A new dynamic cellular learning automata-based skin detector

Skin detection is a difficult and primary task in many image processing applications. Because of the diversity of various image processing tasks, there exists no optimum method that can perform properly for all applications. In this paper, we have proposed a novel skin detection algorithm that combines color and texture information of skin with cellular learning automata to detect skin-like regions in color images. Skin color regions are first detected, by using a committee structure, from among several explicit boundary skin models. Detected skin-color regions are then fed to a texture analyzer which extracts texture features via their color statistical properties and maps them to a skin probability map. This map is then used by cellular learning automata to adaptively make a decision on skin regions. Conducted experiments show that the proposed algorithm achieves the true positive rate of about 86.3% and the false positive rate of about 9.2% on Compaq skin database which shows its efficiency.     

Conductive multichannel PCL/gelatin conduit with tunable mechanical and structural properties for peripheral nerve regeneration

Peripheral nerve injuries remain among the most challenging medical issues despite numerous efforts to devise methods in fabrication of nerve conduits to functionally regenerate axonal defects. In this regard, the current study offers a holistic perspective in design by considering the mechanical, topographical and structural aspects which are crucial for a successful nerve guide conduit. Poly(e-caprolactone) and gelatin were employed to serve this purpose in the form of dual-electrospun films which were rolled and later shaped the assembly of a multichannel conduit. Polyaniline/graphene (PAG) nanocomposite was incorporated to endow the conduit with conductive properties. FTIR analysis, water contact angle measurements, and SEM observations as well as mechanical and conductivity tests were used to evaluate the properties of the conduits. In addition, MTT assay was conducted to assess the proliferation of rat bone marrow-derived mesenchymal stem cells cultured on the films. Incorporating 2% PAG proved to have superior cell support and proliferation, while guaranteeing electrical conductivity of 10.8 × 10⁻⁵ S/cm and remarkable tensile strength of 3.52 ± 1.3 MPa and 14.12 ± 3.1 MPa for wet and dry conditions, respectively. Overall, the observed results highlight the great potential of the fabricated conduit to be used as a candidate for peripheral nerve defects.     

First-Principles Study of Elastic Constants and Interlayer Interactions of Complex Hydrated Oxides: Case Study of Tobermorite and Jennite

It is a common perception that layered materials are soft in the interlayer direction. Herein, we present results of first-principles calculations of the structure and elastic constants of a class for hydrated oxides, tobermorite, and jennite, which illustrate that this is not the case, if (1) the interlayer distance is such that coulombic interlayer interactions become comparable to the iono-covalent intralayer interactions and (2) the existence of interlayer ions and water molecules do not shield the coulombic interlayer interactions. In this case, the mechanically softest directions are two inclined regions that form a hinge mechanism. The investigated class of materials and results are relevant to chemically complex hydrated oxides such as layered calcium–silicate–hydrates (C–S–H), the binding phase of all concrete materials, and the principle source of their strength and stiffness. In addition, the first-principles results may serve as a benchmark for validating empirical force fields required for the analysis of complex calcio–silicate oxides.     

Color PCA eigenimages and their application to compression and watermarking

From the birth of multi-spectral imaging techniques, there has been a tendency to consider and process this new type of data as a set of parallel gray-scale images, instead of an ensemble of an n-D realization. However, it has been proved that using vector-based tools leads to a more appropriate understanding of color images and thus more efficient algorithms for processing them. Such tools are able to take into consideration the high correlation of the color components and thus to successfully carry out energy compaction. In this paper, a novel method is proposed to utilize the principal component analysis in the neighborhoods of an image in order to extract the corresponding eigenimages. These eigenimages exhibit high levels of energy compaction and thus are appropriate for such operations as compression and watermarking. Subsequently, two such methods are proposed in this paper and their comparison with available approaches is presented.     

Speech recognition

The authors have designed, successfully trained and tested an Arabic speech recognition system. This system was implemented using C++ programming language on Windows 95. It can be partitioned into five main modules. These modules are the front-end, feature extraction, training, pattern recognition and decision making and display. The front-end module functions as signal preparation and calibration. This includes: setting the signal sampling rate, removing the DC component from the signal, setting the scaling factor of the signal and detecting the endpoints of the utterance. The endpoint task removes the non-speech signal portions created by the speaker's pauses. This reduces the system computation time needed and the memory requirements. The feature extraction module is mainly a digital signal processor. The training module is the one that finds the best templates for every word or sound (phonemes) in the system's database. In short, this module needs to be executed only one time before users can utilize the system. The next module is the pattern recognition module. Its function is to compare the given utterance (test utterance) to all the stored templates (the reference module). The decision and display module functions as an interface between the user and the hidden system modules. In other words, after getting the recognition module results, this module displays the best candidate(s) and/or their likelihood percentage. The error rates are computed and displayed in this module     

