The Lessons Learned and Experienced Gained Navigating (Graduate) Student life as a Dad and Mentoring a First-Generation Graduate Student

Parenting often presents challenges on its own. Combining it with challenges of graduate studies and financial instability brings additional challenges and puts a higher pressures to handle everyday life situations. In this talk, I will present two experiences from my life. First, I will highlight my path of being an international graduate student while raising two little kids. Following, I will focus on my experience of (partially) mentoring a first-generation graduate student while being a postdoc. In the first part, I will discuss about the challenges of students as parents. I will provide an example of how I took my first exam in the US as a graduate student with a wrist band from a hospital when my son was born. In addition, I will discuss about financial and emotional balancing of graduate student life, while also taking care of two little kids, due to my wife working 80+ hour shifts. In the second part of the talk, I will discuss about my experiences when I was partially mentoring a first-generation PhD student while I was a postdoc. During those times, I had an opportunity to observe some of the challenges of that student, due to a limited support from student’s family and how important it was to provide not just academic support, but also a moral support to keep the student continuing with the studies

Bipedal Model and Hybrid Zero Dynamics of Human Walking with Foot Slip

Foot slip is one of the major causes of falls in human locomotion. Analytical bipedal models provide an insight into the complex slip dynamics and reactive control strategies for slip-induced fall prevention. Most of the existing bipedal dynamics models are built on no foot slip assumption and cannot be used directly for such analysis. We relax the no-slip assumption and present a new bipedal model to capture and predict human walking locomotion under slip. We first validate the proposed slip walking dynamic model by tuning and optimizing the model parameters to match the experimental results. The results demonstrate that the model successfully predicts both the human walking and recovery gaits with slip. Then, we extend the hybrid zero dynamics (HZD) model and properties to capture human walking with slip. We present the closed-form of the HZD for human walking and discuss the transition between the non-slip and slip states through slip recovery control design. The analysis and design are illustrated through human walking experiments. The models and analysis can be further used to design and control wearable robotic assistive devices to prevent slip-and-fall

New records of the rare dragonfly, Black Pennant - Selysiothemis nigra (Vander Linden, 1825) (Insecta: Odonata) in Bosnia and Herzegovina

In 2012, we recorded a Black Pennant, Selysiothemis nigra, at two sites in Bosnia and Herzegovina, i.e. in the surroundings of Klepci village and in Hutovo Blato Nature Park, Neretva River. These are the first recent records of this species in Bosnia and Herzegovina, which had previously been known only from the entomological collection in the Museum of Sarajevo. As this species had previously been recorded on the Croatian side of the Neretva River, these records fit into the distribution area of the species. With the confirmation of this record, the dragonfly fauna of Bosnia and Herzegovina consists of 60 specie

Shoe–Floor Interactions in Human Walking With Slips: Modeling and Experiments

Shoe–floor interactions play a crucial role in determining the possibility of potential slip and fall during human walking. Biomechanical and tribological parameters influence the friction characteristics between the shoe sole and the floor and the existing work mainly focus on experimental studies. In this paper, we present modeling, analysis, and experiments to understand slip and force distributions between the shoe sole and floor surface during human walking. We present results for both soft and hard sole material. The computational approaches for slip and friction force distributions are presented using a spring-beam networks model. The model predictions match the experimentally observed sole deformations with large soft sole deformation at the beginning and the end stages of the stance, which indicates the increased risk for slip. The experiments confirm that both the previously reported required coefficient of friction (RCOF) and the deformation measurements in this study can be used to predict slip occurrence. Moreover, the deformation and force distribution results reported in this study provide further understanding and knowledge of slip initiation and termination under various biomechanical conditions

Design Optimization of a Pneumatic Soft Robotic Actuator Using Model-Based Optimization and Deep Reinforcement Learning

We present two frameworks for design optimization of a multi-chamber pneumatic-driven soft actuator to optimize its mechanical performance. The design goal is to achieve maximal horizontal motion of the top surface of the actuator with a minimum effect on its vertical motion. The parametric shape and layout of air chambers are optimized individually with the firefly algorithm and a deep reinforcement learning approach using both a model-based formulation and finite element analysis. The presented modeling approach extends the analytical formulations for tapered and thickened cantilever beams connected in a structure with virtual spring elements. The deep reinforcement learning-based approach is combined with both the model- and finite element-based environments to fully explore the design space and for comparison and cross-validation purposes. The two-chamber soft actuator was specifically designed to be integrated as a modular element into a soft robotic pad system used for pressure injury prevention, where local control of planar displacements can be advantageous to mitigate the risk of pressure injuries and blisters by minimizing shear forces at the skin-pad contact. A comparison of the results shows that designs achieved using the deep reinforcement based approach best decouples the horizontal and vertical motions, while producing the necessary displacement for the intended application. The results from optimizations were compared computationally and experimentally to the empirically obtained design in the existing literature to validate the optimized design and methodology

