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.     

Sodium and ultrafiltration profiling in hemodialysis: A long-forgotten issue revisited

Sodium and ultrafiltration profiling are method of dialysis in which dialysate sodium concentration and ultrafiltration rate are altered during the course of the dialysis session. Sodium and ultrafiltration profiling have been used, commonly simultaneously, to improve hemodynamic stability during hemodialysis. Sodium profiling is particularly effective in decreasing the incidence of intradialytic hypotension, while ultrafiltration profiling is suggested to decrease subclinical repeated end organ ischemia during dialysis. However, complications such as increased interdialytic weight gain and thirst due to sodium excess have prevented widespread use of sodium profiling. Evidence suggest that different sodium profiling techniques may lead to different clinical results, and preferring sodium balance neutral sodium profiling may mitigate adverse effects related to sodium overload. However, evidence is lacking on the long-term clinical outcomes of different sodium profiling methods. Optimal method of sodium profiling as well as the utility of sodium/ultrafiltration profiling in routine practice await further clinical investigation.     

Variable structure control of a class of uncertain systems

This brief paper proposes a method for tuning the parameters of a variable structure controller. The approach presented extracts the error at the output of the controller and applies a nonlinear tuning law using this error measure. The adaptation mechanism drives the state tracking error vector to the sliding hypersurface and maintains the sliding mode. In the simulations, the approach presented has been tested on the control of Duffing oscillator and the analytical claims have been justified under the existence of measurement noise, uncertainty and large nonzero initial errors.     

Evaluation of the Particle Bonding for Aluminum Sample Produced by Spark Plasma Sintering

Journal of Materials Engineering and Performance - Spark plasma sintering (SPS) is a powder metallurgy process that sinters powder materials within a short time by simultaneous application...     

Desulphiting dried apricots by exposure to hot air flow

Sulphited dried apricots were exposed to hot air flows at 40, 50 and 60 °C and the removal of SO₂ was investigated as their moisture content fell from an initial value of 193.2 g kg^?1 to a final value of 80–90 g kg^?1. A first‐order kinetic model was found for the removal of SO₂ between 40 and 60 °C. Temperature quotients (Q₁₀) for the removal of SO₂ were 2.84 between 40 and 50 °C and 4.93 between 50 and 60 °C; the activation energy (E_a) was 114.40 kJ mol^?1 between 40 and 60 °C. Analysis of the kinetic data also suggested a first‐order reaction for non‐enzymatic browning, with Q₁₀ values of 2.34 between 40 and 50 °C and 5.36 between 50 and 60 °C and an E_a value of 109.36 kJ mol^?1 between 40 and 60 °C. Exposure of dried apricots to a 60 °C air flow resulted in a rate constant for brown pigment formation that was 12 and 5 times higher than those at 40 and 50 °C respectively. © 2002 Society of Chemical Industry     

Adaptive control of let-off system in weaving

In this study, semi-positive let-off system in a conventional weaving loom was controlled using conventional, PID (Proportional Integral Derivative) and fuzzy logic based control systems. To do this, servomotor was installed into the let-off unit of the loom using PID controller, additionally fuzzy logic based let-off control was realised. Experimentally obtained warp tension values for each control methods were compared. According to the results, maximal tension values for the conventional, PID and fuzzy logic controlled systems were found to be 53, 45 and 35 cN, respectively. As a result, it is determined that the least warp tension interval and mean warp tension value are in let-off system controlled by fuzzy logic.     

More about fibre friction and its measurements

Unfortunately, the classical empirical friction laws do not hold true for fibrous and viscoelastic materials comprising most of the textile fibres. In the second half of the twentieth century, fibre surfaces have been studied by many distinguished scientists who were able to complete numerous researches for the frictional characteristics of different types of fibres. Most of the researchers have aimed to develop a new test method and a test device that can be used to measure the frictional characteristics of fibres quickly, accurately and easily in their studies. Unfortunately, there is not a standard test method or a test device for the measurement of textile fibres' friction properties. For today's competitive marketing, the instrument for fibre testing must be very fast and accurate; otherwise, it will not be useful for commercial purposes. For example, hundreds of thousands of cotton bales should be tested within a very short period of time in terms of the length, colour and trash content of the cotton bales. Without having the data describing the properties of cotton fibres, cotton bales cannot be sold commercially in most of the countries. Therefore, it is an important factor that the fibre-testing instrument should be fast and accurate. Most of the properties of cotton fibres can be assessed by using a HVI fibre-testing instrument. In this review, the historical perspective of fibre friction studies has been demonstrated with the fibre friction measurement-testing devices.     

TPS3: A privacy preserving data collection protocol for smart grids

Smart grid (SG) allows for two-way communication between the utility and its consumers and hence they are considered as an inevitable future of the traditional grid. Since consumers are the key component of SGs, providing security and privacy to their personal data is a critical problem. In this paper, a security protocol, namely TPS3, is based on Temporal Perturbation and Shamir’s Secret Sharing (SSS) schemes that are proposed to ensure the privacy of SG consumer’s data. Temporal perturbation is employed to provide temporal privacy, while the SSS scheme is used to ensure data confidentiality. Temporal perturbation adds random delays to the data collected by smart meters, whereas the SSS scheme fragments these data before transmitting them to the data collection server. Joint employment of both schemes makes it hard for attackers to obtain consumer data collected in the SG. The proposed protocol TPS3 is evaluated in terms of privacy, reliability, and communication cost using two different SG topologies. The performance evaluation results clearly show that the TPS3 protocol ensures the privacy and reliability of consumer data in SGs. The results also show that the tradeoff between the communication cost and security of TPS3 is negligible.