Development of a suitable model for characterizing photovoltaic arrays with shaded solar cells

The aim of this study is to investigate the effects of non-uniform solar irradiation distribution on energy output of different interconnected configurations in photovoltaic (PV) arrays. In order to find which configuration is less susceptible to mismatch effects, a PV module model is developed. This model can take into consideration the effects of bypass diodes and the variation of the equivalent circuit parameters with respect to operating conditions. The proposed model can provide sufficient degree of precision as well as solar cell-based analysis in analyzing large scale PV arrays without increasing the computational effort. In order to produce more reliable and robust simulations, improved and extended algorithms are presented. Some results are discussed in detail and some recommendations are extracted by testing several shading scenarios.     

The effects of periodontal therapy on serum antibody levels to Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis (part II)

Levels of IgG and IgM antibodies were estimated against Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis were determined by enzyme linked immunosorbent assay (ELISA) in 17 patients with juvenile periodontitis, 15 with adult periodontitis and 24 healthy controls at the beginning of treatment and 3 to 8 months after periodontal therapy. After treatment, antibodies to A. actinomycetemcomitans and P.gingivalis had decreased in patients, but the levels were still significantly higher than in healthy controls. Whether or not an of antibody level against a specific bacteria changes after periodontal treatment is however, still debatable.     

Surface modification of polyester and polyamide fabrics by low frequency plasma polymerization of acrylic acid

In this study, the surface characteristics of polyester and polyamide fabrics were changed by plasma polymerization technique utilizing acrylic acid as precursor. This monomer was used to produce hydrophilic materials with extended absorbency. The hydrophilicity, total wrinkle recovery angle (WRA°) and breaking strength of the fabrics were determined prior and after plasma polymerization treatment. The modification of surfaces was carried out at low pressure (<100 Pa) and low temperature (<50°C) plasma conditions. The effects of exposure time and discharge power parameters were optimized by comparing properties of the fabrics before and after plasma polymerization treatments. It was shown that two sides of polyester fabric samples were treated equally and homogeneously in plasma reactor. For polyester fabrics, the minimum wetting time, 0.5 s, was observed at two plasma processing parameters of 10 W–45 min and 10 W–20 min, where untreated fabric has a wetting time of 6 s. For polyester fabrics, the maximum value was obtained at 60 W–5 min with the wrinkle recovery angle of 306° where the untreated fabric has 290°. The optimum plasma conditions for polyamide fabrics were determined as 30 W–45 min where 2 s wetting time was observed. Wrinkle recovery angle of untreated polyamide fabric was 264°. In this study, after plasma polymerization of acrylic acid, wrinkle recovery angle values were increased by 13%. No significant change was observed in breaking strength of both fabrics after plasma treatment. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 104: 2318–2322, 2007     

Synthesis and properties of chitosan-modified poly(vinyl butyrate)

Modification of chitosan by grafting of vinyl butyrate was carried out in homogeneous phase using potassium persulfate as redox initator and 1.5% acetic acid as solvent. The percent grafting and grafting efficiency were analysed and the high grafting efficiency up to 94% was observed. The effects of reaction variables such as monomer concentration, initiator concentration, temperature and reaction time were investigated. It was observed that the solubility of chitosan was markedly reduced after grafting with vinyl butyrate. The grafted product is insoluble in common organic solvents as well in dilute organic and inorganic acids. Characterization of the graft copolymers were carried out by using Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC) and Scanning Electron Microscopy (SEM) technics. Characteristic signal of carbonyl group was observed at 1,731 cm⁻¹ which belongs to the poly vinyl butyrate segments in the graft copolymer. The melting transition of the chitosan main chain in the copolymer shifted to 124°C from its original value 101°C. In addition to these, we have also studied topology of the graft copolymer and the SEM micrograph showed continuous homogenous matrix which means there is no phase separation.     

Fine grinding of thermoplastics by high speed friction grinding assisted by guar gum

High speed friction grinding has been used to grind plant and food substances in water but never been explored for grinding of thermoplastics like polylactic acid (PLA), low and high density polyethylene and polypropylene. Such grinding was investigated in this work and was made possible by using 0.5% guar gum solution instead of just water because increasing the viscosity of water reduced their settling and the speed of passing through the grinder. Tensile, flexural, and impact strengths of the plastics were studied and higher grinding efficiency of PLA could be explained by its low elongation-at-break compared to low density polyethylene, high density polyethylene, and polypropylene. The microplastics (2000–45 μm) were studied for mass and particle size distributions and by scanning electron microscopy, ¹³C CP/MAS NMR, Fourier transform infrared spectroscopy, differential scanning calorimetry, and thermogravimetric analysis. In addition, viscosity of guar gum and contact angles was measured. This new technology can produce finely ground microplastics (710–45 μm) for a variety of applications.     

