Technicolor (United States)

The article considers the urgent problem of professional self-determination of students of professional educational organizations in the conditions of the modern labor market and dynamic socio-economic changes. The relevance of the study is due to the need to popularize effective models of forming students’ sustainable professional orientations in the process of teaching academic disciplines. The authors appeal to the topic of professional self-determination is caused by the influence of secondary factors on the choice of profession by students, which negatively affects the career of the students themselves, the quality of education and the country’s economy. The main goal of the study was to develop models of forming students’ sustainable professional orientations in private practice of teaching an academic discipline and a set of measures for their organizational and pedagogical support. The importance of a conscious and personally oriented choice of profession for successful professional development and development of the country’s economy is highlighted. The authors analyzes existing theoretical approaches and definitions of the concept of professional self-determination, as well as factors influencing the choice of profession, including socio-economic, psychological and psychophysical aspects. The article presents the results of empirical studies confirming the need to introduce organizational and pedagogical support for this process in professional education. Based on methodological approaches (competency-based, system-activity-based and personality-oriented), a comprehensive model of supporting students’ professional self-determination is proposed, implemented through academic disciplines using innovative forms and methods of teaching, such as project-based learning, career counseling, simulation games and trainings. Particular attention is paid to the role of the educational process in the formation of students’ sustainable professional guidelines, which helps to increase their motivation and conscious perception of their future professional activities. The article analyzes the results of testing the model of organizational and pedagogical support for professional self-determination within the academic discipline «Marketing» for students majoring in 38.02.04. The article emphasizes the need for a systematic approach to organizing the educational environment and pedagogical support for successful professional self-determination of young people and the development of human resources. The results of the study may be useful for teachers, heads of professional organizations and specialists in the field of career guidance.

espanolLa innovacion es fundamental para conseguir el exito y la competitividad en cualquier empresa, y hace posible que esta pueda responder a los cambios del entorno manteniendo una posicion competitiva. El exito al implantar una estrategia de innovacion en una organizacion dependera de varios factores: el ciclo economico, las cinco fuerzas de Porter, el mercado, etc. y sobre todo los recursos humanos de la empresa. Cuando se pretende incluir la innovacion como estrategia empresarial, los recursos humanos seran la clave para conseguirlo. La mezcla exacta de liderazgo, cultura, comportamiento organizativo, estructura jerarquica, etc. conllevara a considerar la innovacion como la principal estrategia de la empresa. EnglishInnovation is essential to achieve success and competitiveness in any company and makes it possible for it to respond to changes in the environment while maintaining a competitive position. Success in implementing an innovation strategy in an organization will depend on several factors: the economic cycle, Porter’s five forces, the market, etc. and above all the human resources of the company. When it is intended to include innovation as a business strategy, human resources will be the key to achieving it. The exact mix of leadership, culture, organizational behavior, hierarchical structure, etc. It will lead to consider innovation as the main strategy of the company.

Current wearable form factors often house electronics using an enclosure that is attached to the body. This form factor, while wearable, tends to protrude from the body and therefore can limit wearability. While emerging research in on-skin interfaces from the HCI and wearable communities have generated form factors with lower profiles, they often still require support by conventional electronics and associated form factors for the microprocessor, wireless communication, and battery units. In this work, we introduce SkinWire, a fabrication approach that extends the early work in on-skin interfaces to shift wearable devices from their traditional box-like forms to a fully self-contained on-skin form factor. The Skin Wire approach starts with the placement of electronic components into individual PCB islands, which are then distributed over the body surface. The islands are connected through a novel skin-wiring approach that deposits conformal multi-stranded metallic wires on thin silicon substrates through a sewing-based technique. The process affords on-skin interfaces with the needed wiring in limited surface areas. We exemplify the capacity of this approach by shifting an IMU-based hand gesture system - which traditionally come in bulky glove-based form factors - directly onto the skin. Inspired by the emerging body art trend of body wiring, the Skin Wire approach uses readily accessible materials and affords aesthetic customization. We evaluate fabrication parameters, and conduct a user study to uncover wearability concerns.

How can we design a product or movie that will attract, for example, the interest of Pennsylvania adolescents or liberal newspaper critics? What should be the genre of that movie and who should be in the cast? In this work, we seek to identify how we can design new movies with features tailored to a specific user population. We formulate the movie design as an optimization problem over the inference of user-feature scores and selection of the features that maximize the number of attracted users. Our approach, PNP, is based on a heterogeneous, tripartite graph of users, movies, and features (e.g. actors, directors, genres), where users rate movies and features contribute to movies. We learn the preferences by leveraging user similarities defined through different types of relations, and show that our method outperforms state-of-the-art approaches, including matrix factorization and other heterogeneous graph-based analysis. We evaluate PNP on publicly available real-world data and show that it is highly scalable and effectively provides movie designs oriented towards different groups of users, including men, women, and adolescents.

