Assistance strategies for robotized laparoscopy

Robotizing laparoscopic surgery not only allows achieving better accuracy to operate when a scale factor is applied between master and slave or thanks to the use of tools with 3 DoF, which cannot be used in conventional manual surgery, but also due to additional informatic support. Relying on computer assistance different strategies that facilitate the task of the surgeon can be incorporated, either in the form of autonomous navigation or cooperative guidance, providing sensory or visual feedback, or introducing certain limitations of movements. This paper describes different ways of assistance aimed at improving the work capacity of the surgeon and achieving more safety for the patient, and the results obtained with the prototype developed at UPC.Peer ReviewedPostprint (author's final draft

Robotic Platforms for Assistance to People with Disabilities

People with congenital and/or acquired disabilities constitute a great number of dependents today. Robotic platforms to help people with disabilities are being developed with the aim of providing both rehabilitation treatment and assistance to improve their quality of life. A high demand for robotic platforms that provide assistance during rehabilitation is expected because of the health status of the world due to the COVID-19 pandemic. The pandemic has resulted in countries facing major challenges to ensure the health and autonomy of their disabled population. Robotic platforms are necessary to ensure assistance and rehabilitation for disabled people in the current global situation. The capacity of robotic platforms in this area must be continuously improved to benefit the healthcare sector in terms of chronic disease prevention, assistance, and autonomy. For this reason, research about human–robot interaction in these robotic assistance environments must grow and advance because this topic demands sensitive and intelligent robotic platforms that are equipped with complex sensory systems, high handling functionalities, safe control strategies, and intelligent computer vision algorithms. This Special Issue has published eight papers covering recent advances in the field of robotic platforms to assist disabled people in daily or clinical environments. The papers address innovative solutions in this field, including affordable assistive robotics devices, new techniques in computer vision for intelligent and safe human–robot interaction, and advances in mobile manipulators for assistive tasks

Owl and Lizard: Patterns of Head Pose and Eye Pose in Driver Gaze Classification

Accurate, robust, inexpensive gaze tracking in the car can help keep a driver safe by facilitating the more effective study of how to improve (1) vehicle interfaces and (2) the design of future Advanced Driver Assistance Systems. In this paper, we estimate head pose and eye pose from monocular video using methods developed extensively in prior work and ask two new interesting questions. First, how much better can we classify driver gaze using head and eye pose versus just using head pose? Second, are there individual-specific gaze strategies that strongly correlate with how much gaze classification improves with the addition of eye pose information? We answer these questions by evaluating data drawn from an on-road study of 40 drivers. The main insight of the paper is conveyed through the analogy of an "owl" and "lizard" which describes the degree to which the eyes and the head move when shifting gaze. When the head moves a lot ("owl"), not much classification improvement is attained by estimating eye pose on top of head pose. On the other hand, when the head stays still and only the eyes move ("lizard"), classification accuracy increases significantly from adding in eye pose. We characterize how that accuracy varies between people, gaze strategies, and gaze regions.Comment: Accepted for Publication in IET Computer Vision. arXiv admin note: text overlap with arXiv:1507.0476

ELEXS: E-learning based on expert system shell to enhance problem-solving skills

Computer assisted learning "student-to-terminal" remains a major challenge fur the educational policy makers.The computer plays an important role in the learning process if used in an encompassing learning environment individualized to the learner.The system _features and its design philosophy based upon the artificial intelligence technique.The primary aim is to provide tutoring, functions that achieved certain pedagogical aims. The overall motivation of the system developer is to see how much could be achieved in educational terms by introduction of this type of trainee get maximum benefit from the system.ELEXS would seem to have the potential to help teachers manage their classrooms, design and plan instructional activities. improve teaching strategies, and diagnose student learning problems across all curricular areas.The process of making explicit cognitive, strategies such as these has been shown to enhance meta-cognitive functioning and promote increased problem solving performance.The overall conclusion is that participants learn best when the software is a part of their learning environment as well as to provide consultative assistance to preserve teachers in science concept pedagogy and engender in participants an improved self-confidence toward their own ability to successfully teaching science conten

Improving E-Learning by Integrating a Metacognitive Agent

The major disadvantage of the current Learning Management Systems is the lack of learner assistance in their learning processes and, therefore, they can not replace the presence of the teacher who ensures the progress of learning. In fact, we proposed to integrate, for each learner, a metacognitive agent that supported the metacognitive assistance and extracts the defectsin the learning process and strategies. The goal is to invite the learner to correct himself and improve his learning method. Metacognitive questionnaires were distributed to a group of 100 students before, during and after a computer course. The goal is to evaluatethe metacognitive attributes and to determine their influence on the success of learning. Decision trees were used as data analysis tools to extract a set of rules and to discover the influence of these metacognitive attributes on the result obtained by the learners. The results indicate that there are relationships between the different metacognitive attributes and the learners’ success. We note there is the influence of metacognitive incitement on learner outcomes, which reflects the degree of understanding of a learning pedagogical unit by the learner

Motorcycle detection for ADAS through camera and V2V communication, a comparative analysis of two modern technologies

