EXPRESS: Algorithmic governmentality and the space of ethics: Examples from 'People Analytics'

Does human reflexivity disappear as datafication and automation expand and machines take over decision-making? In trying to find answers to this question, we take our lead from recent debates about People Analytics and analyze how the use of algorithmically driven digital technologies like facial recognition and drones in work-organizations and societies at large shape the conditions of ethical conduct. Linking the concepts of algorithmic governmentality and space of ethics, we analyze how such technologies come to form part of governing practices in specific contexts. We conclude that datafication and automation have huge implications for human reflexivity and the capacity to enact responsibility in decision-making. But that itself does not mean that the space for ethical conduct disappears, which is the impression left in some literatures, but rather that is modified and (re) constituted in the interplay of mechanisms of closure (like automating decision-making, black-boxing and circumventing reflexivity), and opening (such as dis-closing contingent values and interests in processes of problematization, contestation and resistance). We suggest that future research investigates in more detail the dynamics of closure and opening in empirical studies of the use and effects of algorithmically driven digital technologies in organizations and societies.

The Ductility and Shape-Memory Properties of Ni–Mn–Ga–Cu Heusler Alloys

The effect of Cu addition on crystal structure, compressive properties and shape-memory effect of Ni50Mn25Ga25−xCux alloys was studied. With increasing Cu content, the type of crystal structure evolves following a sequence: L21 → 10M → 2M → 2M+γ. Addition of Cu significantly improves room temperature ductility. In polycrystalline Ni50Mn25Ga17Cu8 alloy, a full recoverable strain equal to 7 pct was achieved. High martensitic transformation temperature and large shape-memory effect makes this material potential candidate in high-temperature shape-memory applications.

The influence of multi-point roller-dies on the shape deviation differences of profile in flexible stretch-bending forming

In the process of flexible 3D stretch bending, the shape deviation difference between the contact zone and non-contact zone is studied. It is obvious that in the contact zone, the die regulates the deformation of the profile to make it conform to the target shape with small shape deviation; in the non-contact zone, the profile has no die restriction and deviates from the target shape with large shape deviation. When the dies are placed equidistantly along the x-axis, the shape deviation of the non-contact zone near the clamp side is greater than that near the middle of the profile. Arrange the distance between adjacent dies in equal ratio along the x-axis, so that the spacing near the clamp side is a little smaller, and the spacing near the middle of the profile is a bit larger. The difference between the shape deviation of the non-contact zone profile near the clamp side and the middle of the profile decreases, and the maximum shape deviation is reduced, which greatly improves the processing accuracy and quality. However, with the increase of the distance difference between adjacent dies, the shape deviation difference of the non-contact zone near the middle of the profile also increases greatly. Although the clamp side decreases, the maximum shape deviation has become the shape deviation of the profile in the non-contact zone near the middle of the profile.

Learning to Caricature via Semantic Shape Transform

Caricature is an artistic drawing created to abstract or exaggerate facial features of a person. Rendering visually pleasing caricatures is a difficult task that requires professional skills, and thus it is of great interest to design a method to automatically generate such drawings. To deal with large shape changes, we propose an algorithm based on a semantic shape transform to produce diverse and plausible shape exaggerations. Specifically, we predict pixel-wise semantic correspondences and perform image warping on the input photo to achieve dense shape transformation. We show that the proposed framework is able to render visually pleasing shape exaggerations while maintaining their facial structures. In addition, our model allows users to manipulate the shape via the semantic map. We demonstrate the effectiveness of our approach on a large photograph-caricature benchmark dataset with comparisons to the state-of-the-art methods.

High–load capacity origami transformable wheel

Composite membrane origami has been an efficient and effective method for constructing transformable mechanisms while considerably simplifying their design, fabrication, and assembly; however, its limited load-bearing capability has restricted its application potential. With respect to wheel design, membrane origami offers unique benefits compared with its conventional counterparts, such as simple fabrication, high weight-to-payload ratio, and large shape variation, enabling softness and flexibility in a kinematic mechanism that neutralizes joint distortion and absorbs shocks from the ground. Here, we report a transformable wheel based on membrane origami capable of bearing more than a 10-kilonewton load. To achieve a high payload, we adopt a thick membrane as an essential element and introduce a wireframe design rule for thick membrane accommodation. An increase in the thickness can cause a geometric conflict for the facet and the membrane, but the excessive strain energy accumulation is unique to the thickness increase of the membrane. Thus, the design rules for accommodating membrane thickness aim to address both geometric and physical characteristics, and these rules are applied to basic origami patterns to obtain the desired wheel shapes and transformation. The capability of the resulting wheel applied to a passenger vehicle and validated through a field test. Our study shows that membrane origami can be used for high-payload applications.