Moving the needle—what does RSAP look for and what does it aim to do?

Peer reviewe

Probabilistic alternate path analysis of steel moment-resisting frames

This research presents a probabilistic assessment of progressive collapse in intermediate Steel Moment-Resisting Frames (SMRFs) subjected to different levels of column damage. Damage levels were represented by gradual reductions in column stiffness to the extent that tensile forces are created in columns sustaining large deformations, and columns were allowed to enter completely plastic zone. To this aim, low- to mid-rise structures with 4, 8, and 12 stories were examined. The effect of composite slabs on the vertical displacement response of SMRFs was taken as a variable. A number of 11 column damage scenarios were defined with either one or two damaged columns, located at different positions in the plan, which were applied to all floor levels. Incremental dynamic analysis was conducted for each damage scenario using the finite element OpenSees framework. Moreover, a state-of-the-art approach was employed in fragility analysis. The results showed that higher floors are more sensitive to partial damage due to less structural components involved in progressive collapse. However, in case of large damages, lower floors prove to be more critical due to greater deal of gravity loads. Shorter and taller structures perform better in large and partial damages to column, respectively. Moreover, the failure probability of SMRFs reduced by considering the composite slab stiffness. Subjected to single-column damage scenarios, SMRFs reach life safety limit state once tensile forces are created in the damaged column. In contrast, all performance levels are met in double-column damages when the column has still its compressive capacity

Multiple Object Tracking in Urban Traffic Scenes with a Multiclass Object Detector

Multiple object tracking (MOT) in urban traffic aims to produce the trajectories of the different road users that move across the field of view with different directions and speeds and that can have varying appearances and sizes. Occlusions and interactions among the different objects are expected and common due to the nature of urban road traffic. In this work, a tracking framework employing classification label information from a deep learning detection approach is used for associating the different objects, in addition to object position and appearances. We want to investigate the performance of a modern multiclass object detector for the MOT task in traffic scenes. Results show that the object labels improve tracking performance, but that the output of object detectors are not always reliable.Comment: 13th International Symposium on Visual Computing (ISVC

Visualising kinematics of an elastic Ossur ESR prosthetic foot using novel low-cost optical tracking systems

A novel method of measuring kinematics of elastic body is the subject of this investigation. Unlike kinematics of rigid body large elastic deformation tends to modify the dynamics of motion. In the case of amputee runner the change in kinematics of the foot depends on the stiffness, body mass and running beat frequency. Current measurement techniques, such as gait analysis assumes rigid elements. Currently there are inertia measurement unit (IMU) based systems that uses accelerometers and gyro to determine acceleration, velocities and orientations of the sensors. They are not capable of measuring changes in lengths or positions of the objects that they are attached to. For that reason predicting velocities and displacement by integrating acceleration is not always viable due to time step limits of the integrations that are necessary. Here a new optical device is developed and presented that is accurate and is practically error free to monitor Foot elastic deformation. In this paper the Dynamic elastic response of Ossur Running foot is being investigated using this device. The data generated show complete phase synchronisation with IMU but much better accuracy in terms of velocity and relative displacement of the feet due to flexure as a result of elastic response to Impulse

Capabilities and advantages of cloud computing in the implementation of Electronic Health Record

Background: With regard to the high cost of the Electronic Health Record (EHR), in recent years the use of new technologies, in particular cloud computing, has increased. The purpose of this study was to review systematically the studies conducted in the field of cloud computing. Methods: The present study was a systematic review conducted in 2017. Search was performed in the Scopus, Web of Sciences, IEEE, Pub Med and Google Scholar databases by combination keywords. From the 431 article that selected at the first, after applying the inclusion and exclusion criteria, 27 articles were selected for surveyed. Data gathering was done by a self-made check list and was analyzed by content analysis method. Results: The finding of this study showed that cloud computing is a very widespread technology. It includes domains such as cost, security and privacy, scalability, mutual performance and interoperability, implementation platform and independence of Cloud Computing, ability to search and exploration, reducing errors and improving the quality, structure, flexibility and sharing ability. It will be effective for electronic health record. Conclusion: According to the findings of the present study, higher capabilities of cloud computing are useful in implementing EHR in a variety of contexts. It also provides wide opportunities for managers, analysts and providers of health information systems. Considering the advantages and domains of cloud computing in the establishment of HER, it is recommended to use this technology. © 2018 Maryam Ahmadi, Nasim Aslani

