Robust recognition and segmentation of human actions using HMMs with missing observations

This paper describes the integration of missing observation data with hidden Markov models to create a framework that is able to segment and classify individual actions from a stream of human motion using an incomplete 3D human pose estimation. Based on this framework, a model is trained to automatically segment and classify an activity sequence into its constituent subactions during inferencing. This is achieved by introducing action labels into the observation vector and setting these labels as missing data during inferencing, thus forcing the system to infer the probability of each action label. Additionally, missing data provides recognition-level support for occlusions and imperfect silhouette segmentation, permitting the use of a fast (real-time) pose estimation that delegates the burden of handling undetected limbs onto the action recognition system. Findings show that the use of missing data to segment activities is an accurate and elegant approach. Furthermore, action recognition can be accurate even when almost half of the pose feature data is missing due to occlusions, since not all of the pose data is important all of the time

Design characteristics that improve the fatigue life of threaded pipe connections

Threaded pipe connections are commonly used to connect risers, tendons, drill pipes and well casing strings. In these applications fatigue resistance plays an important role. A large variety of patented design features exist, all claiming to improve the connection’s fatigue life. However, patent documents only contain claims and numerical or experimental data about these connection’s performance is generally not published. This makes it hard to make a quantitative comparison between different designs. In this study an overview is given of fatigue resistant threaded connections. Two major methods to improve the fatigue life of a connection were identified. First of all, local stress concentrations can be reduced by optimizing the geometry of the threads. Second the global shape of the connection can be optimized to obtain a more uniform load distribution. Using a parametric finite element model, different designs were compared. The connections were modelled by a 2D axisymmetric geometry with non-linear material properties and elaborate contact conditions. Selected designs have been subjected to experimental tests in a four-point bending fatigue setup. The experimental tests serve as a validation for the results of the numerical simulations. It was found that the multiaxial stress distribution at the thread roots is the defining factor for the fatigue life of the connection. Nevertheless, these stresses can be changed by the global geometry of the connection. It can be concluded that the fatigue life of threaded connections is determined by a combination of global and local aspects which should both be analysed for fatigue life calculations

EURASIP Journal on Applied Signal Processing 2005:13, 2110–2126 c ○ 2005 Hindawi Publishing Corporation Robust Recognition and Segmentation of Human Actions Using HMMs with Missing Observations

This paper describes the integration of missing observation data with hidden Markov models to create a framework that is able to segment and classify individual actions from a stream of human motion using an incomplete 3D human pose estimation. Based on this framework, a model is trained to automatically segment and classify an activity sequence into its constituent subactions during inferencing. This is achieved by introducing action labels into the observation vector and setting these labels as missing data during inferencing, thus forcing the system to infer the probability of each action label. Additionally, missing data provides recognitionlevel support for occlusions and imperfect silhouette segmentation, permitting the use of a fast (real-time) pose estimation that delegates the burden of handling undetected limbs onto the action recognition system. Findings show that the use of missing data to segment activities is an accurate and elegant approach. Furthermore, action recognition can be accurate even when almost half of the pose feature data is missing due to occlusions, since not all of the pose data is important all of the time

Using interaction signatures to find and label chairs and floors

The use of interaction signatures to recognize objects without considering the object\u27s physical structure is discussed. Without object recognition, smart homes cannot make full use of video cameras because vision systems cannot provide object-related context to the human activities monitored. One important advantage of interaction signatures is that people frequently and repeatedly interact with household objects, so the system can build evidence for object locations and labels

Object labelling from human action recognition

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Evaluation of diabetic peer support in Malawi

BackgroundType 2 diabetes is a major health concern worldwide and requires urgent attention from health care providers and policy makers. Due to shortage of health care workers in low-income countries, peer support programs have been viewed as a viable option in management of diabetes and have shown to be effective in sub-Saharan Africa. ObjectiveThe aim of this study is to assess and evaluate the Kamuzu Central Hospital (KCH) diabetic peer support program’s (DPSP) impact 4 years after its establishment by assessing knowledge, self-efficacy and behaviours of DPSP members compared to non-members.Methodology This is a cross-sectional study done among diabetic patients attending clinics between 12th August and 25th September 2018 at KCH. Self and interviewer-administered questionnaires (designed based on validated survey instruments) were used. The participants (n=176) were recruited consecutively after consenting. Results Results showed DPSP members were more knowledgeable regarding the effects of skipping meals and sweet juice on blood glucose and conditions not associated with diabetes. In terms of self-efficacy and behaviour changes, DPSP members believe that they are more able to correct hypoglycaemia, to communicate their concerns to health workers and to perform daily foot exam compared to non-members.Conclusion The KCH (Lilongwe) Diabetes Peer Support program has positively impacted its members and should be scaled up to engage all diabetic patients in Malawi. Ongoing training for peer supporters is necessary to update and reinforce management, knowledge and skills, and to ensure fidelity in program implementation

