise ratio along with the capacity of the channel is analyzed theoretically while computing the limits for the downlink and the valid operating frequency to highlight the core parameters that affect the crosstalk interference between channels. The tradeoff in using the uplink on the same channel as the downlink is also discussed and analyzed. The operating frequency is 10 MHz, a bit-rate of 20 Mb/s is demonstrated on the uplink, and 10 Mb/s is demonstrated on the downlink. An in vivo human skin model for a 5-mm × 5-mm plate size with 21.2-mm separation is extracted, and the capacity's equation of the channel is computed using the equations for the analysis of the system.This work was supported by the Natural Sciences and Engineering Research Council of Canada, Canada. The authors would like to acknowledge the financial support from the Canada Research Chair in Smart Medical Devices and the design tools from CMC Microsystems.Scopu

Handwriting-Based Gender Classification Using End-to-End Deep Neural Networks

Handwriting-based gender classification is a well-researched problem that has been approached mainly by traditional machine learning techniques. In this paper, we propose a novel deep learning-based approach for this task. Specifically, we present a convolutional neural network (CNN), which performs automatic feature extraction from a given handwritten image, followed by classification of the writer's gender. Also, we introduce a new dataset of labeled handwritten samples, in Hebrew and English, of 405 participants. Comparing the gender classification accuracy on this dataset against human examiners, our results show that the proposed deep learning-based approach is substantially more accurate than that of humans

Some theoretical aspects of tertiary treatment of water/oil emulsions by adsorption and coalescence mechanisms: A review

The massive increase in the volumes of oily contaminated produced waters associated with various industrial sectors has initiated considerable technological and scientific efforts related to the development of new cleaning strategies. The petrochemical industry (oil and gas production and processing) contributes to those volumes by approximately 340 billion barrels per year. The removal of emulsified oily components is a matter of particular interest because the high emulsion stability necessitates sophisticated technological approaches as well as a deep theoretical understanding of key mechanisms of oil/water separation. This review deals with the theoretical aspects of the treatment of emulsified oil/water mixtures and is particularly focused on tertiary treatment, which means the reduction of the oil content from 70-100 ppm to below 10 ppm, depending on national regulations for water discharge. The review concerns the mechanisms of oil/water separation and it covers the (i) adsorption isotherms, (ii) kinetics of adsorption, (iii) interfacial interactions between oil/water mixtures and solid surfaces, and (iv) oil/water separation techniques based on the wettability of solid/oil/water interfaces. The advantages and drawbacks of commonly used as well as newly proposed kinetic and adsorption models are reviewed, and their applicability for the characterization of oil/water separation is discussed. The lack of suitable adsorption isotherms that can be correctly applied for a description of oil adsorption at external and internal solid surfaces of both nonporous and porous structures is pointed out. The direct using of common isotherms, which were originally developed for gas adsorption, often leads to the incorrect data description because the adsorption of oily components at solid surfaces does not fit the assumptions from which these models were originally derived. Particularly, it results in problematic calculations of the thermodynamic parameters of sorption. The importance of nonlinear analysis of data is discussed, since recent studies have indicated that the error structure of experimental data is usually changed if the original nonlinear adsorption isotherms are transformed into their linearized forms. The comparison between the pseudo-first-order and pseudo-second-order kinetic models was performed. It was shown that the correlation between data and models strongly depends on the selection of data, particularly on the frequency of collected data in time scale. The wettability of solid surfaces by oil in air and under water is discussed, regarding the surface morphology of surfaces. We demonstrate that the combination of surface chemistry and topology strongly influences the separation of oil/water emulsions.This work was made possible by a grant from the Qatar National Research Fund under its National Priorities Research Program (award number NPRP12S-0311-190299) and by financial support from the ConocoPhillips Global Water Sustainability Center (GWSC). The paper?s content is solely the responsibility of the authors and does not necessarily represent the official views of the Qatar National Research Fund or ConocoPhillips. This research was also funded by Qatar University through Qatar University Collaborative Grant QUCGCAM- 20/21-4.Scopu