Automatic recognition fingerspelling gestures in multiple languages for a communication interface for the disabled

This paper presents the design and evaluation of a multi-lingual fingerspelling recognition module that is designed for an information terminal. Through the use of multimodal input and output methods, the information terminal acts as a communication medium between deaf and blind people. The system converts fingerspelled words to speech and vice versa using fingerspelling recognition, fingerspelling synthesis, speech recognition and speech synthesis in Czech, Russian, and Turkish languages. We describe an adaptive skin color based fingersign recognition system with a close to real-time performance and present recognition results on 88 different letters signed by five different signers, using above four hours of training and test videos.     

3D Printing of Polyvinylidene Fluoride Based Piezoelectric Nanocomposites: An Overview

Recently, polyvinylidene fluoride (PVDF) based nanocomposites have attracted much attention for next-generation wearable applications such as promising piezoelectric energy harvesters (nanogenerators), energy storage devices, sensing devices, and biomedical devices due to their high flexibility, and high dielectric and piezoelectric properties. 3D printing technology, PVDF based piezoelectric nanocomposites, the studies based on 3D printing of PVDF based piezoelectric nanocomposites by inkjet printing and fused deposition modeling, and enhancements of energy harvesting and storage performance of nanocomposites by structural design are comprehensively overviewed here. An insight is provided into 3D printing techniques, structure and properties of PVDF based polymers, various nanofillers and production methods for nanocomposites, solutions to enhance β phase (crystallinity) of PVDF, and improvements of nanocomposites’ breakdown strength, discharged energy density, and piezoelectric power output by mentoring structural design.     

The role of plasticizer on the exfoliation and dispersion and fracture behavior of clay particles in PVC matrix: a comprehensive morphological study

The clay nanoparticles are readily dispersed and exfoliated in the PVC matrix with the help of Dioctyl phthalate (DOP) plasticizer. X-ray, TEM and AFM analysis of the nanocomposites indicate that there is an optimum concentration of DOP for the process. If used in high concentrations, the ability to transfer forces to the clay particles through the polymer matrix decreases due to substantial decrease in viscosity. The individual platy montmorillonite particles dispersed in PVC matrix were directly observed by AFM and found to lie preferentially on their basal surfaces, especially when the compounded batch is compression molded. The edges of the particles were in some cases straight forming hexagonal angles and in other cases irregular.     

Friction and adsorption properties of normal and high-oleic soybean oils

The steel/steel boundary friction properties of soybean oil (SBO) and high-oleic soybean oil (HOSBO) are compared. HOSBO is significantly more saturated than SBO and more oxidatively stable. Changes in degree of unsaturation affect lateral interactions of adsorbate molecules, which in turn affects their adsorption and, hence, their boundary lubrication properties. To investigate this possibility, the free energies of adsorption (ΔG _ads) of SBO, HOSBO, and methyl laurate (ML) were determined from the analysis of friction-derived adsorption isotherms using the Langmuir and Temkin adsorption models. The results showed a stronger adsorption for the vegetable oils than for ML, an indication of multiple interactions between the ester groups of the triglycerides and the steel surface. The result also showed no difference in the ΔG _ads values of SBO and HOSBO obtained using either the Langmuir or Temkin models. This was interpreted as an indication of the lack of appreciable net lateral interaction between triglyceride adsorbates.     

πSynthesis and evaluation of a series of α-hydroxy ethers derived from isopropyl oleate

Several fatty derivatives with bulky moieties were prepared by treatment of epoxidized isopropyl oleate with a number of alcohols in the presence of sulfuric acid catalyst to provide a series of α-hydroxy ethers in good yield. The materials were analyzed for cold flow performance through cloud point and pour point determinations. The most promising α-hydroxy ether produced in this study, with respect to both low temperature behavior and economic criteria, was isopropyl 9(10)-(2-ethylhexoxy) 10(9)-hydroxystearate, which has a cloud point of −23°C and pour point of −24°C.     