In pursuit of happiness : Creation of an academic hospitalist wellness committee and well-being survey

Physician burnout poses a critical threat to the delivery of healthcare. A solution to this problem is a leadership imperative. Managing demands on physicians can prevent burnout and foster engagement. This study assesses stress and burnout within an academic hospitalist group and identifies areas to focus interventions on both personal and systemic levels.Includes bibliographical reference

Evaluation des endommagements dans les structures BA à partir de mesures vibratoires: études expérimentales et numériques

International audience Après un événement (séisme, modifications du voisinage, ...), une structure BA peut être endommagée. La capacité résistante de cette structure peut être évaluée par des mesures vibratoires. A l'heure actuelle, ce type de mesures permet le diagnostic à l'échelle globale (toute la structure) et de manière qualitative alors que la localisation et la quantification des endommagements restent encore à approfondir. Dans le cadre de cette recherche, le diagnostic à l'échelle locale d'une structure poteaux-poutres béton armé instrumentée en laboratoire est étudié. Ce travail s'insère dans un contexte national de réévaluation des structures existantes. En première partie, le travail de recherche a commencé par une expérimentation en laboratoire sur une structure poteaux-poutres de type H (deux poteaux et une poutre). Différentes sollicitations croissantes ont été imposées au milieu de la poutre correspondant à différents états d'endommagement. Des mesures de champs de déplacement de toute la structure et des mesures vibratoires par accéléromètres ont été effectuées. A partir des mesures vibratoires, les caractéristiques dynamiques de la structure ont été identifiées (fréquences propres, déformées modales). Ces caractéristiques ont permis de caler un modèle numérique EF simplifié (établi par Matlab), qui utilise les éléments « barres » et les connexions semi-rigides entre les poteaux et les poutres. Les rigidités de ces connexions ont été identifiées par des boucles d'optimisation pour trouver les résultats qui s'approchent le plus des résultats expérimentaux. Les rigidités identifiées des connexions sont utilisées pour calculer des facteurs de rigidités qui varient entre 0 (rotule parfaite) et 1 (encastrement parfait). Ils apportent des informations sur l'état d'endommagement des connexions étudiées. Par conséquent, l'évaluation des connexions par des mesures dynamiques, à l'échelle du laboratoire, est possible. En deuxième partie, pour pouvoir vérifier l'influence des endommagements locaux sur d'une part, la réponse dynamique globale de la structure et d'autre part, sur la capacité structurelle globale de toute la structure, un code EF plus complexe (Castem) a été utilisé. Des éléments poutres multifibres ont été utilisés pour modéliser la structure du type portique. Dans un premier temps, les paramètres des matériaux (« béton » et « acier ») ont été identifiés en fonction des résultats expérimentaux sur les matériaux. Ensuite, le résultat numérique sur le portique est comparé avec l'expérimentation. La pertinence du modèle numérique dans l'évaluation de la capacité de la structure après les premiers endommagements est discutée.</p

Prediction of Maximum Lactate Concentration During an All-Out Anaerobic Test in Elite Ice Hockey Players

International Journal of Exercise Science 16(4) 1385-1397, 2023. The lack of specific on-ice tests to predict maximum lactate concentration limits the ability of coaches to better track and develop their ice hockey players. Thus, this study aimed to develop an equation for indirectly assessing the maximum lactate concentration produced from an all-out on-ice skating effort in elite adolescent ice hockey players. Twenty elite male ice hockey players participated in this study (age = 15.7 ± 1.0 year). The lactate anaerobic skating test (LAST) consisted of skating back and forth on an 18.2 m course at maximal speed with abrupt stops at each end for a total of 6 shuttles (total distance = 218.2 m; average time = 52.0 ± 2.0 s). The oxygen uptake was measured using a portable metabolic analyzer (Cosmed K4b2) and the maximum post-exercise lactate concentration with a Lactate Pro analyzer. The variables used to estimate lactate concentration were time, heart rate, number of skating strides in the last shuffle (6th) and the skating stride index. The average maximum lactate concentration was 14.4 mmol· L−1, which is expected in elite players. The analysis of explained common variance using T-test (r² = 0.759) and linear regression (r² = 0.863) demonstrates the validity of the model. Additionally, the root mean square error (RMSE = 0.60 mmol· L−1), the mean absolute error (MAE = 0.45mmol· L−1) and the standard error of estimate (SEE = 0.69 mmol· L−1) values further confirm the accuracy of the model. Thus, using simple and easy-to-measure variables (i.e., time and skating stride), coaches will be able to monitor more effectively their players’ progress in an effort to optimize their individual on-ice performance