Forecasting Enrollment Model Based on First-Order Fuzzy Time Series

This paper proposes a novel improvement of forecasting approach based on using time-invariant fuzzy time series. In contrast to traditional forecasting methods, fuzzy time series can be also applied to problems, in which historical data are linguistic values. It is shown that proposed time-invariant method improves the performance of forecasting process. Further, the effect of using different number of fuzzy sets is tested as well. As with the most of cited papers, historical enrollment of the University of Alabama is used in this study to illustrate the forecasting process. Subsequently, the performance of the proposed method is compared with existing fuzzy time series time-invariant models based on forecasting accuracy. It reveals a certain performance superiority of the proposed method over methods described in the literature

Detection and prediction of falls among elderly people using walkers

Falls of elderly people are big health burden, especially for long-term consequence. Yet we already have research, describing how exactly elderly fall and reasons of falls. We aimed to develop means that could not only detect falls and send alerts to relatives and doctors to conquer one of the biggest fears of elderly to fall and do not have the ability to call for help, but also tried to implement fall prevention system. This system based on “relatively safe walking patterns” that our system tries to detect during the walk. During the work we used SensorTag 2.0 CC2650 sensors, iPhone and Apple Watch to collect motion data (Gyroscope, Accelerometer and Magnetometer) and compared the accuracy of each device. As we chosen iPhone and Apple Watch to use Core ML framework to integrate the neural network model we generated using Keras into prototype app. The iPhone app perfectly detects falls, but it needs to collect data more accurately, to improve the machine learning model to improve the work of prediction falls. The Apple Watch app does not work acceptable, despite well prepared Keras model and requires revision

Experimental observation of steady and drifting roll patterns in a nonlinear optical system near a codimension-two point

We report the first, to our knowledge, experimental investigation of a two-component Kerr-type nonlinear optical system with diffractive feedback. In accordance with theoretical predictions, transitions between steady and drifting roll patterns were experimentally observed near a certain point of the parameter space. Temporal frequency of the drifting rolls measured as a function of control parameters agreed qualitatively with the theoretical dependence

The influence of residual stresses in welded structures on the limit stresses of the cycle

Author proposes a method of determination of the diagrams of ultimate stresses in a cycle for welded components structural elements with different level of steady-state residual stresses based on test results for small specimen

Remote Sensing of Chiral Signatures on Mars

We describe circular polarization as a remote sensing diagnostic of chiral signatures which may be applied to Mars. The remarkable phenomenon of homochirality provides a unique biosignature which can be amenable to remote sensing through circular polarization spectroscopy. The natural tendency of microbes to congregate in close knit communities would be beneficial for such a survey. Observations of selected areas of the Mars surface could reveal chiral signatures and hence explore the possibility of extant or preserved biological material. We describe a new instrumental technique that may enable observations of this form.Comment: 14 pages, 3 figures; to be published in Planetary and Space Scienc

Spatial Topology and its Structural Analysis based on the Concept of Simplicial Complex

This paper introduces a model that identifies spatial relationships for a structural analysis based on the concept of simplicial complex. The spatial relationships are identified through overlapping two map layers, namely a primary layer and a contextual layer. The identified spatial relationships are represented as a simplical complex, in which simplices and vertices respectively represent two layers of objects. The model relies on the simplical complex for structural representation and analysis. To quantify structural properties of individual primary objects (or equivalently simplices), and the simplicial complex as a whole, we define a set of centrality measures by considering multidimensional chains of connectivity, i.e. the number of contextual objects shared by a pair of primary objects. With the model, the interaction and relationships with a geographic system are modeled from both local and global perspectives. The structural properties and modeling capabilities are illustrated with a simple example and a case study applied to the structural analysis of an urban system.Comment: 14 pages, 7 figures, 2 tables, submitted for publicatio

The Flow Dimension and Capacity for Structuring Urban Street Networks

This paper aims to measure the efficiency of urban street networks (a kind of complex networks) from the perspective of the multidimensional chain of connectivity (or flow). More specifically, we define two quantities: flow dimension and flow capacity, to characterize structures of urban street networks. To our surprise for the topologies of urban street networks, previously confirmed as a form of small world and scale-free networks, we find that (1) the range of their flow dimension is rather wider than their random and regular counterparts, (2) their flow dimension shows a power-law distribution, and (3) they have a higher flow capacity than their random and regular counterparts. The findings confirm that (1) both the wider range of flow dimension and the higher flow capacity can be a signature of small world networks, and (2) the flow capacity can be an alternative quantity for measuring the efficiency of networks or that of the individual nodes. The findings are illustrated using three urban street networks (two in the Europe and one in the USA).Comment: 14 pages, 9 figures, 4 tables, revised November 200

The Withering Away of the Danger Society: The Pensions Reforms of 1956 and 1964 in the Soviet Union

While a framework of statist welfare practices was constructed in the 1930s, the principles that underwrote it—and that defined the interaction of individual citizens and state agencies—were changed as a consequence of World War II and transformed as a result of Stalin's death and the onset of de-Stalinization. Following a major sequence of welfare reforms in the Khrushchev period, most people's encounters with social risk were substantially minimized. By the Brezhnev era, problems associated with moral hazard were creating new challenges for policy makers: not only did people enjoy the right to a job, as they had done for decades, but perverse incentives discouraged innovation and, for some, hard work. A welfare system had been established that went far beyond the universalism of Western Europe. Cash transfers diffused social risks. Furthermore, welfare touched almost all areas of life, from jobs to leisure, creating a new kind of industrial society, in which many social risks had been artificially eliminated. The effectiveness of this system was highly uneven, and many miserable examples of welfare provision persisted, but this revised relationship between risk and welfare guided the mentalities of policy makers and ordinary people alike. This article offers a commentary on the long-term nature of this process but focuses particularly on the reforms associated with Khrushchev, especially the pension laws of 1956 and 1964.</jats:p

Using CRISPR-Cas9 to Generate Isogenic Controls from DCMA Patient-Derived Induced Pluripotent Stem Cells

Dilated cardiomyopathy with ataxia syndrome (DCMA) is an autosomal recessive disease frequently characterized by heart failure in early childhood. Although globally rare, DCMA is common in the Hutterites of southern Alberta who represent the largest collection of patients in the world. Alberta Children’s Hospital investigators previously identified a single intronic G>C mutation in the poorly characterized gene DNAJC19 as being responsible for DCMA. In collaboration with Stanford University, we have generated induced pluripotent stem cell (iPSCs) from DCMA patient peripheral blood mononuclear cells. Differentiating iPSCs into beating cardiomyocytes (iPSC-CMs) creates a disease-, patient-, and tissue-specific in vitro model of DCMA. However, our current model system has limitations due to lack of appropriately matched controls. This thesis aimed to create isogenic controls from our patient-derived iPSCs using the clusters of regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated endonuclease 9 (Cas9) system. We hypothesized that repairing the G>C mutation in DNAJC19 of our patient iPSCs will produce iPSC-CMs with a phenotype comparable to healthy controls and introducing the G>C mutation into DNAJC19 of healthy iPSCs will produce iPSC-CMs with a DCMA phenotype. Although isogenic controls have yet to be derived, this thesis outlines a potential workflow for the genomic editing of DCMA iPSCs. Our approach utilizes the use of an RNP-complex system that is delivered to iPSCs via lipofection using Lipofectamine Stem