Optimization of the water-based road-marking paint by experimental design, mixture method

The main purpose of this research is formulating and optimizing a new road-marking paint which is an environmentally friendly product. This paint is produced with an emulsion of an acrylic copolymer and contains the least of the volatile organic compounds. The formulation and optimization procedure is carried out on the base of experimental design by the method of mixture in which the important paint properties are modeled by using special cubic model. The present method has the capability of investigation the effect of raw materials at different levels with fewer experiments than factorial and fractional factorial design.

In this research, the main parameters such as resin, pigment and filler were selected at different levels, and different samples were prepared by combination of additives and other required reagents. The properties of wet and dry films of the samples were determined using ASTM test methods. Different responses such as pigment volume concentration (PVC), latex critical pigment volume concentration (LCPVC), abrasion resistance, hardness, gloss, no pick up time and surface drying time, were selected as the objective functions of this study. By running DX6 software, using special cubic model and selection of desired range of end-use properties, the region of optimum paint formula was determined.

The accuracy of the model was examined by preparing a sample in optimized region and by determining its final properties, experimentally. The results exhibit a good agreement between the model and experimental measurements. This product was compared with commercial solvent based traffic paint and good quality was reported in end-use properties.     

The acetylation and enzymatic degradation of starch films

The preparation of films from starch and their degradation by amylase enzymes is described. Starch acetate was prepared by acetylation of starch with a pyridine/acetic anhydride mixture. The resulting polymer was cast into films from solutions of 90% formic acid. A series of films with a range of acetyl content were then exposed to buffered amylase solutions and the retained tensile strength measured. It was found that with a sufficient acetyl content the wet strength of the films was maintained in the aqueous solutions, but that the acetyl content was sufficiently low enough to permit degradation by a mixture of alpha and beta amylases within a period of 1 h. These films could be useful as membranes in bioreactors, which could be degraded at will by the addition of enzymes to the system. © 1993 John Wiley & Sons, Inc.     

High calcium cementless fly ash binder with low environmental footprint: Optimum Taguchi design

Despite the myriad of research efforts on exploiting fly ash as an alternative binder, its current role in industry is largely restricted to the supplementary use, which enables only partial replacement of conventional portland cement. Herein, we propose an unprecedented binder composite with the promising early-age strength, which is cost-effective and reduces the CO₂ footprint compared with portland cement. The major constituent is fly ash occupying 76.4%-80.3% by the total mass of the constituents, while calcium oxide, nanosilica, and the minimum amounts of sodium-based activators are added to induce the early-age strength development. Optimization of the composition via the Taguchi design of experiments produced the early (7-day) compressive strength of 16.18 MPa. This value is encouraging considering that it is comparable to that of conventional portland cement and that a cementless composition with the minimum amounts of sodium-based activators was employed. The extensive materials analysis demonstrates that the starting Ca/Na molar ratio and the amount of nanosilica play instrumental roles in strength development by influencing the formation of key reaction products, which include the sodium-substituted AFm phase (the U-phase), katoite and portlandite. Overall, the promising early-age strength coupled with the significantly decreased amount of sodium-based chemicals and the reduced CO₂ footprint will lay a foundation for development of low-cost, environmentally friendly binder in diverse industries.     

Merger of Energetic Affinity and Optimal Geometry Provides New Class of Boron Nitride Based Sorbents with Unprecedented Hydrogen Storage Capacity

Hydrogen is an ideal synthetic fuel because it is lightweight, abundant and its oxidation product (water) is environmentally benign. However, its utilization is impeded by the lack of an efficient storage device. A new building block approach is proposed for an exhaustive search of optimal hydrogen uptakes in a series of low density boron nitride (BN) nanoarchitectures via extensive 3868 ab initio‐based multiscale simulations. By probing various geometries, temperatures, pressures, and doping ratios, these results demonstrate a maximum uptake of 8.65 wt% at 300 K, the highest hydrogen uptake on sorbents at room temperature without doping. Li⁺ doping of the nanoarchitectures offers a set of optimal combinations of gravimetric and volumetric uptakes, surpassing the US Department of Energy targets. These findings suggest that the merger of energetic affinity and optimal geometry in BN building blocks overcomes the intrinsic limitations of sorbent materials, putting hybrid BN nanoarchitectures on equal footing with hydrides while demonstrating a superior capacity‐kinetics–thermodynamics relationship.