A Data Fusion Perspective on Human Motion Analysis Including Multiple Camera Applications

Proceedings of: 5th International Work-Conference on the Interplay Between Natural and Artificial Computation, (IWINAC 2013). Mallorca, Spain, June 10-14.Human motion analysis methods have received increasing attention during the last two decades. In parallel, data fusion technologies have emerged as a powerful tool for the estimation of properties of objects in the real world. This papers presents a view of human motion analysis from the viewpoint of data fusion. JDL process model and Dasarathy's input-output hierarchy are employed to categorize the works in the area. A survey of the literature in human motion analysis from multiple cameras is included. Future research directions in the area are identified after this review.Publicad

Exploring the characteristics and most bothersome symptoms in MECP2 duplication syndrome to pave the path toward developing parent-oriented outcome measures

BACKGROUND: MECP2 Duplication Syndrome (MDS), resulting from the duplication of Xq28 region, including MECP2, is a rare disorder with a nascent understanding in clinical features and severity. Studies using antisense oligonucleotides revealed a broad phenotypic rescue in transgenic mice. With human clinical trials on the horizon, there is a need to develop clinical outcome measures for MDS. METHODS: We surveyed caregivers of MDS individuals to explore the frequency and severity of MDS clinical features, and identify the most meaningful symptoms/domains that need to be included in the outcome measure scales. RESULTS: A total of 101 responses were eligible for the survey. The top six most meaningful symptoms to caregivers in descending order included epilepsy, gross motor, fine motor, communication, infection, and constipation problems. Epilepsy was present in 58.4% of the subjects and 75% were drug‐resistant, Furthermore, ~12% required intensive care unit (ICU) admission. Infections were present in 55% of the subjects, and one‐fourth of them required ICU admission. Constipation was present in ~85% of the subjects and one‐third required enemas/suppositories. CONCLUSION: Our study is one of the largest cohorts conducted on MDS individuals characterizing the frequency and severity of MDS symptoms. Additionally, these study results will contribute to establishing a foundation to develop parent‐reported outcomes in MDS

Tool flank wear prediction using high-frequency machine data from industrial edge device

Tool flank wear monitoring can minimize machining downtime costs while increasing productivity and product quality. In some industrial applications, only a limited level of tool wear is allowed to attain necessary tolerances. It may become challenging to monitor a limited level of tool wear in the data collected from the machine due to the other components, such as the flexible vibrations of the machine, dominating the measurement signals. In this study, a tool wear monitoring technique to predict limited levels of tool wear from the spindle motor current and dynamometer measurements is presented. High-frequency spindle motor current data is collected with an industrial edge device while the cutting forces and torque are measured with a rotary dynamometer in drilling tests for a selected number of holes. Feature engineering is conducted to identify the statistical features of the measurement signals that are most sensitive to small changes in tool wear. A neural network based on the long short-term memory (LSTM) architecture is developed to predict tool flank wear from the measured spindle motor current and dynamometer signals. It is demonstrated that the proposed technique predicts tool flank wear with good accuracy and high computational efficiency. The proposed technique can easily be implemented in an industrial edge device as a real-time predictive maintenance application to minimize the costs due to manufacturing downtime and tool underuse or overuse.Comment: The first four authors have equal contributio

Stylistic document retrieval for Turkish

In information retrieval (IR) systems, there are a query and a collection of documents compared with this query and ranked according to a particular similarity measure. Since texts with the same content can be written by different authors, the writing styles of the documents change as well accordingly. This observation brings the idea of investigating text by means of style. In this paper, we analyze text documents in terms of stylistic features of the written text and measure effectiveness of these features in an IR system. Our main focus is on Turkish text documents. Although there are many studies about broadening IR systems with style based enhancement, there is no similar application for Turkish which performs retrieval depending purely on style. © 2009 IEEE

Functional biology of the Steel syndrome founder allele and evidence for clan genomics derivation of COL27A1 pathogenic alleles worldwide

