Generative adversarial network-based semi-supervised learning for pathological speech classification

A challenge in applying machine learning algorithms to pathological speech classification is the labelled data shortage problem. Labelled data acquisition often requires significant human effort and time-consuming experimental design. Further, for medical applications, privacy and ethical issues must be addressed where patient data is collected. While labelled data are expensive and scarce, unlabelled data are typically inexpensive and plentiful. In this paper, we propose a semi-supervised learning approach that employs a generative adversarial network to incorporate both labelled and unlabelled data into training. We observe a promising accuracy gain with this approach compared to a baseline convolutional neural network trained only on labelled pathological speech data

Investigation into the characteristics of proton exchange membrane fuel cell-based power system

© The Institution of Engineering and Technology.Fuel cells (FCs) use hydrogen as their prime fuel source, which promotes them as one of the attractive options for clean energy generators. Though they have been around for some time, their characteristics are not yet fully understood. This study offers a thorough investigation into the characteristics of proton exchange membrane (PEM) type of FCs based power system. This study first presents a concise explanation of the working principles of the PEM electrolyser and FCs supported by novel modelling using MATLAB. The simulation results are then validated by a series of experiments carried out on operational 500 mW FC followed by detailed performance parameters of such type of FCs. Parameters affect the efficiencies of each part of the system are investigated and the total system's efficiency is then calculated. The efficiency of the electrolyser and PEM FC was found to be 85 and 60%, respectively. Polarisation curve has been used in order to evaluate FC's performance. From the polarisation curve, it is noted the efficiency of the FC increases with increasing pressure and temperature. The activation losses are reduced when the temperature increased. Moreover, the mass transfer is enhanced toward reducing the PEMFC's resistance

Prediction of the shelf-life of date seeds brew by integration of acceptability and quality indices

The storage shelf life of brews has become progressively important in recent years for the beverage’s manufacturers. The objectives of this study were to investigate the proximate composition and mineral contents of the proposed roasted date seeds powders, to model the kinetic changes in the properties of the brews during storage and to establish a predictive model for forecasting the shelf life by integration of consumer acceptability and quality attributes of the brews. Foremost, the chemical composition and mineral content analysis of both full fat and low-fat powders were investigated using the standard methods. The brews were prepared using hot water and then stored up to 30 days at 4, 25, 38 °C. Samples of brews were taken initially and after 2, 4, 6, 12, 18, 24 and 30 days for conducting pH measurement and sensory evaluation. Kinetic modelling for the properties were conducted by applying the nonlinear regression technique. Besides, the shelf life of the brews was predicted by integration of the acceptability and quality indicators. The results revealed that pH, H3O+ and sensory attributes of the brews were significantly influenced by the storage conditions. Descriptive models have been developed for describing the different properties and the shelf life of brews. In addition, the brews were microbiologically stable during the predicted shelf life period under different storage temperatures and times

Broadband semiconductor light sources operating at 1060 nm based on InAs:Sb/GaAs submonolayer quantum dots

In this paper, we investigate the potential of submonolayer-grown InAs:Sb/GaAs quantum dots as active medium for opto-electronic devices emitting in the 1060 nm spectral range. Grown as multiple sheets of InAs in a GaAs matrix, submonolayer quantum dots yield light-emitting devices with large material gain and fast recovery dynamics. Alloying these structures with antimony enhances the carrier localization and red shifts the emission, whereas dramatically broadening the optical bandwidth. In a combined experimental and numerical study, we trace this effect to an Sb-induced bimodal distribution of localized and delocalized exciton states. While the former do not participate in the lasing process, they give rise to a bandwidth broadening at superluminescence operation and optical amplification. Above threshold laser properties like gain and slope efficiency are mainly determined by the delocalized fraction of carriers

Dictionary learning for fast classification based on soft-thresholding.

