Computer Aided Industrial Design

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COMPARATIVE GAIT ANALYSIS BETWEEN CHILDREN WITH AUTISM AND AGE MATCHED CONTROLS

There are very few studies that have analyzed the gait of children with autism. The purpose of this study was to investigate gait of children with autism using temporal-spatial variables. Fifteen children with autism and fifteen age matched typically developing children walked 3 times on the GAITRite® system. Dependent variables were statistically analyzed using independent samples t-tests with Bonferroni adjustments. Results show a reduction in cadence, gait velocity, step length and an increase in step width for the children with autism. In conclusion, our results suggest that the children with autism have abnormal gait compared to age matched controls

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Abstract The gravitational waves (GW170817) produced during a binary neutron star inspiral, followed by a gamma-ray burst (GRB 170817A) and afterglows from X-ray to radio wavelength, were observed. By combining the distance obtained from gravitational waves with the red shift obtained from electromagnetic waves, even the Hubble constant was estimated. This indicates the start of new era of multimessenger astronomy. In addition to the masses of inspiralling neutron stars, the tidal deformability, which depends on the inner structures of neutron stars, has been estimated from gravitational waves. This confirms that even strong interactions can be tested by using gravitational waves. In this article, we review the effect of the tidal deformability of neutron stars on the gravitational waves produced during the inspiral process and discuss the implications of the detected tidal deformability for the neutron star's equations of state

THE EFFECTS OF WEARING ROLLER SHOES ON MUSCLE ACTIVITY IN THE LOWER EXTREMITY DURING WALKING

Roller shoes have become increasingly popular among children and its features of retractable wheels which allow the user to walk or roll without changing the footwear. Maintaining balance during forward walking with roller shoes is not an easy task. To prevent falling backward, the user needs to lock the knees and tighten the ankles and thighs while the upper body is slightly leaning forward. Constant walking with roller shoes forces the user to walk in a manner much different from normal gait. Prolonged exposure to un-natural stresses on human body forces our body to evolve by strengthening those incorrect and temporary functions (Clement et al., 1981). For children, the chronic stress may lead to serious injuries in the lower extremity later in life. If any potential of injury exists in a movement it is critical to examine the associated muscle activity that may lead to injury. To the best of our knowledge, the effects of wearing roller shoes on muscle activity in the lower extremity have rarely been studied, especially in the youth population. Thus, the purpose of this study was to compare muscle activity in the lower extremity during walking wearing jogging and roller shoes

Class-Attentive Diffusion Network for Semi-Supervised Classification

Recently, graph neural networks for semi-supervised classification have been widely studied. However, existing methods only use the information of limited neighbors and do not deal with the inter-class connections in graphs. In this paper, we propose Adaptive aggregation with Class-Attentive Diffusion (AdaCAD), a new aggregation scheme that adaptively aggregates nodes probably of the same class among K-hop neighbors. To this end, we first propose a novel stochastic process, called Class-Attentive Diffusion (CAD), that strengthens attention to intra-class nodes and attenuates attention to inter-class nodes. In contrast to the existing diffusion methods with a transition matrix determined solely by the graph structure, CAD considers both the node features and the graph structure with the design of our class-attentive transition matrix that utilizes a classifier. Then, we further propose an adaptive update scheme that leverages different reflection ratios of the diffusion result for each node depending on the local class-context. As the main advantage, AdaCAD alleviates the problem of undesired mixing of inter-class features caused by discrepancies between node labels and the graph topology. Built on AdaCAD, we construct a simple model called Class-Attentive Diffusion Network (CAD-Net). Extensive experiments on seven benchmark datasets consistently demonstrate the efficacy of the proposed method and our CAD-Net significantly outperforms the state-of-the-art methods. Code is available at https://github.com/ljin0429/CAD-Net.Comment: Accepted to AAAI 202

IJA: An Efficient Algorithm for Query Processing in Sensor Networks

One of main features in sensor networks is the function that processes real time state information after gathering needed data from many domains. The component technologies consisting of each node called a sensor node that are including physical sensors, processors, actuators and power have advanced significantly over the last decade. Thanks to the advanced technology, over time sensor networks have been adopted in an all-round industry sensing physical phenomenon. However, sensor nodes in sensor networks are considerably constrained because with their energy and memory resources they have a very limited ability to process any information compared to conventional computer systems. Thus query processing over the nodes should be constrained because of their limitations. Due to the problems, the join operations in sensor networks are typically processed in a distributed manner over a set of nodes and have been studied. By way of example while simple queries, such as select and aggregate queries, in sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. Therefore, in this paper, we propose and describe an Incremental Join Algorithm (IJA) in Sensor Networks to reduce the overhead caused by moving a join pair to the final join node or to minimize the communication cost that is the main consumer of the battery when processing the distributed queries in sensor networks environments. At the same time, the simulation result shows that the proposed IJA algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join algorithm

Establishment, Regeneration, and Succession of Korean Red Pine (Pinus densiflora S. et Z.) Forest in Korea

Seed production of Korean red pine (Pinus densiflora Siebold & Zucc.) was ranging from 25 to 27 seeds/m2 with a viability averaging between 42 and 44%. Seed dispersal reaches about 80 m. Germination rate of seed varied from 19 to 90%, and survival rate of seedling varied from 0 to 30% depending on moisture condition in field experiment. Survivorship curve of the pine population showed type III. Species composition of the pine forest was characterized by possessing plants with resistant capacity to water deficit such as Rhododendron micranthum, Vaccinium hirtum var. koreanum, Spodiopogon sibiricus, and Lespedeza cyrtobotrya. Ecological longevity of the pine was about 140 years based on mean age of gap makers. Natural maintenance of the pine forest depended on disturbance regime, which is dominated by endogenous factor. Natural regeneration of the pine forest is possible only in a very restricted site such as ridgetop with thin and infertile soil condition. Therefore, active and systematic management is required for artificial regeneration of the forest as is known in silivicultural method. Pine gall midge damage accelerated succession of the pine forest to the deciduous broadleaved forest dominated by oak except on the ridgetop where the forest can be maintained naturally

The Impact of SST-Forced and Unforced Teleconnections on 2015/16 El Nino Winter Precipitation over the Western United States

The factors impacting western U.S. winter precipitation during the 2015/16 El Nio are investigated using the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data, and simulations with the Goddard Earth Observing System version 5 (GEOS-5) atmospheric general circulation model forced with specified sea surface temperatures (SSTs). Results reveal that the simulated response to the tropical Pacific SST associated with the 2015/16 El Nio was to produce wetter than normal conditions over much of the west coast including California - a result at odds with the negative precipitation anomalies observed over much of the Southwestern U.S. It is shown that two factors acted to partly counter the canonical ENSO response in that region. First, a potentially predictable but modest response to the unusually strong and persistent warm SST in the northeastern Pacific decreased precipitation in the Southwestern U.S. by increasing sea level pressure, driving anticyclonic circulation and atmospheric descent, and reducing moisture transport into that region. Second, large-scale unforced (by SST) components of atmospheric variability (consisting of the leading modes of unpredictable intra-ensemble variability) resembling the positive phase of the North Atlantic Oscillation and Arctic Oscillation are found to be an important contributor to the drying over the western U.S. While a statistical reconstruction of the precipitation from our simulations that account for internal atmospheric variability does much to close the gap between the ensemble mean and observed precipitation in the Southwestern U.S., some differences remain, indicating that model error is also playing a role