| 1. |
|
|
| 2. |
|
|
| 3. |
- Bekiroglu, Yasemin, et al.
(författare)
-
SARAFun, Smart Assembly Robot with Advanced FUNctionalities, H2020
- 2017
-
Ingår i: Impact. - : Science Impact, Ltd.. - 2398-7073. ; 2017:5, s. 67-69
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- While Industrial robots are very successful in many areas of industrial manufacturing, assembly automation still suffers from complex time consuming programming and the need of dedicated hardware. ABB has developed YuMi, a collaborative inherently safe assembly robot that is expected to reduce integration costs significantly by offering a standardized hardware setup and simple fitting of the robot into existing workplaces. Internal Pilot testing at ABB has however shown that when YuMi is programmed with traditional methods the programming time even for simple assembly tasks will remain very long. The SARAFun project has been formed to enable a non-expert user to integrate a new bi-manual assembly task on a YuMi robot in less than a day. This will be accomplished by augmenting the YuMi robot with cutting edge sensory and cognitive abilities as well as reasoning abilities required to plan and execute an assembly task. The overall conceptual approach is that the robot should be capable of learning and executing assembly tasks in a human like manner. Studies will be made to understand how human assembly workers learn and perform assembly tasks. The human performance will be modelled and transferred to the YuMi robot as assembly skills. The robot will learn assembly tasks, such as insertion or folding, by observing the task being performed by a human instructor. The robot will then analyze the task and generate an assembly program, including exception handling, and design 3D printable fingers tailored for gripping the parts at hand. Aided by the human instructor, the robot will finally learn to perform the actual assembly task, relying on sensory feedback from vision, force and tactile sensing as well as physical human robot interaction. During this phase the robot will gradually improve its understanding of the assembly at hand until it is capable of performing the assembly in a fast and robust manner.
|
|
| 4. |
- Novak, Iona, et al.
(författare)
-
Early, Accurate Diagnosis and Early Intervention in Cerebral Palsy : Advances in Diagnosis and Treatment
- 2017
-
Ingår i: JAMA pediatrics. - : American Medical Association. - 2168-6203 .- 2168-6211. ; 171:9, s. 897-907
-
Forskningsöversikt (refereegranskat)abstract
- Importance: Cerebral palsy describes the most common physical disability in childhood and occurs in 1 in 500 live births. Historically, the diagnosis has been made between age 12 and 24 months but now can be made before 6 months' corrected age.Objectives: To systematically review best available evidence for early, accurate diagnosis of cerebral palsy and to summarize best available evidence about cerebral palsy-specific early intervention that should follow early diagnosis to optimize neuroplasticity and function.Evidence Review: This study systematically searched the literature about early diagnosis of cerebral palsy in MEDLINE (1956-2016), EMBASE (1980-2016), CINAHL (1983-2016), and the Cochrane Library (1988-2016) and by hand searching. Search terms included cerebral palsy, diagnosis, detection, prediction, identification, predictive validity, accuracy, sensitivity, and specificity. The study included systematic reviews with or without meta-analyses, criteria of diagnostic accuracy, and evidence-based clinical guidelines. Findings are reported according to the PRISMA statement, and recommendations are reported according to the Appraisal of Guidelines, Research and Evaluation (AGREE) II instrument.Findings: Six systematic reviews and 2 evidence-based clinical guidelines met inclusion criteria. All included articles had high methodological Quality Assessment of Diagnostic Accuracy Studies (QUADAS) ratings. In infants, clinical signs and symptoms of cerebral palsy emerge and evolve before age 2 years; therefore, a combination of standardized tools should be used to predict risk in conjunction with clinical history. Before 5 months' corrected age, the most predictive tools for detecting risk are term-age magnetic resonance imaging (86%-89% sensitivity), the Prechtl Qualitative Assessment of General Movements (98% sensitivity), and the Hammersmith Infant Neurological Examination (90% sensitivity). After 5 months' corrected age, the most predictive tools for detecting risk are magnetic resonance imaging (86%-89% sensitivity) (where safe and feasible), the Hammersmith Infant Neurological Examination (90% sensitivity), and the Developmental Assessment of Young Children (83% C index). Topography and severity of cerebral palsy are more difficult to ascertain in infancy, and magnetic resonance imaging and the Hammersmith Infant Neurological Examination may be helpful in assisting clinical decisions. In high-income countries, 2 in 3 individuals with cerebral palsy will walk, 3 in 4 will talk, and 1 in 2 will have normal intelligence.Conclusions and Relevance: Early diagnosis begins with a medical history and involves using neuroimaging, standardized neurological, and standardized motor assessments that indicate congruent abnormal findings indicative of cerebral palsy. Clinicians should understand the importance of prompt referral to diagnostic-specific early intervention to optimize infant motor and cognitive plasticity, prevent secondary complications, and enhance caregiver well-being.
|
|
| 5. |
- Treasure, Anne M., et al.
(författare)
-
Marine Mammals Exploring the Oceans Pole to Pole A Review of the MEOP Consortium
- 2017
-
Ingår i: Oceanography. - : The Oceanography Society. - 1042-8275. ; 30:2, s. 132-138
-
Tidskriftsartikel (refereegranskat)abstract
- Polar oceans are poorly monitored despite the important role they play in regulating Earth's climate system. Marine mammals equipped with biologging devices are now being used to fill the data gaps in these logistically difficult to sample regions. Since 2002, instrumented animals have been generating exceptionally large data sets of oceanographic CTD casts (>500,000 profiles), which are now freely available to the scientific community through the MEOP data portal (http://meop.net). MEOP (Marine Mammals Exploring the Oceans Pole to Pole) is a consortium of international researchers dedicated to sharing animal-derived data and knowledge about the polar oceans. Collectively, MEOP demonstrates the power and cost-effectiveness of using marine mammals as data-collection platforms that can dramatically improve the ocean observing system for biological and physical oceanographers. Here, we review the MEOP program and database to bring it to the attention of the international community.
|
|
