AI ethics and systemic risks in finance

The paper suggests that AI ethics should pay attention to morally relevant systemic effects of AI use. It draws the attention of ethicists and practitioners to systemic risks that have been neglected so far in professional AI-related codes of conduct, industrial standards and ethical discussions more generally. The paper uses the financial industry as an example to ask: how can AI-enhanced systemic risks be ethically accounted for? Which specific issues does AI use raise for ethics that takes systemic effects into account? The paper (1) relates the literature about AI ethics to the ethics of systemic risks to clarify the moral relevance of AI use with respect to the imposition of systemic risks, (2) proposes a theoretical framework based on the ethics of complexity and (3) applies this framework to discuss implications for AI ethics concerned with AI-enhanced systemic risks.

Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review

The birth of mass production started in the early 1900s. The manufacturing industries were transformed from mechanization to digitalization with the help of Information and Communication Technology (ICT). Now, the advancement of ICT and the Internet of Things has enabled smart manufacturing or Industry 4.0. Industry 4.0 refers to the various technologies that are transforming the way we work in manufacturing industries such as Internet of Things, cloud, big data, AI, robotics, blockchain, autonomous vehicles, enterprise software, etc. Additionally, the Industry 4.0 concept refers to new production patterns involving new technologies, manufacturing factors, and workforce organization. It changes the production process and creates a highly efficient production system that reduces production costs and improves product quality. The concept of Industry 4.0 is relatively new; there is high uncertainty, lack of knowledge and limited publication about the performance measurement and quality management with respect to Industry 4.0. Conversely, manufacturing companies are still struggling to understand the variety of Industry 4.0 technologies. Industrial standards are used to measure performance and manage the quality of the product and services. In order to fill this gap, our study focuses on how the manufacturing industries use different industrial standards to measure performance and manage the quality of the product and services. This paper reviews the current methods, industrial standards, key performance indicators (KPIs) used for performance measurement systems in data-driven Industry 4.0, and the case studies to understand how smart manufacturing companies are taking advantage of Industry 4.0. Furthermore, this article discusses the digitalization of quality called Quality 4.0, research challenges and opportunities in data-driven Industry 4.0 are discussed.

Engineering sensitivity and spectral range of photodetection in van der Waals materials and hybrids

Exploration of van der Waals heterostructures in the field of optoelectronics has produced photodetectors with very high bandwidth as well as ultra-high sensitivity. Appropriate engineering of these heterostructures allows us to exploit multiple light-to-electricity conversion mechanisms, ranging from photovoltaic, photoconductive to photogating processes. These mechanisms manifest in different sensitivity and speed of photoresponse. In addition, integrating graphene-based hybrid structures with photonic platforms provides a high gain-bandwidth product, with bandwidths >> 1 GHz. In this review, we discuss the progression in the field of photodetection in 2D hybrids. We emphasize the physical mechanisms at play in diverse architectures and discuss the origin of enhanced photoresponse in hybrids. Recent developments in 2D photodetectors based on room temperature detection, photon-counting ability, integration with Si and other pressing issues, that need to be addressed for these materials to be integrated with industrial standards have been discussed.

Windtech – A Sensory Device for ‘Cold’ Sensation Measurements

Windtech device is a novel tool for measuring the sensation of the ‘cold’. Cold poses numerous challenges for industrial operations, human survival, and living convenience. The impact of the cold is not possible to be quantified just based on temperatures; however other factors such as wind speed, humidity, irradiance have to be taken into consideration. Efforts have been made to develop combined indices such as wind chill temperature (WCT), AccuWeather RealFeel®, and others. The presented article discusses these along with the industrial standards that emphasize on the quantification of the ‘cold’. The following article introduces the Windtech device and its operating principle involving ‘heated temperature’, where the ‘heated temperature’ is affected by environmental parameters including ambient temperature, humidity, wind velocity, and irradiance. The discussed Windtech device is calibrated for operation according to the ISO 11079:2007 standard.

New Mainstream Films and Television Dramas in China: The Construction of Industrial Aesthetics and Consumption of Youth Culture

As a significant industrial and cultural phenomenon, the rise of new mainstream films and TV dramas in China embodies the inclusion of multiple cultures (mainstream culture, grassroot culture, youth culture, etc.) and the respect for diverse audiences. In particular, such trends bring into focus the youth market and explore the image-based expression of youth culture, subculture and fashion culture. However, this author argues that the production of such films and TV dramas also needs to further pursue market-orientated strategies, sustainable development, and conformity to industrial standards. In short, the production of new mainstream films and TV dramas should not revert to the previous production pattern of mainstream films.