Wearable Knee Assistive Devices for Kneeling Tasks in Construction

Construction workers regularly perform tasks that require kneeling, crawling, and squatting. Working in awkward kneeling postures for prolonged time periods can lead to knee pain, injuries, and osteoarthritis. In this paper, we present lightweight, wearable sensing and knee assistive devices for construction workers during kneeling and squatting tasks. Analysis of kneeling on level and slopped surfaces (0, 10, 20 degs) is performed for single- and double-leg kneeling tasks. Measurements from the integrated inertial measurement units are used for real-time gait detection and lower-limb pose estimation. Detected gait events and pose estimation are used to control the assistive knee-joint torque provided by lightweight exoskeletons with powerful quasi-direct drive actuation. Human subject experiments are conducted to validate the effectiveness of the proposed analysis and control design. The results show reduction in knee extension/flexion muscle activation (up to 39%) during stand-to-kneel and kneel-to-stand tasks. Knee-ground contact forces/pressures are also reduced (up to 15%) under robotic assistance during single-leg kneeling. Increasing assistive knee torque shows redistribution of the subject’s weight from the knee in contact with the ground to both supporting feet. The proposed system provides an enabling tool to potentially reduce musculoskeletal injury risks of construction workers

Prilog poznavanju herpetofaune (Amphibia & Reptilia) donjeg dijela rijeke Neretve (Hrvatska i Bosna i Hercegovina)

In this paper we present newly collected data and historical overview of the herpetofauna of Neretva River Valley. During two consecutive years (2011, 2012) we collected new data about the presence of reptiles and amphibians in the area, on 25 sampling sites, of which 21 in Croatia and 4 in Bosnia and Herzegovina. During our survey we recorded the presence of 21 species of which 18 are listed in the IUCN Red list. The literature records added another 13 species, so the total number for amphibians and reptiles in the area is 34 species, 11 amphibian and 23 reptiles. With such a high diversity, the area of Neretva River is one of the hotspots of the amphibian and reptile diversity in Croatia. Lower Neretva Valley is now days under a strong anthropogenic influence, and most of the area is used for plantations and intensive agriculture. It is of a critical importance to conserve and protect the remaining natural habitat in the future.U ovom radu predstavljamo novo prikupljene podatke, kao i povijesni pregled herpetofaune doline rijeke Neretve. Tijekom 2011. i 2012. godine prikupili smo podatke o prisutnosti vodozemaca i gmazova na 25 lokaliteta, od kojih se 21 nalazio u Hrvatskoj a 4 u Bosni i Hercegovini. Tijekom našeg istraživanja utvrdili smo prisutnost 21 vrste, od kojih je 18 navedeno na IUCN-ovom Crvenom Popisu. Literaturnim nalazima utvrdili smo prisutnost još 13 vrsta, tako da je poznati broj vrsta na području Neretve 34, od čega 11 vrsta vodozemaca i 23 vrste gmazova. Sa ovolikim brojem vrsta, područje rijeke Neretve može se smatrati vrućom točkom bioraznolikosti vodozemaca i gmazova u Hrvatskoj. Donji tok rijeke Neretve je danas pod snažnim antropogenim utjecajem, i veći dio se upotrebljava za plantaže i intenzivnu poljoprivredu. U budućnosti će biti od ključne važnosti očuvati preostala prirodna staništa toga područja

A robotic bipedal model for human walking with slips

Abstract—Slip is the major cause of falls in human locomo-tion. We present a new bipedal modeling approach to capture and predict human walking locomotion with slips. Compared with the existing bipedal models, the proposed slip walking model includes the human foot rolling effects, the existence of the double-stance gait and active ankle joints. One of the major developments is the relaxation of the non-slip assumption that is used in the existing bipedal models. We conduct extensive experiments to optimize the model parameters and to validate the proposed walking model with slips. The experimental results demonstrate that the model successfully predicts the human walking and recovery gaits with slips. I

Classifying hazardous movements and loads during manual materials handling using accelerometers and instrumented insoles.

Improper manual material handling (MMH) techniques are shown to lead to low back pain, the most common work-related musculoskeletal disorder. Due to the complex nature and variability of MMH and obtrusiveness and subjectiveness of existing hazard analysis methods, providing systematic, continuous, and automated risk assessment is challenging. We present a machine learning algorithm to detect and classify MMH tasks using minimally-intrusive instrumented insoles and chest-mounted accelerometers. Six participants performed standing, walking, lifting/lowering, carrying, side-to-side load transferring (i.e., 5.7 kg and 12.5 kg), and pushing/pulling. Lifting and carrying loads as well as hazardous behaviors (i.e., stooping, overextending and jerky lifting) were detected with 85.3%/81.5% average accuracies with/without chest accelerometer. The proposed system allows for continuous exposure assessment during MMH and provides objective data for use with analytical risk assessment models that can be used to increase workplace safety through exposure estimation