Effects of composition and phase relations on mechanical properties and crystallization of silicate glasses

Crystallization, mechanical properties, and workability are all important for the commercialization and optimization of silicate glass compositions. However, the inter-relations of these properties as a function of glass composition have received little investigation. Soda-lime-silica glasses with Na₂O-MgO-CaO-Al₂O₃-SiO₂ compositions relevant to commercial glass manufacture were experimentally studied and multiple liquidus temperature and viscosity models were used to complement the experimental results. Liquidus temperatures of the fabricated glasses were measured by the temperature gradient technique, and Rietveld refinements were applied to X-Ray powder diffraction (XRD) data for devitrified glasses, enabling quantitative determination of the crystalline and amorphous fractions and the nature of the crystals. Structural properties were investigated by Raman spectroscopy. Acoustic echography, micro-Vicker's indentation, and single-edge-notched bend testing methods were used to measure Young's moduli, hardness, and fracture toughness, respectively. It is shown that it is possible to design lower-melting soda-lime-silica glass compositions without compromising their mechanical and crystallization properties. Unlike Young's modulus, brittleness is highly responsive to the composition in soda-lime-silica glasses, and notably low brittleness values can be obtained in glasses with compositions in the wollastonite primary phase field: an effect that is more pronounced in the silica primary phase field. The measured bulk crystal fractions of the glasses subjected to devitrification at the lowest possible industrial conditioning temperatures indicate that soda-lime-silica glass melts can be conditioned close to their liquidus temperatures within the compositional ranges of the primary phase fields of cristobalite, wollastonite, or their combinations.     

Integrated Risk of Progress-Based Costs and Schedule Delays in Construction Projects

This article aims to explore the impact of the integration of risk factors into delayed milestones for construction projects. A simulation model was developed to determine the impact of schedule variability on cost estimation. To generate random scenarios a Monte Carlo Simulation (MCS) technique was applied. The developed model computes the cost impact of delayed milestone in the expected budget. Using a risk integration approach revealed the critical time frame that may lead to a budget deficit for a project. As a result, a number of cost-sensitive risk factors and schedule delays were identified for the critical time period where the risk of budget deficit increases. The method of integration proposed in this article highlights the priority of risk factors and schedule delays for construction contracts involving Payments at Event Occurrences (PEO). Consequently, the developed method can be useful for practitioners in anticipation of potential increase of costs, hence, prevention of failure due to budget deficit.     

A genetic algorithm based heuristic for scheduling of virtual manufacturing cells (VMCs)

We present a genetic algorithm (GA) based heuristic approach for job scheduling in virtual manufacturing cells (VMCs). In a VMC, machines are dedicated to a part as in a regular cell, but machines are not physically relocated in a contiguous area. Cell configurations are therefore temporary, and assignments are made to optimize the scheduling objective under changing demand conditions. We consider the case where there are multiple jobs with different processing routes. There are multiple machine types with several identical machines in each type and are located in different locations in the shop floor. Scheduling objective is weighted makespan and total traveling distance minimization. The scheduling decisions are the (i) assignment of jobs to the machines, and (ii) the job start time at each machine. To evaluate the effectiveness of the GA heuristic we compare it with a mixed integer programming (MIP) solution. This is done on a wide range of benchmark problem. Computational results show that GA is promising in finding good solutions in very shorter times and can be substituted in the place of MIP model.     

Multi-objective rule mining using a chaotic particle swarm optimization algorithm

In this paper, classification rule mining which is one of the most studied tasks in data mining community has been modeled as a multi-objective optimization problem with predictive accuracy and comprehensibility objectives. A multi-objective chaotic particle swarm optimization (PSO) method has been introduced as a search strategy to mine classification rules within datasets. The used extension to PSO uses similarity measure for neighborhood and far-neighborhood search to store the global best particles found in multi-objective manner. For the bi-objective problem of rule mining of high accuracy/comprehensibility, the multi-objective approach is intended to allow the PSO algorithm to return an approximation to the upper accuracy/comprehensibility border, containing solutions that are spread across the border. The experimental results show the efficiency of the algorithm.     

An upper bound on the minimum number of monomials required to separate dichotomies of {-1, 1}n

It is known that any dichotomy of {-1, 1}n can be learned (separated) with a higher-order neuron (polynomial function) with 2n inputs (monomials). In general, less than 2n monomials are sufficient to solve a given dichotomy. In spite of the efforts to develop algorithms for finding solutions with fewer monomials, there have been relatively fewer studies investigating maximum density (Pi(n)), the minimum number of monomials that would suffice to separate an arbitrary dichotomy of {-1, 1}n . This article derives a theoretical (upper) bound for this quantity, superseding previously known bounds. The main theorem here states that for any binary classification problem in {-1, 1}n (n > 1), one can always find a polynomial function solution with 2n -2n/4 or fewer monomials. In particular, any dichotomy of {-1, 1}n can be learned by a higher-order neuron with a fan-in of 2n -2n/4 or less. With this result, for the first time, a deterministic ratio bound independent of n is established as Pi(n)/2n < or = 0 75. The main theorem is constructive, so it provides a deterministic algorithm for achieving the theoretical result. The study presented provides the basic mathematical tools and forms the basis for further analyses that may have implications for neural computation mechanisms employed in the cerebral cortex.