Deformation Characteristics in a Stretch-Based Dimensional Correction Method for Open, Thin-Walled Extrusions

Dimensional accuracy of incoming components is crucial for automated welding and assembly in mass volume production. However, thin-walled extrusions made to industrial standards show severe dimensional variations, including gap opening, sidewall inclination, local convexity, and so on. Thus, one major challenge is to provide a low-cost correction method to improve the dimensional accuracy at a level demanded by automated assembly and/or product fit-up. A novel correction method called transverse stretch and local bending (TSLB) has recently been developed, enabling one to efficiently correct the dimensional deviations in thin-walled, U-channel profiles at a low cost. However, the lack of in-depth understanding of the underlying mechanism makes it challenging to efficiently optimise and control the process. In this study, the feasibility of this new technique was experimentally validated by four groups of TSLB tests with different profile dimensions, showing a dimensional accuracy improvement of about 92% compared with the as-received parts. The evolution of the critical dimensional characteristics, including gap opening and bottom convexity, is analysed numerically throughout four stages consisting of inserting, releasing, calibration, and springback. It is found that the inserting stage greatly reduces the dimensional deviations in a pure bending state, while the calibration stages further minimise the deviations in the bending and transverse stretching combined state. In addition, the wedge angle of the tool is found to be critical to the dimensional accuracy improvement. The low wedge angle facilitates the correction of sidewall inclination and gap opening, while the high wedge angle contributes to mitigating bottom convexity. The overall outcome of this study enhances the fundamental understanding of the effects of in-process stretching and local-bending on the dimensional capabilities of U-channel extrusions. This can ultimately generate guidelines that will lead to new application areas of aluminium extrusions in highly competitive marketplaces.

Analytical Model and Numerical Analysis of Composite Wrap System Applied to Steel Pipeline

Composite overwraps are a cost-effective repair technology, appropriate for corrosion defects, dents, and gouges for both onshore and offshore steel pipelines. The main benefit of polymer-based sleeves is safe installation without taking the pipeline out of service. This paper presents a new calculation procedure proposed in the form of an algorithm for the sizing of composite repairs of corroded pipelines when the sleeve is applied at zero internal pressure. The main objective of the presented methodology is determination of the effective thickness of the composite repair without its overestimation or underestimation. The authors used a non-linear finite element method with constitutive models allowing analysis of the steel, putty, and composite structures. The validation of the results of numerical computations compared to the experimental ones showed an appropriate agreement. The numerical calculations were applied to compare the analytical results in relation to those obtained by the standards ASME PCC-2 or ISO/TS 24817. The comparison showed that the proposed solution confirmed its effectiveness in reducing the thickness of the sleeve significantly, thus, showing that the current industrial standards provide a considerably excessive composite wrap around the steel pipe corroded area, which leads to an unnecessary increase in the repair costs.

Wafer-scale functional circuits based on two dimensional semiconductors with fabrication optimized by machine learning

Triggered by the pioneering research on graphene, the family of two-dimensional layered materials (2DLMs) has been investigated for more than a decade, and appealing functionalities have been demonstrated. However, there are still challenges inhibiting high-quality growth and circuit-level integration, and results from previous studies are still far from complying with industrial standards. Here, we overcome these challenges by utilizing machine-learning (ML) algorithms to evaluate key process parameters that impact the electrical characteristics of MoS2 top-gated field-effect transistors (FETs). The wafer-scale fabrication processes are then guided by ML combined with grid searching to co-optimize device performance, including mobility, threshold voltage and subthreshold swing. A 62-level SPICE modeling was implemented for MoS2 FETs and further used to construct functional digital, analog, and photodetection circuits. Finally, we present wafer-scale test FET arrays and a 4-bit full adder employing industry-standard design flows and processes. Taken together, these results experimentally validate the application potential of ML-assisted fabrication optimization for beyond-silicon electronic materials.

Alkali-treated wheat gluten cross-linked with sodium alginate as a bio-based wood adhesive for interior grade particleboard

A bio-based wood adhesive formulation free of formaldehyde and made from alkali-treated wheat gluten (WG) and sodium alginate (SA) was developed. Its formulation was optimised, and it was characterised by Fourier Transform Infrared (FT-IR) spectroscopy. The bio-adhesive was utilized to make particleboards both with virgin wood particles and recycled wood particles. A dry bio-adhesive content of 35% (w/w) was used to make samples with both type of particles. Single-layer samples of 10 mm thickness were obtained using wood particles of 1 mm (both virgin and recycled). These samples then were subjected to 3-point bending tests. Whereas the bending strength of samples made with recycled wood particles was 18.09 N/m2 and therefore satisfied Type 18 of the Japanese industrial standards (JIS A 5908:2015), the bending strength of the samples made with virgin wood particles was 8.08 N/m2 and satisfied ‘Type 8 Base particleboard Decorative particleboard’ of the Japanese standards. The density of particleboard samples made from recycled wood particles was 916 kg/m3, while that of samples made from virgin wood particles was 732 kg/m3. The alkali-treated WG and SA bio-adhesive has the potential to be used to re-manufacture particleboards, which can then be recycled and not disposed in landfills.