Multi-objective surrogate based hull-form optimization using high-fidelity rans computations

RANS-based optimization procedures for ship design become increasingly complex and require the development of more efficient optimization techniques. The four phases of the design procedure are: shape parameterization, global sensitivity analysis, multi-objective optimization and design review. The dimensions of the design space can be mitigated by a smart choice for the shape parameterization and by screening and ranking the design variables in the global sensitivity phase. Subsequently, Surrogate Based Global Optimization (SBGO) is used to reduce the cost of the multi-objective optimization phase. For a practical application it is shown that the computational time reduces from two weeks to only a day when using SBGO instead of applying a Multi-Objective Genetic Algorithm (MOGA) directly to the solver. The design review phase is then used to verify and further develop the optimal design. Here, we focus on automatic ship design techniques which comprises the first three steps of the design procedure. Accelerating the ship design process is subject of ongoing research at the Maritime Research Institute Netherlands, making it useful for practical applications with turnaround times of only a few weeks

NeutrEx:A 3D Quality Component Measure on Facial Expression Neutrality

Accurate face recognition systems are increasingly important in sensitive applications like border control or migration management. Therefore, it becomes crucial to quantify the quality of facial images to ensure that low-quality images are not affecting recognition accuracy. In this context, the current draft of ISO/IEC 29794-5 introduces the concept of component quality to estimate how single factors of variation affect recognition outcomes. In this study, we propose a quality measure (NeutrEx) based on the accumulated distances of a 3D face reconstruction to a neutral expression anchor. Our evaluations demonstrate the superiority of our proposed method compared to baseline approaches obtained by training Support Vector Machines on face embeddings extracted from a pre-trained Convolutional Neural Network for facial expression classification. Furthermore, we highlight the explainable nature of our NeutrEx measures by computing per-vertex distances to unveil the most impactful face regions and allow operators to give actionable feedback to subjects

Bringing AI to the clinic: blueprint for a vendor-neutral AI deployment infrastructure

AI provides tremendous opportunities for improving patient care, but at present there is little evidence of real-world uptake. An important barrier is the lack of well-designed, vendor-neutral and future-proof infrastructures for deployment. Because current AI algorithms are very narrow in scope, it is expected that a typical hospital will deploy many algorithms concurrently. Managing stand-alone point solutions for all of these algorithms will be unmanageable. A solution to this problem is a dedicated platform for deployment of AI. Here we describe a blueprint for such a platform and the high-level design and implementation considerations of such a system that can be used clinically as well as for research and development. Close collaboration between radiologists, data scientists, software developers and experts in hospital IT as well as involvement of patients is crucial in order to successfully bring AI to the clinic

Digital tracking algorithm reveals the influence of structural irregularities on joint movements in the human cervical spine

The final publication is available at Elsevier via https://dx.doi.org/10.1016/j.clinbiomech.2018.04.015 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/Background Disc height loss and osteophytes change the local mechanical environment in the spine; while previous research has examined kinematic dysfunction under degenerative change, none has looked at the influence of disc height loss and osteophytes throughout movement. Methods Twenty patients with pain related to the head, neck or shoulders were imaged via videofluoroscopy as they underwent sagittal-plane flexion and extension. A clinician graded disc height loss and osteophytes as “severe/moderate”, “mild”, or “none”. A novel tracking algorithm quantified motions of each vertebra. This information was used to calculate intervertebral angular and shear displacements. The digital algorithm made it practical to track individual vertebrae in multiple patients through hundreds of images without bias. Findings Cases without height loss/osteophytes had a consistent increase in intervertebral angular displacement from C2/C3 to C5/C6, like that of healthy individuals, and mild height losses did not produce aberrations that were systematic or necessarily discernable. However, joints with moderate to severe disc height loss and osteophytes exhibited reduced range of motion compared to adjacent unaffected joints in that patient and corresponding joints in patients without structural irregularities. Interpretation Digitally-obtained motion histories of individual joints allowed anatomical joint changes to be linked with changes in joint movement patterns. Specifically, disc height loss and osteophytes were found to influence cervical spine movement in the sagittal plane, reducing angular motions at affected joints by approximately 10% between those with and without height loss and osteophytes. Further, these joint changes were associated with perturbed intervertebral angular and shear movements.Natural Sciences and Engineering Research Council (NSERC) Discovery Grant

Plurality in the Measurement of Social Media Use and Mental Health: An Exploratory Study Among Adolescents and Young Adults

On a daily basis, individuals between 12 and 25 years of age engage with their mobile devices for many hours. Social Media Use (SMU) has important implications for the social life of younger individuals in particular. However, measuring SMU and its effects often poses challenges to researchers. In this exploratory study, we focus on some of these challenges, by addressing how plurality in the measurement and age-specific characteristics of SMU can influence its relationship with measures of subjective mental health (MH). We conducted a survey among a nationally representative sample of Dutch adolescents and young adults (N=3,669). Using these data, we show that measures of SMU show little similarity with each other, and that age-group differences underlie SMU. Similar to the small associations previously shown in social media-effects research, we also find some evidence that greater SMU associates to drops and to increases in MH. Albeit nuanced, associations between SMU and MH were found to be characterized by both linear and quadratic functions. These findings bear implications for the level of association between different measures of SMU and its theorized relationship with other dependent variables of interest in media-effects research

