Experience goals in designing professional tools : evoking meaningful experiences at work

For most adults, work is an important part of life. Experiences at work are shaped considerably by the workplace context wherein professional tools often play a crucial role. Given this significance, this doctoral research is concerned with human flourishing at work as mediated by professional tools and work-related service touchpoints. This dissertation concentrates on prioritising meaningful experiences as high-level design goals in the early phase of the design process, which enables a creative approach to professional tool innovation. In the last three decades, the societal change from the materialistic to the experiential has boosted business-to-consumer design practices with a focus on experiential quality. Compelling consumer experiences in daily life have raised the bar of people’s expectations for desirable experiences at work. In contrast, current work tool design in the business-to-business setting is mainly driven by product performance criteria, system productivity, and cost efficiency. The value of meaningful experiences at work as a catalyst for employee flourishing seems largely neglected in work tool design. This dissertation therefore proposes to shift the orientation of work tool design from product-centred problem solving towards experience-focused possibility seeking. This research follows Hassenzahl’s proposition of experience design, to think intended experiences before concrete design outcome. To maintain the designers’ focus on experiential objectives throughout the design process, this dissertation introduces a key conceptual instrument of inquiry into design practice, namely, the experience goal (Xgoal). This dissertation defines Xgoals as high-level design objectives that concretise the intended momentary emotion or lasting meaning that a person feels about a product or service to be designed. The main challenges of Xgoal setting and realisation correspond to a design abduction process in which designers constantly experiment with tentative Xgoals until a preferable match between the two emerges. Thus, this research investigates Xgoal setting and utilisation for work tool design in the specific context of the Finnish metals and engineering industry where traditional problem-solving engineering design dominates. Theoretically, this research utilises the multidisciplinary lenses of positive psychology, organisational management, and possibility-driven design thinking to study Xgoals in creative design practice. Methodologically, this dissertation extracts data from 20 master student projects that collaborated with heavy industry companies. These projects were deliberately designed for meaningful experiences at work in relation to professional tool innovation. The analysis of these project reports emphasises design reasoning for Xgoal setting and utilisation in design activities. Finally, Xgoals as designerly instruments were evaluated in expert interviews. The findings of this research first indicate that Xgoals with in-depth meaning can lead a possibility-driven design process because Xgoals define the in-depth reason for design opportunities rather than a means to a solution. Xgoals can facilitate the considered design space expansion from the main product towards a product-service system and from styling towards human-product interaction, face-to-face communication, and organisational strategy. Second, the findings suggest that the mechanisms of meaningful work can complement a Positive Design Framework, and further propose Xgoals in terms of design for virtue, personal significance and pleasure intertwined with the meaningfulness of work. Third, this research uncovers design strategies for experiences of pride at work along social and temporal dimensions. Finally, this dissertation suggests the generative, reflective, and communicative functions of Xgoals in design practice. This research contributes a theory-inspired and design case-based approach to tool design for evoking meaningful experiences at work. Future studies on this could concentrate on applying the proposed framework and design strategies to other domains, and further develop context-dependent Xgoal setting and utilisation methods for possibility-driven design

Multiscale Modelling Of Platelet Aggregation

During clotting under flow, platelets bind and activate on collagen and release autocrinic factors such ADP and thromboxane, while tissue factor (TF) on the damaged wall leads to localized thrombin generation. Toward patient-specific simulation of thrombosis, a multiscale approach was developed to account for: platelet signaling (neural network trained by pairwise agonist scanning, PAS-NN), platelet positions (lattice kinetic Monte Carlo, LKMC), wall-generated thrombin and platelet-released ADP/thromboxane convection-diffusion (PDE), and flow over a growing clot (lattice Boltzmann). LKMC included shear-driven platelet aggregate restructuring. The PDEs for thrombin, ADP, and thromboxane were solved by finite element method using cell activation-driven adaptive triangular meshing. At all times, intracellular calcium was known for each platelet by PAS-NN in response to its unique exposure to local collagen, ADP, thromboxane, and thrombin. The model accurately predicted clot morphology and growth with time on collagen/TF surface as compared to microfluidic blood perfusion experiments. The model also predicted the complete occlusion of the blood channel under pressure relief settings. Prior to occlusion, intrathrombus concentrations reached 50 nM thrombin, ~1 μM thromboxane, and ~10 μM ADP, while the wall shear rate on the rough clot peaked at ~1000-2000 sec-1. Additionally, clotting on TF/collagen was accurately simulated for modulators of platelet cyclooxygenase-1, P2Y1, and IP-receptor. The model was then extended to a rectangular channel with symmetric Gaussian obstacles representative of a coronary artery with severe stenosis. The upgraded stenosis model was able to predict platelet deposition dynamics at the post-stenotic segment corresponding to development of artery thrombosis prior to severe myocardial infarction. The presence of stenosis conditions alters the hemodynamics of normal hemostasis, showing a different thrombus growth mechanism. The model was able to recreate the platelet aggregation process under the complex recirculating flow features and make reasonable prediction on the clot morphology with flow separation. The model also detected recirculating transport dynamics for diffusible species in response to vortex features, posing interesting questions on the interplay between biological signaling and prevailing hemodynamics. In future work, the model will be extended to clot growth with a patient cardio-vasculature under pulsatile flow conditions