BackgroundHow physical activity (PA) and sitting time may change after first myocardial infarction (MI) and the association with mortality in postmenopausal women is unknown.Methods and ResultsParticipants included postmenopausal women in the Women's Health Initiative‐Observational Study, aged 50 to 79 years who experienced a clinical MI during the study. This analysis included 856 women who had adequate data on PA exposure and 533 women for sitting time exposures. Sitting time was self‐reported at baseline, year 3, and year 6. Self‐reported PA was reported at baseline through year 8. Change in PA and sitting time were calculated as the difference between the cumulative average immediately following MI and the cumulative average immediately preceding MI. The 4 categories of change were: maintained low, decreased, increased, and maintained high. The cut points were ≥7.5 metabolic equivalent of task hours/week versus <7.5 metabolic equivalent of task hours/week for PA and ≥8 h/day versus <8 h/day for sitting time. Cox proportional hazard models estimated hazard ratios and 95% CIs for all‐cause, coronary heart disease, and cardiovascular disease mortality. Compared with women who maintained low PA (referent), the risk of all‐cause mortality was: 0.54 (0.34–0.86) for increased PA and 0.52 (0.36–0.73) for maintained high PA. Women who had pre‐MI levels of sitting time <8 h/day, every 1 h/day increase in sitting time was associated with a 9% increased risk (hazard ratio=1.09, 95% CI: 1.01, 1.19) of all‐cause mortality.ConclusionsMeeting the recommended PA guidelines pre‐ and post‐MI may have a protective role against mortality in postmenopausal women.

Neural node embedding has been recently developed as a powerful representation for supervised tasks with graph data. We leverage this recent advance and propose a novel approach for unsupervised community discovery in graphs. Through extensive experimental studies on simulated and real-world data, we demonstrate consistent improvement of the proposed approach over the current state-of-the-arts. Specifically, our approach empirically attains the information theoretic limits under the benchmark Stochastic Block Models and exhibits better stability and accuracy over the best known algorithms in the community recovery limits.

Tracking multiple people in an indoor environment enables various smart building applications such as HVAC energy saving, patient/child monitoring, etc. Researchers have explored various sensing methods including vision, motion, and RF, which either require specific installation requirements or high deployment density. We introduce a passive sparse sensing method based on ambient structural vibration induced by foot strikes. Our system tracks multiple people based on the premise that human foot strikes have spatio-temporal variation, and hence do not fully overlap. The system achieved less than 0.4m accuracy in both one and two persons stepping conditions.

The polarization of the BSC(γ 1 ) with a BSC(γ 2 ) is characterized explicitly for γ 1 , γ 2 ∈ [0, 1/2]. The polarization yields a channel W− which is a BSC(λ), and a channel W+ which is composed of a BSC(ξ) with probability 1 − λ and a BSC(ϕ) with probability λ. The parameters λ, ξ and ϕ are functions of γ 1 and γ 2 . For a general binary-input, output-symmetric, discrete, memoryless (BMS) channel W, a simple method is identified for constructing polar codes based on the fact that each polarized channel is defined by a mutual information profile, and is comprised of sub-channel components, similar to results by [Pedarsani et al., 2011; Tal and Vardy, 2013]. Algebraic polar transforms may be applied recursively to each sub-channel component. As an example, polar codes are constructed for a hybrid BMS channel with an erasure probability ϵ, a bit-flip probability γ, and capacity C(ϵ, γ) = (1 − ϵ)(1 − h b (γ)) where h b (x) ≜ −x log 2 (x)−(1−x) log 2 (1−x). Based on the structure of polarization via explicit parameters, relations regarding the information density and channel dispersion V (W) are analyzed for polarized channels, including the super-martingale property of V (W). The analysis depends on second-order terms involving the function ψ(x) ≜ x log 2 2 x + (1 − x) log 2 2(1 − x).

Matrix completion (MC) with additional information has found wide applicability in several machine learning applications. Among algorithms for solving such problems, Inductive Matrix Completion(IMC) has drawn a considerable amount of attention, not only for its well established theoretical guarantees but also for its superior performance in various real-world applications. However, IMC based methods usually place very strong constraints on the quality of the features(side information) to ensure accurate recovery, which might not be met in practice. In this paper, we propose Goal-directed Inductive Matrix Completion(GIMC) to learn a nonlinear mapping of the features so that they satisfy the required properties. A key distinction between GIMC and IMC is that the feature mapping is learnt in a supervised manner, deviating from the traditional approach of unsupervised feature learning followed by model training. We establish the superiority of our method on several popular machine learning applications including multi-label learning, multi-class classification, and semi-supervised clustering.