Classifiers based on sparse representations have recently been shown to provide excellent results in many visual recognition and classification tasks. However, the high cost of computing sparse representations at test time is a major obstacle that limits the applicability of these methods in large-scale problems, or in scenarios where computational power is restricted. We consider in this paper a simple yet efficient alternative to sparse coding for feature extraction. We study a classification scheme that applies the soft-thresholding nonlinear mapping in a dictionary, followed by a linear classifier. A novel supervised dictionary learning algorithm tailored for this low complexity classification architecture is proposed. The dictionary learning problem, which jointly learns the dictionary and linear classifier, is cast as a difference of convex (DC) program and solved efficiently with an iterative DC solver. We conduct experiments on several datasets, and show that our learning algorithm that leverages the structure of the classification problem outperforms generic learning procedures. Our simple classifier based on soft-thresholding also competes with the recent sparse coding classifiers, when the dictionary is learned appropriately. The adopted classification scheme further requires less computational time at the testing stage, compared to other classifiers. The proposed scheme shows the potential of the adequately trained soft-thresholding mapping for classification and paves the way towards the development of very efficient classification methods for vision problems

Differential phase shift quantum key distribution with variable loss revealing blinding and control side-channel attacks

Realistic quantum key distribution (QKD) systems suffer from side-channel attacks, which manipulate single-photon detectors. Although measurement-device-independent QKD schemes were proposed to free QKD parties (Alice and Bob) from such measurement devices, these schemes are not easy to be implemented in practice because they require precise synchronization between signals from distant parties. On the other hand, differential phase shift (DPS) QKD is a simple system for practical implementation with current optical equipment. In this study, we propose a simple modification in DPS QKD to prevent side-channel attacks (control blinding and controlling attacks) such that Bob randomly attenuates the incoming signal. This modification allows Bob to utilize photon statistics during attenuated time slots in DPS-QKD systems, using which the side-channel attacks are revealed

Some physicochemical properties of dextrin produced by extrusion process

Dextrinization of corn starch by twin screw extruder was studied. The effect of extruder operating conditions (five different screw speeds: 35, 45, 55, 65, and 70; and three temperatures: 125, 130, and 135 °C) on some physicochemical properties of dextrin (total soluble solid, water absorption index, water solubility index, and total color difference) was investigated. Results showed that as the screw speed and temperature of extrusion were increased the water absorption index of dextrin tended to drop meanwhile the total soluble solid, water solubility index, and color were inclined to rise. The range of total soluble solid, water absorption index, water solubility index and total color difference was 2.1–4.6 Brix, 159–203%, 20–51%, 3.5–14.1, respectively

Monitoring coincident clicks in differential-quadrature-phase shift QKD to reveal detector blinding and control attacks

Side-channel attacks manipulating single-photon detectors (SPDs) have known to be loopholes in realistic quantum key distribution (QKD) systems. Although measurement-device-independent (MDI) QKD schemes have been proposed and studied to avoid those loopholes, they are not easy to implement in practice because they Require some synchronization between signals sent from two distant parties. In this paper, we propose a new countermeasure against a side-channel attack (control blinding and controlling attacks). It utilizes coincident clicks in differential-quadrature-phase shift (DQPS) QKD systems. Our scheme requires no change in the system configuration of the conventional protocol. Unlike MDI-QKD, side-channel attacks can be found without difficulty in practical implementations

Competitive online algorithm for leasing wireless channels in 3-tier sharing framework

Abstract To meet the ever growing need for wireless spectrum, the Federal Communication Commision (FCC) introduced a spectrum sharing model called the 3-Tier Sharing Framework. In this model, under-utilized federal spectrum will be released for shared use where the highest preference will be given to Tier-1 followed by Tier-2 and then Tier-3. In this paper, we present a model where a wireless operator, who is interested in maximizing its profit, can operate as a Tier-2 and/or a Tier-3 user. Tier-2 is characterized by paid but “almost” guaranteed and interference free channel access while Tier-3 access is free but has lesser guarantee and also faces channel interference. So the operator has to optimally decide between paid but better channel quality and free but degraded channel quality. Also, the operator has to make these decisions without knowing future market parameters like customer demands or channel availability. We use tools from ski-rental literature to design a deterministic online algorithm for leasing channels which does not rely on the knowledge of market statistics. The efficiency of the online algorithm is analyzed by deriving its competitive ratio (CR) and by conducting simulations. The mathematical model for leasing channels is a novel generalization of the classical ski-rental problem. We therefore make fundamental contribution to ski-rental literature which may have diverse applications beyond the problem considered in this paper