© 2020, The Author(s). Previously we reported the identification of a homozygous COL27A1 (c.2089G\u3eC; p.Gly697Arg) missense variant and proposed it as a founder allele in Puerto Rico segregating with Steel syndrome (STLS, MIM #615155); a rare osteochondrodysplasia characterized by short stature, congenital bilateral hip dysplasia, carpal coalitions, and scoliosis. We now report segregation of this variant in five probands from the initial clinical report defining the syndrome and an additional family of Puerto Rican descent with multiple affected adult individuals. We modeled the orthologous variant in murine Col27a1 and found it recapitulates some of the major Steel syndrome associated skeletal features including reduced body length, scoliosis, and a more rounded skull shape. Characterization of the in vivo murine model shows abnormal collagen deposition in the extracellular matrix and disorganization of the proliferative zone of the growth plate. We report additional COL27A1 pathogenic variant alleles identified in unrelated consanguineous Turkish kindreds suggesting Clan Genomics and identity-by-descent homozygosity contributing to disease in this population. The hypothesis that carrier states for this autosomal recessive osteochondrodysplasia may contribute to common complex traits is further explored in a large clinical population cohort. Our findings auNorthwell Healthnt our understanding of COL27A1 biology and its role in skeletal development; and expand the functional allelic architecture in this gene underlying both rare and common disease phenotypes

The neutrino signal at HALO: learning about the primary supernova neutrino fluxes and neutrino properties

Core-collapse supernova neutrinos undergo a variety of phenomena when they travel from the high neutrino density region and large matter densities to the Earth. We perform analytical calculations of the supernova neutrino fluxes including collective effects due to the neutrino-neutrino interactions, the Mikheev-Smirnov-Wolfenstein (MSW) effect due to the neutrino interactions with the background matter and decoherence of the wave packets as they propagate in space. We predict the numbers of one- and two-neutron charged and neutral-current electron-neutrino scattering on lead events. We show that, due to the energy thresholds, the ratios of one- to two-neutron events are sensitive to the pinching parameters of neutrino fluxes at the neutrinosphere, almost independently of the presently unknown neutrino properties. Besides, such events have an interesting sensitivity to the spectral split features that depend upon the presence/absence of energy equipartition among neutrino flavors. Our calculations show that a lead-based observatory like the Helium And Lead Observatory (HALO) has the potential to pin down important characteristics of the neutrino fluxes at the neutrinosphere, and provide us with information on the neutrino transport in the supernova core.Comment: 30 pages, 12 figures, 6 tables, minor correction

Analytical Benchmark Problems for Multifidelity Optimization Methods

The paper presents a collection of analytical benchmark problems specifically selected to provide a set of stress tests for the assessment of multifidelity optimization methods. In addition, the paper discusses a comprehensive ensemble of metrics and criteria recommended for the rigorous and meaningful assessment of the performance of multifidelity strategies and algorithms

Detection of mosaic and population-level structural variants with Sniffles2

Calling structural variations (SVs) is technically challenging, but using long reads remains the most accurate way to identify complex genomic alterations. Here we present Sniffles2, which improves over current methods by implementing a repeat aware clustering coupled with a fast consensus sequence and coverage-adaptive filtering. Sniffles2 is 11.8 times faster and 29% more accurate than state-of-the-art SV callers across different coverages (5–50×), sequencing technologies (ONT and HiFi) and SV types. Furthermore, Sniffles2 solves the problem of family-level to population-level SV calling to produce fully genotyped VCF files. Across 11 probands, we accurately identified causative SVs around MECP2, including highly complex alleles with three overlapping SVs. Sniffles2 also enables the detection of mosaic SVs in bulk long-read data. As a result, we identified multiple mosaic SVs in brain tissue from a patient with multiple system atrophy. The identified SV showed a remarkable diversity within the cingulate cortex, impacting both genes involved in neuron function and repetitive elements