Design and update of a classification system: The UCSD map of science

Global maps of science can be used as a reference system to chart career trajectories, the location of emerging research frontiers, or the expertise profiles of institutes or nations. This paper details data preparation, analysis, and layout performed when designing and subsequently updating the UCSD map of science and classification system. The original classification and map use 7.2 million papers and their references from Elsevier's Scopus (about 15,000 source titles, 2001-2005) and Thomson Reuters' Web of Science (WoS) Science, Social Science, Arts & Humanities Citation Indexes (about 9,000 source titles, 2001-2004)-about 16,000 unique source titles. The updated map and classification adds six years (2005-2010) of WoS data and three years (2006-2008) from Scopus to the existing category structure-increasing the number of source titles to about 25,000. To our knowledge, this is the first time that a widely used map of science was updated. A comparison of the original 5-year and the new 10-year maps and classification system show (i) an increase in the total number of journals that can be mapped by 9,409 journals (social sciences had a 80% increase, humanities a 119% increase, medical (32%) and natural science (74%)), (ii) a simplification of the map by assigning all but five highly interdisciplinary journals to exactly one discipline, (iii) a more even distribution of journals over the 554 subdisciplines and 13 disciplines when calculating the coefficient of variation, and (iv) a better reflection of journal clusters when compared with paper-level citation data. When evaluating the map with a listing of desirable features for maps of science, the updated map is shown to have higher mapping accuracy, easier understandability as fewer journals are multiply classified, and higher usability for the generation of data overlays, among others

Design and update of a classification system : the UCSD map of science

Global maps of science can be used as a reference system to chart career trajectories, the location of emerging research frontiers, or the expertise profiles of institutes or nations. This paper details data preparation, analysis, and layout performed when designing and subsequently updating the UCSD map of science and classification system. The original classification and map use 7.2 million papers and their references from Elsevier’s Scopus (about 15,000 source titles, 2001–2005) and Thomson Reuters’ Web of Science (WoS) Science, Social Science, Arts & Humanities Citation Indexes (about 9,000 source titles, 2001–2004)–about 16,000 unique source titles. The updated map and classification adds six years (2005–2010) of WoS data and three years (2006–2008) from Scopus to the existing category structure–increasing the number of source titles to about 25,000. To our knowledge, this is the first time that a widely used map of science was updated. A comparison of the original 5-year and the new 10-year maps and classification system show (i) an increase in the total number of journals that can be mapped by 9,409 journals (social sciences had a 80% increase, humanities a 119% increase, medical (32%) and natural science (74%)), (ii) a simplification of the map by assigning all but five highly interdisciplinary journals to exactly one discipline, (iii) a more even distribution of journals over the 554 subdisciplines and 13 disciplines when calculating the coefficient of variation, and (iv) a better reflection of journal clusters when compared with paper-level citation data. When evaluating the map with a listing of desirable features for maps of science, the updated map is shown to have higher mapping accuracy, easier understandability as fewer journals are multiply classified, and higher usability for the generation of data overlays, among others

Locomotor adaptation to a powered ankle-foot orthosis depends on control method

<p>Abstract</p> <p>Background</p> <p>We studied human locomotor adaptation to powered ankle-foot orthoses with the intent of identifying differences between two different orthosis control methods. The first orthosis control method used a footswitch to provide bang-bang control (a kinematic control) and the second orthosis control method used a proportional myoelectric signal from the soleus (a physiological control). Both controllers activated an artificial pneumatic muscle providing plantar flexion torque.</p> <p>Methods</p> <p>Subjects walked on a treadmill for two thirty-minute sessions spaced three days apart under either footswitch control (n = 6) or myoelectric control (n = 6). We recorded lower limb electromyography (EMG), joint kinematics, and orthosis kinetics. We compared stance phase EMG amplitudes, correlation of joint angle patterns, and mechanical work performed by the powered orthosis between the two controllers over time.</p> <p>Results</p> <p>During steady state at the end of the second session, subjects using proportional myoelectric control had much lower soleus and gastrocnemius activation than the subjects using footswitch control. The substantial decrease in triceps surae recruitment allowed the proportional myoelectric control subjects to walk with ankle kinematics close to normal and reduce negative work performed by the orthosis. The footswitch control subjects walked with substantially perturbed ankle kinematics and performed more negative work with the orthosis.</p> <p>Conclusion</p> <p>These results provide evidence that the choice of orthosis control method can greatly alter how humans adapt to powered orthosis assistance during walking. Specifically, proportional myoelectric control results in larger reductions in muscle activation and gait kinematics more similar to normal compared to footswitch control.</p

Mobile sensing systems

Thesis: S.M. in Naval Architecture and Marine Engineering, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.Thesis: Mech. E., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 213-217).Recent advances in small-scale portable computing have lead to an explosion in swarming as a viable method to approach large-scale data problems in the commercial, scientific, and defense sectors. This increased attention to large-scale swarm robotics has lead to an increase in swarm intelligence concepts, giving more potential to address issues more effectively and timely than any single unit. However, the majority of today's autonomous platforms are prohibitively costly and too complex for marketable research applications. This is particularly true when considering the demands required to be temporally and spatially pervasive in a marine environment. This work presents a low cost, portable, and highly maneuverable platform as a method to collect, share, and process environmental data. Our platform is modular, allowing a variety of sensor combinations, and may yield a heterogeneous swarm. Kalman filters are utilized to provide integrated, real-time dynamic self-awareness. In addition to an environmentally savvy platform, we define computational framework and characteristics, which allow complex problems to be solved in a distributed and collective manner. This computational framework includes two methods for scalar field estimation, which rely on low order orthogonal Hermite basis functions. Low order fits provide a natural method for low-pass filtering, thus avoiding ambient noise recovery in the reconstruction process. Real-time sampling and recovery allow for individual and collectively autonomous behaviors driven through globally assessed environmental parameters. Finally, we give evidence that large numbers can cooperatively tackle large-scale problems much more efficiently and timely than more capable and expensive units. This is particularly true when utilizing a unique methodology, presented herein, to best assemble in order to most affectively reconstruct sparse spatial scalar fields.by Brandon M. Zoss.S.M. in Naval Architecture and Marine EngineeringMech. E