Is cheating a human function? The roles of presence,state hostility,and enjoyment in an unfair video game

In sports and board games, when an opponent cheats, the other players typically greet it with disdain, anger, and disengagement. However, work has yet to fully address the role of the computer cheating in video games. In this study, participants played either a cheating or a non-cheating version of a modified open-source tower-defense game. Results indicate that when a computer competitor cheats, players perceive the opponent as being more human. Cheating also increases player aggravation and presence, but does not affect enjoyment of the experience. Additionally, players that firmly believed that their opponent was controlled by the computer exhibited significantly less state hostility compared to players that were less certain of the nature of their competitor. Game designers can integrate subtle levels of cheating into computer opponents without any real negative responses from the players. The results indicate that minor levels of cheating might also increase player engagement with video games.     

Slip initiation on frictional fractures

Direct shear tests and biaxial compression tests are conducted to investigate the onset of slip along a non-homogeneous frictional surface and to determine the effect of specimen thickness and confining stress on slip initiation and propagation. The specimens are made of two and three acrylic blocks with the contact surfaces between blocks having on their upper half a frictional strength smaller than on their lower half. This creates a “weak” surface on the upper half and a “strong” surface on the lower half. The specimens are then loaded in direct shear or biaxial compression with confining pressures ranging from 0.7 to 3.5 MPa. The onset of slip, slip propagation, and the stress field generated at the front and center of the blocks interfaces are monitored using a photoelastic technique where a thin photoelastic film is placed at the location where observations are made. The onset of slip at the weak-strong zone interface is treated as propagation of a frictional crack under Mode II loading. The critical stress intensity factor, K_IIC, at the onset of slip is obtained from photoelastic techniques. The results show a weak dependency of K_IIC on the normal stress applied and no influence of the specimen size for specimens thicker than 25.4 mm; for thinner specimens the K_IIC values are smaller because the boundaries of the specimen prevent the full development of the stress field ahead of the crack tip. The experiments show a linear increase of the critical energy release rate with normal stress which is explained with linear elastic fracture mechanics theories.     

Towards quality requirements via animated formal specifications

Assuring a high quality requirements specification document involves both an early validation process and an increased level of participation. An approach and its supporting environment which combines the benefits of a formal system specification and its subsequent execution via a rapid prototype is reported. The environment assists in the construction, clarification, validation and visualisation of a formal specification. An illustrative case study demonstrates the consequences of assertions about system properties at this early stage of software development. Our approach involves the pragmatic combination of technical benefits of formal systems engineering based techniques with the context‐sensitive notions of increased participation of both developer and user stakeholders to move us closer towards a quality requirements specification document.     

Ensemble learning of diffractive optical networks

A plethora of research advances have emerged in the fields of optics and photonics that benefit from harnessing the power of machine learning.Specifically,there has been a revival of interest in optical computing hardware due to its potential advantages for machine learning tasks in terms of parallelization,power efficiency and computation speed.Diffractive deep neural networks(D²NNs)form such an optical computing framework that benefits from deep learning-based design of successive diffractive layers to all-optically process information as the input light diffracts through these passive layers.D²NNs have demonstrated success in various tasks,including object classification,the spectral encoding of information,optical pulse shaping and imaging.Here,we substantially improve the inference performance of diffractive optical networks using feature engineering and ensemble learning.After independently training 1252 D²NNs that were diversely engineered with a variety of passive input filters,we applied a pruning algorithm to select an optimized ensemble of D²NNs that collectively improved the image classification accuracy.Through this pruning,we numerically demonstrated that ensembles of N=14 and N=30 D²NNs achieve blind testing accuracies of 61.14±0.23%and 62.13±0.05%,respectively,on the classification of GFAR-10 test images,providing an inference improvennent of>16%compared to the average performance of the individual D²NNs within each ensemble.These results constitute the highest inference accuracies achieved to date by any diffractive optical neural network design on the same dataset and might provide a significant leap to extend the application space of diffractive optical image classification and machine vision systems.