The effect of environmental education on female and male students' knowledge level through visual mass media

This study investigates the effects of environmental education on female and male students' knowledge level through visual mass media. The data gathered by researcher made questionnaire which the specialist calculated its reliability (0.77). To get the research aim researcher used semi experimental method using the pre-test and post-test method between experimental and control group. The sample of this study was 60 university students who were selected by simple randomly among 1450 students of Shahid Rajaee teacher training university that didn't pass any course about the environment. Then they were divided randomly to experimental (n = 30) and control (n = 30) groups. The experimental group was taught by using visual (film) mass media, while the control group didn't receive any education. The information processed and analyzed by independent t-test. Results showed that the visual mass media have a positive impact on environmental knowledge of the students. So it is recommended to use visual media productions (videos, clips, etc.) as a platform for delivering knowledge, information and education,  in environmental issues

Techno-economic assessment and optimization of a solar-assisted industrial post-combustion CO2 capture and utilization plant

This paper studies the techno-economic feasibility of the solar-assisted regeneration process of the largest industrial CO2 removal monoethanolamine-based plant in Iran. The plant incorporating parabolic troughs is modelled using System Advisor Model software and the weather data are derived from the European Commission's Photovoltaic Geographical Information System. Sensitivity analyses are realized to evaluate the effect of important parameters, i.e., the solar multiple and the hours of storage, and to reveal the optimum case. The studied impacts are linked to the overall net energy generation and the levelized cost of heat (LCOH). The optimum case is found to have a solar multiple of 3.1 and 18-hours of storage, resulting in a solar share of 0.7 and a LCOH of 3.85 (¢/kWh). When compared to the base case (solar multiple of 2 and 6 h of storage), the optimum solution results in a similar LCOH but it achieves the generation of an additional 16,112 MWhth annually. The thermal energy supplied by the solar system leads to an annual reduction in the natural gas consumption of approximately 3.8 million m3 that results in a CO2 emission reduction of 7.1 kton.The corresponding authors would like to acknowledge the University of Tehran and the Iran’s National Elites Foundation for providing support at this work. The authors would also like to thank Paul Gilman from SAM support at the National Renewable Energy Laboratory. Last but not least, technical supports of the Kermanshah Petrochemical Industries Co. and the Shahrekord Carbon Dioxide Co. are gratefully acknowledged. Fontina Petrakopoulou would like to thank the Spanish Min- istry of Science, Innovation and Universities and the Universi- dad Carlos III de Madrid (Ramón y Cajal Programme, RYC-2016- 20971)

Multi-task localization of the hemidiaphragms and lung segmentation in portable chest X-ray images of COVID-19 patients

BACKGROUND: The COVID-19 can cause long-term symptoms in the patients after they overcome the disease. Given that this disease mainly damages the respiratory system, these symptoms are often related with breathing problems that can be caused by an affected diaphragm. The diaphragmatic function can be assessed with imaging modalities like computerized tomography or chest X-ray. However, this process must be performed by expert clinicians with manual visual inspection. Moreover, during the pandemic, the clinicians were asked to prioritize the use of portable devices, preventing the risk of cross-contamination. Nevertheless, the captures of these devices are of a lower quality. OBJECTIVES: The automatic quantification of the diaphragmatic function can determine the damage of COVID-19 on each patient and assess their evolution during the recovery period, a task that could also be complemented with the lung segmentation. METHODS: We propose a novel multi-task fully automatic methodology to simultaneously localize the position of the hemidiaphragms and to segment the lung boundaries with a convolutional architecture using portable chest X-ray images of COVID-19 patients. For that aim, the hemidiaphragms’ landmarks are located adapting the paradigm of heatmap regression. RESULTS: The methodology is exhaustively validated with four analyses, achieving an 82.31% 2.78% of accuracy when localizing the hemidiaphragms’ landmarks and a Dice score of 0.9688 0.0012 in lung segmentation. CONCLUSIONS: The results demonstrate that the model is able to perform both tasks simultaneously, being a helpful tool for clinicians despite the lower quality of the portable chest X-ray images