Motorcycles are one of the most dangerous means of transportation. Its death toll is higher than in others, due to the inherent vulnerability of motorcycle drivers. The latest strategies in Advanced Driving Assistance Systems (ADAS) are trying to mitigate this problem by applying the advances of modern technologies to the road transport. This paper presents two different approaches on motorcycle protection, based on two of the most modern available technologies in ADAS, i.e. Computer Vision and Vehicle to Vehicle Communication (V2V). The first approach is based on data fusion of Laser Scanner and Computer Vision, providing accurate obstacle detection and localization based on laser scanner, and obstacle classification using computer vision and laser. The second approach is based on ad-hoc V2V technology and provides detection in case of occlusion for visual sensors. Both technologies have been tested in the presented work, and a performance comparison is given. Tests performed in different driving situations allows to measure the performance of every algorithm and the limitations of each of them based on empirical and scientific foundations. The conclusions of the presented work help foster of expert systems in the automotive sector by providing further discussion of the viability and impact from each of these systems in real scenarios

Community Building for Children’s Health: Lessons From Community Partnerships for Healthy Children

· This article describes Community Partnerships for Healthy Children (CPHC), a 10-year, $17 million initiative of the Sierra Health Foundation targeted at improving children’s health in northern California by mobilizing communities to use their assets. Implementation grants were modest ($50,000 annually), but technical assistance and communications support were also provided. · The initiative rolled out in four phases. Overall, a total of 31 communities participated in the initiative. Twenty-six communities remained through phase three, with 18 engaging in the final fourth phase. · Evidence indicates that CPHC improved the health of some children in some communities with regard to some outcomes, but did not improve the health of children at the population level. Community building appears to be well-suited to devising and implementing successful strategies to address straightforward health issues in the short term; more time, resources, and expertise are needed for more complex problems. · The community collaboratives achieved many of the intermediate goals of the initiative. The evidence is strong that communities did identify and respond to needs. · Most of the collaboratives on their own had access to few resources initially, but over time they were able to gather fiscal and human resources from a variety of sources and combine them to provide services such as recreation programs or family resource centers. Collaboratives involved in the final grant stage had been able to raise from other sources an amount nearly twice the foundation’s investment in CPHC. · The collaboratives were similar in role but differed in many other ways, such as the geographic scope and the existing assets. Collaboratives that had members with certain skills (such as grantwriting, public relations, and computer skills) had greater success

2011-2013 Connecting Consumer with Care: Grant Area Evaluation

The Blue Cross Blue Shield of Massachusetts Foundation has funded the Connecting Consumers with Care grant program consistently since 2001. The program supports community health centers and community-based organizations in helping consumers enroll in and maintain publicly subsidized health insurance coverage. The program also encourages collaborative problem solving to minimize system-level barriers and enhanced education and empowerment of consumers so that they may navigate systems of health coverage and care with decreasing dependence on grantee organizations. During the October 2011 -- September 2013 grant cycle, the Foundation funded 13 organizations across Massachusetts. While this funding period preceded the first Affordable Care Act (ACA) open enrollment period, lessons from the outreach, enrollment, and post-enrollment work of these grantees remain invaluable to efforts to connect consumers with health coverage and care both in Massachusetts and across the country.This report describes findings from the evaluation of the 2011 -- 2013 grant cycle. The aims of the evaluation were to 1) assess progress made across the grantee sites on select outreach and enrollment measures; 2) describe the practices grantees adopted to reach out to and enroll consumers in insurance, increase consumer self-sufficiency, and collaborate with other agencies to minimize barriers to care; and 3) characterize barriers experienced by grantees as they worked to meet the goals of the program

Unmanned Aerial Systems for Wildland and Forest Fires

Wildfires represent an important natural risk causing economic losses, human death and important environmental damage. In recent years, we witness an increase in fire intensity and frequency. Research has been conducted towards the development of dedicated solutions for wildland and forest fire assistance and fighting. Systems were proposed for the remote detection and tracking of fires. These systems have shown improvements in the area of efficient data collection and fire characterization within small scale environments. However, wildfires cover large areas making some of the proposed ground-based systems unsuitable for optimal coverage. To tackle this limitation, Unmanned Aerial Systems (UAS) were proposed. UAS have proven to be useful due to their maneuverability, allowing for the implementation of remote sensing, allocation strategies and task planning. They can provide a low-cost alternative for the prevention, detection and real-time support of firefighting. In this paper we review previous work related to the use of UAS in wildfires. Onboard sensor instruments, fire perception algorithms and coordination strategies are considered. In addition, we present some of the recent frameworks proposing the use of both aerial vehicles and Unmanned Ground Vehicles (UV) for a more efficient wildland firefighting strategy at a larger scale.Comment: A recent published version of this paper is available at: https://doi.org/10.3390/drones501001

States of Change

States of Change documents efforts by state policymakers and local practitioners to devise useful approaches to helping low-income job seekers stay employed and begin advancing. It draws, in part, from our experiences working on these issues since 1997 with five states -- Washington, Oregon, Colorado, Oklahoma and Florida -- as well as on examples and lessons in several other states. In general, states are trying a number of retention strategies, but few have been tested. Therefore, we expect that many strategies discussed will soon be modified or replaced with new approaches. We hope that States of Change encourages this process of testing and innovation by providing a sense of what is being tried and learned around the country, and what challenges remain