SoK: Training Machine Learning Models over Multiple Sources with Privacy Preservation

Nowadays, gathering high-quality training data from multiple data controllers with privacy preservation is a key challenge to train high-quality machine learning models. The potential solutions could dramatically break the barriers among isolated data corpus, and consequently enlarge the range of data available for processing. To this end, both academia researchers and industrial vendors are recently strongly motivated to propose two main-stream folders of solutions: 1) Secure Multi-party Learning (MPL for short); and 2) Federated Learning (FL for short). These two solutions have their advantages and limitations when we evaluate them from privacy preservation, ways of communication, communication overhead, format of data, the accuracy of trained models, and application scenarios. Motivated to demonstrate the research progress and discuss the insights on the future directions, we thoroughly investigate these protocols and frameworks of both MPL and FL. At first, we define the problem of training machine learning models over multiple data sources with privacy-preserving (TMMPP for short). Then, we compare the recent studies of TMMPP from the aspects of the technical routes, parties supported, data partitioning, threat model, and supported machine learning models, to show the advantages and limitations. Next, we introduce the state-of-the-art platforms which support online training over multiple data sources. Finally, we discuss the potential directions to resolve the problem of TMMPP.Comment: 17 pages, 4 figure

Inferring Economic Condition Uncertainty from Electricity Big Data

Inferring the uncertainties in economic conditions are of significant importance for both decision makers as well as market players. In this paper, we propose a novel method based on Hidden Markov Model (HMM) to construct the Economic Condition Uncertainty (ECU) index that can be used to infer the economic condition uncertainties. The ECU index is a dimensionless index ranges between zero and one, this makes it to be comparable among sectors, regions and periods. We use the daily electricity consumption data of nearly 20 thousand firms in Shanghai from 2018 to 2020 to construct the ECU indexes. Results show that all ECU indexes, no matter at sectoral level or regional level, successfully captured the negative impacts of COVID-19 on Shanghai's economic conditions. Besides, the ECU indexes also presented the heterogeneities in different districts as well as in different sectors. This reflects the facts that changes in uncertainties of economic conditions are mainly related to regional economic structures and targeted regulation policies faced by sectors. The ECU index can also be easily extended to measure uncertainties of economic conditions in different fields which has great potentials in the future

3D printing and epoxy-infusion treatment of curved continuous carbon fibre reinforced dual-polymer composites

A manufacturing technique was developed to fabricate curved continuous carbon fibre reinforced composites based on 3D printing and epoxy-infusion treatment. Composite preforms were first manufactured by material-extrusion based 3D printing of continuous carbon fibre reinforced thermoplastic polyamide-6 (PA-6) filaments. Powder thermoset epoxy was added to the preforms to fill up the gaps, remove air voids and enhance the interfacial bonding through a traditional vacuum bagging and oven curing process. Uniaxial tensile tests showed that the stiffness and strength of the printed composites were increased by 29.3% and 22.1%, respectively, compared to the thermoplastic-only composite specimens. The epoxy-infusion treatment technique was also adopted to manufacture composites with curved fibre alignment and investigate the performance of 3D printed notched specimens under uniaxial tension. It was shown that the placement of continuous carbon fibres along the principal stress trajectories increased the failure strength and the fracture toughness of the composites by 81% and 157% respectively, compared to the unidirectional and concentric placement methods

“Lock-in” Effect of Emission Standard and Its Impact on the Choice of Market Based Instruments

A country’s existing emission standard policy will lead to a “lock in” effect. When the country plans to adopt new market-based instruments to control greenhouse gas emissions, it must consider this effect as it chooses among instruments to avoid larger efficiency loss. In this paper, we find that the “lock in” effect will cause a kink point to occur on the marginal abatement cost (MAC) curve. This change of shape for the MAC curve reminds us to be cautious in choosing market-based instruments when applying Weitzman’s rule. We also introduce this concept into a dynamic multi-regional computable general equilibrium (CGE) model for China and simulate MAC curves for all regions. After applying Weitzman’s rule, we propose a timeline for introducing price instruments under different marginal benefit (MB) curve scenarios

Effects of thermal process conditions on crystallinity and mechanical properties in material extrusion additive manufacturing of discontinuous carbon fibre reinforced polyphenylene sulphide composites

This study investigates the thermal behaviour of discontinuous carbon fibre reinforced polyphenylene sulphide (CF/PPS), additively manufactured by material extrusion, with a focus on the effects of thermal process conditions on the degree of crystallinity, oxidation crosslinking and mechanical properties of CF/PPS from filament fabrication, material extrusion to annealing treatment. The screw extrusion parameters are optimised by performing a thermal analysis of the fabricated filaments. The effect of crosslinking reactions on the crystallinity process in determining the mechanical properties of the printed samples is illustrated by investigating the influence of the printing conditions. Furthermore, the effect of annealing treatment on the semi-crystalline polyphenylene sulphide (PPS) is studied by measuring the degree of crystallinity and viscoelasticity behaviours. Results demonstrate that the flexural properties of the printed CF/PPS composites at elevated processing temperatures are determined by the oxidation crosslinking between PPS chains. These enhance the crystallisation process of semi-crystalline polymers by acting as the nucleating agent first but negatively affect the mechanical properties at higher temperatures because of the detrimental effects of the polymer inter-chain bonding. The maximum flexural strength of printed CF/PPS reached 164.65 MPa when processing at an extrusion temperature of 280°C, a printing temperature of 320°C, and an annealing temperature of 130°C for 6 h. By adjusting the thermal treatment conditions, the degree of the crystallinity and the mechanical properties of the printed CF/PPS composites can be designed, controlled and tailored