Morphing Attack Detection -- Database, Evaluation Platform and Benchmarking

Morphing attacks have posed a severe threat to Face Recognition System (FRS). Despite the number of advancements reported in recent works, we note serious open issues such as independent benchmarking, generalizability challenges and considerations to age, gender, ethnicity that are inadequately addressed. Morphing Attack Detection (MAD) algorithms often are prone to generalization challenges as they are database dependent. The existing databases, mostly of semi-public nature, lack in diversity in terms of ethnicity, various morphing process and post-processing pipelines. Further, they do not reflect a realistic operational scenario for Automated Border Control (ABC) and do not provide a basis to test MAD on unseen data, in order to benchmark the robustness of algorithms. In this work, we present a new sequestered dataset for facilitating the advancements of MAD where the algorithms can be tested on unseen data in an effort to better generalize. The newly constructed dataset consists of facial images from 150 subjects from various ethnicities, age-groups and both genders. In order to challenge the existing MAD algorithms, the morphed images are with careful subject pre-selection created from the contributing images, and further post-processed to remove morphing artifacts. The images are also printed and scanned to remove all digital cues and to simulate a realistic challenge for MAD algorithms. Further, we present a new online evaluation platform to test algorithms on sequestered data. With the platform we can benchmark the morph detection performance and study the generalization ability. This work also presents a detailed analysis on various subsets of sequestered data and outlines open challenges for future directions in MAD research.Comment: This paper is a pre-print. The article is accepted for publication in IEEE Transactions on Information Forensics and Security (TIFS

Morphing Attack Detection -- Database, Evaluation Platform and Benchmarking

Morphing attacks have posed a severe threat to Face Recognition System (FRS). Despite the number of advancements reported in recent works, we note serious open issues such as independent benchmarking, generalizability challenges and considerations to age, gender, ethnicity that are inadequately addressed. Morphing Attack Detection (MAD) algorithms often are prone to generalization challenges as they are database dependent. The existing databases, mostly of semi-public nature, lack in diversity in terms of ethnicity, various morphing process and post-processing pipelines. Further, they do not reflect a realistic operational scenario for Automated Border Control (ABC) and do not provide a basis to test MAD on unseen data, in order to benchmark the robustness of algorithms. In this work, we present a new sequestered dataset for facilitating the advancements of MAD where the algorithms can be tested on unseen data in an effort to better generalize. The newly constructed dataset consists of facial images from 150 subjects from various ethnicities, age-groups and both genders. In order to challenge the existing MAD algorithms, the morphed images are with careful subject pre-selection created from the contributing images, and further post-processed to remove morphing artifacts. The images are also printed and scanned to remove all digital cues and to simulate a realistic challenge for MAD algorithms. Further, we present a new online evaluation platform to test algorithms on sequestered data. With the platform we can benchmark the morph detection performance and study the generalization ability. This work also presents a detailed analysis on various subsets of sequestered data and outlines open challenges for future directions in MAD research

Symbiodinium Transcriptomes: Genome Insights into the Dinoflagellate Symbionts of Reef-Building Corals

Dinoflagellates are unicellular algae that are ubiquitously abundant in aquatic environments. Species of the genus Symbiodinium form symbiotic relationships with reef-building corals and other marine invertebrates. Despite their ecologic importance, little is known about the genetics of dinoflagellates in general and Symbiodinium in particular. Here, we used 454 sequencing to generate transcriptome data from two Symbiodinium species from different clades (clade A and clade B). With more than 56,000 assembled sequences per species, these data represent the largest transcriptomic resource for dinoflagellates to date. Our results corroborate previous observations that dinoflagellates possess the complete nucleosome machinery. We found a complete set of core histones as well as several H3 variants and H2A.Z in one species. Furthermore, transcriptome analysis points toward a low number of transcription factors in Symbiodinium spp. that also differ in the distribution of DNA-binding domains relative to other eukaryotes. In particular the cold shock domain was predominant among transcription factors. Additionally, we found a high number of antioxidative genes in comparison to non-symbiotic but evolutionary related organisms. These findings might be of relevance in the context of the role that Symbiodinium spp. play as coral symbionts

Leonardo's Paradox:path and shape instabilities of particles and bubbles

Bubble and particle laden flows are important in a wide range of industrial and geophysical processes. This broad application field stimulated bubbly and particle laden flow research. In the upper limit research focuses on dense, highly laden flows, which provides overall statistical properties of such flows. In the lower limit the research addresses the problem of single bubble and particle behavior, providing a more fundamental knowledge of the hydrodynamic forces acting on bodies. This thesis focuses on both single solid particle and bubble behavior