scholarly journals Modeling sensitivity indices of industrial enterprise organizational change

2021 ◽  
Vol 10 (45) ◽  
pp. 230-241
Author(s):  
Victoriia Bilyk ◽  
Olena Kolomytseva ◽  
Olha Myshkovych ◽  
Nataliia Tymoshyk ◽  
Denis Shcherbatykh
Keyword(s):  
Organizational Change ◽  
Theory And Practice ◽  
Organizational Changes ◽  
Short Term ◽  
Industrial Enterprises ◽  
Sensitivity Indices ◽  
Proposed Model ◽  
Development Effectiveness ◽  
Made In

Evaluation of sensitivity of commercial enterprises to organizational changes should be made in terms of short-term planning for which it is important to ensure the financial results, as well as in terms of long-term planning, which is important for non-monetary indicators of development effectiveness. To solve this problem, the paper is designed model sensitivity Descriptive indicators of industrial enterprises to organizational changes, reflecting monetary and non-monetary effects of organizational change. The authors determined that the proposed model allows for the analysis of organizational change with regard to their impact on monetary and non-monetary efficiency. This paper contributes to the theory and practice at the border to ensure a balance between short-term and long-term development of industrial enterprises. Convincingly demonstrated the possibility of using research results in practice.

scholarly journals How do Employees Adapt to Organizational Change? The Role of Meaning-making and Work Engagement

2020 ◽  
Vol 23 ◽  
Author(s):  
Machteld van den Heuvel ◽  
Evangelia Demerouti ◽  
Arnold B. Bakker ◽  
Jørn Hetland ◽  
Wilmar B. Schaufeli
Keyword(s):  
Organizational Change ◽  
Work Engagement ◽  
Meaning Making ◽  
Radical Change ◽  
Conservation Of Resources ◽  
Adaptive Performance ◽  
Role Performance ◽  
Short Term ◽  
Office Design

Abstract This multi-wave, multi-source study focuses on the benefits of work engagement for employee adaptation to organizational change. The change entailed the implementation of a flexible office design in an engineering firm, which caused radical change for employees. Building on conservation of resources (COR) theory and change transition models, we predict that work engagement trajectories during change are crucial for successful adaptation. The hypothesized process was that initial employee meaning-making will facilitate work engagement, which, in turn, predicts supervisor-rated adaptive performance (i.e. adaptive work-role performance and extra-role performance) via attitude-to-change. Attitude-to-change was modeled as reciprocally related to work engagement at different points in time. Weekly questionnaires were completed by 71 employees during the first five weeks of the change (296 observations). Latent growth trajectories using weekly engagement measures showed no overall growth, but did show significant variance around the slope of work engagement. Meaning-making and attitude-to-change at the onset were positively related to initial levels, but not to growth of work engagement. Meaning-making was indirectly related to short-term attitude-to-change via work engagement. Short-term attitude-to-change was predictive of supervisor-rated adaptive performance and long-term attitude-to-change. Finally, work engagement (slope) predicted long-term attitude-to-change and supervisor-rated extra-role performance via short-term attitude-to-change. Taken together, the study contributes to knowledge about micro-level transition processes of employee adaptation and the benefits of work engagement during change.

scholarly journals Visions of Human Futures in Space and SETI

2017 ◽  
Author(s):  
Jason T. Wright ◽  
Michael P. Oman-Reagan
Keyword(s):  
Solar System ◽  
Science Fiction ◽  
Dark Matter Particle ◽  
Short Term ◽  
National Science ◽  
The Galaxy ◽  
Near Future ◽  
Far Future ◽  
Made In

We discuss how visions for the futures of humanity in space and SETI are intertwined, and are shaped by prior work in the fields and by science fiction. This appears in the language used in the fields, and in the sometimes implicit assumptions made in discussions of them. We give examples from articulations of the so-called Fermi Paradox, discussions of the settlement of the Solar System (in the near future) and the Galaxy (in the far future), and METI. We argue that science fiction, especially the campy variety, is a significant contributor to the ‘giggle factor’ that hinders serious discussion and funding for SETI and Solar System settlement projects. We argue that humanity's long-term future in space will be shaped by our short-term visions for who goes there and how. Because of the way they entered the fields, we recommend avoiding the term ‘colony’ and its cognates when discussing the settlement of space, as well as other terms with similar pedigrees. We offer examples of science fiction and other writing that broaden and challenge our visions of human futures in space and SETI. In an appendix, we use an analogy with the well-funded and relatively uncontroversial searches for the dark matter particle to argue that SETI's lack of funding in the national science portfolio is primarily a problem of perception, not inherent merit.Also on arXiv: https://arxiv.org/abs/1708.05318Please cite this version:Wright, Jason T., and Michael P. Oman-Reagan. “Visions of Human Futures in Space and SETI.” International Journal of Astrobiology, 2017, 1–12. doi:10.1017/S1473550417000222.