Towards High Performance Video Object Detection

There has been significant progresses for image object detection in recent years. Nevertheless, video object detection has received little attention, although it is more challenging and more important in practical scenarios. Built upon the recent works, this work proposes a unified approach based on the principle of multi-frame end-to-end learning of features and cross-frame motion. Our approach extends prior works with three new techniques and steadily pushes forward the performance envelope (speed-accuracy tradeoff), towards high performance video object detection

Atomic Layer Deposition (ALD) film characterization

This report shows deposition characteristics for aluminum oxide (Al2O3), hafnium oxide (HfO2), and titanium dioxide (TiO2) films deposited in the Cambridge Nanotech Savannah system. A brief study of the presence of pinholes in these films is also presented

Flow-Guided Feature Aggregation for Video Object Detection

Extending state-of-the-art object detectors from image to video is challenging. The accuracy of detection suffers from degenerated object appearances in videos, e.g., motion blur, video defocus, rare poses, etc. Existing work attempts to exploit temporal information on box level, but such methods are not trained end-to-end. We present flow-guided feature aggregation, an accurate and end-to-end learning framework for video object detection. It leverages temporal coherence on feature level instead. It improves the per-frame features by aggregation of nearby features along the motion paths, and thus improves the video recognition accuracy. Our method significantly improves upon strong single-frame baselines in ImageNet VID, especially for more challenging fast moving objects. Our framework is principled, and on par with the best engineered systems winning the ImageNet VID challenges 2016, without additional bells-and-whistles. The proposed method, together with Deep Feature Flow, powered the winning entry of ImageNet VID challenges 2017. The code is available at https://github.com/msracver/Flow-Guided-Feature-Aggregation

The Effect of High School Program and University Study Length on Taiwanese EFL University Students’ Motivational Identities and Learning Strategy Use

Language learning strategies and motivational selves are two important factors that contribute to language learning success. Examining these variables and discovering what impacts them can help learners to understand their own motivation and strategy use and help teachers formulate better lesson plans and instruction. Besides being independent variables, they have also been shown to be related to one another. This study seeks to examine the impact of high school program and current year of study on Taiwanese university English majors’ motivational selves and language learning strategy choices. Using the SILL and a Motivational Self Systems questionnaire, data was collected from 96 students across all four undergraduate years at a private Taiwanese university. The results show that there are correlations between motivational factors and some types of learning strategies. However, there were no significant differences among the sample according to either high school program or current year of study. It is suggested that other factors, such as geographical location of the students’ homes or the economic level of the students’ families may have an impact. Future research should continue to explore these phenomena. Keywords: Language learning strategies, L2 motivation, Motivational self system, EFL students, SILL DOI: 10.7176/JLLL/53-0

Flexible Neural Electrode Array Based-on Porous Graphene for Cortical Microstimulation and Sensing.

Neural sensing and stimulation have been the backbone of neuroscience research, brain-machine interfaces and clinical neuromodulation therapies for decades. To-date, most of the neural stimulation systems have relied on sharp metal microelectrodes with poor electrochemical properties that induce extensive damage to the tissue and significantly degrade the long-term stability of implantable systems. Here, we demonstrate a flexible cortical microelectrode array based on porous graphene, which is capable of efficient electrophysiological sensing and stimulation from the brain surface, without penetrating into the tissue. Porous graphene electrodes show superior impedance and charge injection characteristics making them ideal for high efficiency cortical sensing and stimulation. They exhibit no physical delamination or degradation even after 1 million biphasic stimulation cycles, confirming high endurance. In in vivo experiments with rodents, same array is used to sense brain activity patterns with high spatio-temporal resolution and to control leg muscles with high-precision electrical stimulation from the cortical surface. Flexible porous graphene array offers a minimally invasive but high efficiency neuromodulation scheme with potential applications in cortical mapping, brain-computer interfaces, treatment of neurological disorders, where high resolution and simultaneous recording and stimulation of neural activity are crucial

FINITE ELEMENT ANALYZE OF THE FIRST METATARSAL VERTICAL ARCH OF THE FOOT IN THE HIGH-HEELED GAIT

A two-dimensional numerical model of the foot, incorporating, for the first time in the literature, realistic geometric and material properties of both skeletal and soft tissue components of the foot, was developed for biomechanical analysis of its structural behavior during gait. Using a Finite Element solver, the stress distribution within the first metatarsal vertical: arch of the foot (FMVA) structure was obtained and regions of elevated stresses for three subphases of the stance (heel-strike, push-off, and toe-off) were located. Validation of the pressure state was achieved by comparing model predictions of contact pressure distribution with Novel Pedar. The presently developed measurement and numerical analysis tools open new approaches for clinical applications, from simulation of the development mechanisms of common foot disorders to pre-and post-interventional evaluation of their treatment

PLANTAR MECHANICS INFLUENCE OF DIFFERENT AND EXTRINSIC BIOMECHANICS INSTRUMENTALlTIES IN STANDING VERTICAL JUMP

The research has studied and compared with the areal characters of plantar pressure distribution in standing vertical jump, MMP (mean maximum pressure), MVP (mean value pressure) and the plantar force changes. The research has studied the formation of the shockproof mechanism in different designed shockproof systems, the aim is to guide to design shockproof shoes and to strengthen people's understanding to sports shockproof shoes