Push Recovery for Humanoid Robots using Linearized Double Inverted Pendulum

Biped robots have come a long way in imitating a human being\u27s anatomy and posture. Standing balance and push recovery are some of the biggest challenges for such robots. This work presents a novel simplified model for a humanoid robot to recover from external disturbances. The proposed Linearized Double Inverted Pendulum, models the dynamics of a complex humanoid robot that can use ankle and hip recovery strategies while taking full advantage of the advances in controls theory research. To support this, an LQR based control architecture is also presented in this work. The joint torque signals are generated along with ankle torque constraints to ensure the Center of Pressure stays within the support polygon. Simulation results show that the presented model can successfully recover from external disturbances while using minimal effort when compared to other widely used simplified models. It optimally uses the the torso weight to generate angular momentum about the pelvis of the robot to counter-balance the effects of external disturbances. The proposed method was validated on simulated `TigerBot-VII\u27, a humanoid robot

Testing the Accuracy of Eukaryotic Phylogenetic Profiles for Prediction of Biological Function

A phylogenetic profile captures the pattern of gene gain and loss throughout evolutionary time. Proteins that interact directly or indirectly within the cell to perform a biological function will often co-evolve, and this co-evolution should be well reflected within their phylogenetic profiles. Thus similar phylogenetic profiles are commonly used for grouping proteins into functional groups. However, it remains unclear how the size and content of the phylogenetic profile impacts the ability to predict function, particularly in Eukaryotes. Here we developed a straightforward approach to address this question by constructing a complete set of phylogenetic profiles for 31 fully sequenced Eukaryotes. Using Gene Ontology as our gold standard, we compared the accuracy of functional predictions made by a comprehensive array of permutations on the complete set of genomes. Our permutations showed that phylogenetic profiles containing between 25 and 31 Eukaryotic genomes performed equally well and significantly better than all other permuted genome sets, with one exception: we uncovered a core of group of 18 genomes that achieved statistically identical accuracy. This core group contained genomes from each branch of the eukaryotic phylogeny, but also contained several groups of closely related organisms, suggesting that a balance between phylogenetic breadth and depth may improve our ability to use Eukaryotic specific phylogenetic profiles for functional annotations

The Effect of Knowledge Sharing on Open Source Contribution: A Multi-platform Perspective

Open source software (OSS) community plays a key role in contemporary software development. However, there is a need to better understand the factors which influence individuals’ voluntary contribution on open source platforms. In this paper, we investigate how different types of knowledge sharing affect an individuals’ contribution towards open source projects. We further refine knowledge sharing taxonomy by classifying explicit knowledge sharing into two sub-types – strong explicit knowledge sharing and weak explicit knowledge sharing, depending on the extent of interpersonal interaction required for knowledge transfer. In this paper, we take a multi-platform perspective – we collect data from GitHub – the biggest online platform to host open source software development, and Gitter – an open source instant messaging and chat room application designed for developers. We map the user identities across these two platforms. We analyze monthly panel data for the year 2017 consisting of 3,695 individuals. The results demonstrate that both strong and weak explicit knowledge sharing have positive relationship with open source contribution. Moreover, the tacit knowledge sharing positively moderates these relationships. Our paper extends the theoretical understanding of different knowledge sharing types and their inter-relationship, and their respective impact on contribution. Our findings have important implications for the OSS community, and especially help OSS platform designers get a better understanding of the symbiosis between different OSS platforms

Image Segmentation Techniques: A Survey

Segmenting an image utilizing diverse strategies is the primary technique of Image Processing. The technique is broadly utilized in clinical image handling, face acknowledgment, walker location, and so on. Various objects in an image can be recognized using image segmentation methods. Researchers have come up with various image segmentation methods for effective analysis. This paper presents a survey and sums up the designs process of essential image segmentation methods broadly utilized with their advantages and weaknesses

Image Segmentation Techniques: A Survey

Segmenting an image utilizing diverse strategies is the primary technique of Image Processing. The technique is broadly utilized in clinical image handling, face acknowledgment, walker location, and so on. Various objects in an image can be recognized using image segmentation methods. Researchers have come up with various image segmentation methods for effective analysis. This paper presents a survey and sums up the designs process of essential image segmentation methods broadly utilized with their advantages and weaknesses

Mathematical modelling of a hand crank generator for powering lower-limb exoskeletons

SummaryWith advances in technology and ageing societal concerns growing, personal care devices are gaining importance globally. One such area is lower-limb exoskeletons, used to assist persons to move around for normal daily living. Most of the commercially available assistive exoskeletons use rechargeable Li-ion batteries, which require frequent charging to meet the operational needs. Charging becomes a problem when a person relying on a mobility exoskeleton has to go outdoors for shopping or a leisure walk. Experimental data from on-going research to develop assistive mobility exoskeletons for elderly persons indicates that, the power required for exoskeletons is around 45–60W which falls in the output range of hand-crank generators. So use of hand-crank generators as a charging source is discussed. In this work, we develop a mathematical model to investigate the potential of hand-crank devices in charging mobility exoskeletons and to give relation between input cranking speed and output charging power, and estimate the cranking time

The knowledge and attitudes towards domestic violence among pregnant women in Delhi, India

Background: Domestic violence during pregnancy endangers the health of the mother and her child. Aim and Objective: To ascertain the knowledge and attitudes towards domestic violence among pregnant women in India and to find out their sociodemographic predictors. Settings and design: This cross-sectional analysis of baseline data from a prospective study was conducted at the antenatal care (ANC) clinic of a major tertiary care government hospital in New Delhi from 2015-2018. Methods and material: The data were collected through face-to-face interviews with 1500 pregnant women up to 20 weeks of gestation. A p-value < 0.05 was considered statistically significant. Results: The mean (SD) age of the participants was 24.6 (3.6) years. All the participants were married. A total of 1169 (77.9%) participants were aware of domestic violence. The participant comprehension of the types of domestic violence was highest for physical (89.9%), emotional (68.4%), economical (21.5%), and sexual (17.4%) violence. On adjusted analysis, education ?10 years and higher SES were associated with a comprehensive awareness of domestic violence. Conclusions: The awareness of domestic violence, especially beyond physical violence, is low among pregnant women in India

Learning cross-lingual phonological and orthagraphic adaptations: a case study in improving neural machine translation between low-resource languages

Out-of-vocabulary (OOV) words can pose serious challenges for machine translation (MT) tasks, and in particular, for low-resource language (LRL) pairs, i.e., language pairs for which few or no parallel corpora exist. Our work adapts variants of seq2seq models to perform transduction of such words from Hindi to Bhojpuri (an LRL instance), learning from a set of cognate pairs built from a bilingual dictionary of Hindi--Bhojpuri words. We demonstrate that our models can be effectively used for language pairs that have limited parallel corpora; our models work at the character level to grasp phonetic and orthographic similarities across multiple types of word adaptations, whether synchronic or diachronic, loan words or cognates. We describe the training aspects of several character level NMT systems that we adapted to this task and characterize their typical errors. Our method improves BLEU score by 6.3 on the Hindi-to-Bhojpuri translation task. Further, we show that such transductions can generalize well to other languages by applying it successfully to Hindi -- Bangla cognate pairs. Our work can be seen as an important step in the process of: (i) resolving the OOV words problem arising in MT tasks, (ii) creating effective parallel corpora for resource-constrained languages, and (iii) leveraging the enhanced semantic knowledge captured by word-level embeddings to perform character-level tasks.Comment: 47 pages, 4 figures, 21 tables (including Appendices