scholarly journals Progress in Pediatric Kidney Transplantation

2014 ◽  
Vol 7 (1) ◽  
pp. 115-122
Author(s):  
Jodi M. Smith ◽  
Vikas R. Dharnidharka
Keyword(s):  
Kidney Transplantation ◽  
Graft Survival ◽  
Pediatric Population ◽  
Short Term ◽  
Allocation Policy ◽  
Pediatric Kidney Transplantation ◽  
Timely Access ◽  
The Impact ◽  
Made In

Significant progress has been made in pediatric kidney transplantation. Advances in immunosuppression have dramatically decreased rates of acute rejection leading to improved short term graft survival but similar improvements in long term graft survival remain elusive. Changes in allocation policy provide the pediatric population with timely access to transplant but there remains concern about the impact of less HLA matching and a decrease in living donors. This report presents data from North America on these successes and the ongoing challenges that face the pediatric transplant community.

scholarly journals Neural Architecture Search for a Highly Efficient Network with Random Skip Connections

2020 ◽  
Vol 10 (11) ◽  
pp. 3712
Author(s):  
Dongjing Shan ◽  
Xiongwei Zhang ◽  
Wenhua Shi ◽  
Li Li
Keyword(s):  
State Of The Art ◽  
Cell Structure ◽  
Frequency Discrimination ◽  
Search Space ◽  
Short Term ◽  
Cell Parameters ◽  
Neural Architecture ◽  
Proposed Model ◽  
Initialization Scheme

Regarding the sequence learning of neural networks, there exists a problem of how to capture long-term dependencies and alleviate the gradient vanishing phenomenon. To manage this problem, we proposed a neural network with random connections via a scheme of a neural architecture search. First, a dense network was designed and trained to construct a search space, and then another network was generated by random sampling in the space, whose skip connections could transmit information directly over multiple periods and capture long-term dependencies more efficiently. Moreover, we devised a novel cell structure that required less memory and computational power than the structures of long short-term memories (LSTMs), and finally, we performed a special initialization scheme on the cell parameters, which could permit unhindered gradient propagation on the time axis at the beginning of training. In the experiments, we evaluated four sequential tasks: adding, copying, frequency discrimination, and image classification; we also adopted several state-of-the-art methods for comparison. The experimental results demonstrated that our proposed model achieved the best performance.

scholarly journals An LSTM-Based Method with Attention Mechanism for Travel Time Prediction

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 861 ◽  
Author(s):  
Xiangdong Ran ◽  
Zhiguang Shan ◽  
Yufei Fang ◽  
Chuang Lin
Keyword(s):  
Short Term Memory ◽  
Attention Mechanism ◽  
Traffic Prediction ◽  
Travel Time Prediction ◽  
Short Term ◽  
Term Memory ◽  
Proposed Model ◽  
Departure Time ◽  
Long Short Term Memory

Traffic prediction is based on modeling the complex non-linear spatiotemporal traffic dynamics in road network. In recent years, Long Short-Term Memory has been applied to traffic prediction, achieving better performance. The existing Long Short-Term Memory methods for traffic prediction have two drawbacks: they do not use the departure time through the links for traffic prediction, and the way of modeling long-term dependence in time series is not direct in terms of traffic prediction. Attention mechanism is implemented by constructing a neural network according to its task and has recently demonstrated success in a wide range of tasks. In this paper, we propose an Long Short-Term Memory-based method with attention mechanism for travel time prediction. We present the proposed model in a tree structure. The proposed model substitutes a tree structure with attention mechanism for the unfold way of standard Long Short-Term Memory to construct the depth of Long Short-Term Memory and modeling long-term dependence. The attention mechanism is over the output layer of each Long Short-Term Memory unit. The departure time is used as the aspect of the attention mechanism and the attention mechanism integrates departure time into the proposed model. We use AdaGrad method for training the proposed model. Based on the datasets provided by Highways England, the experimental results show that the proposed model can achieve better accuracy than the Long Short-Term Memory and other baseline methods. The case study suggests that the departure time is effectively employed by using attention mechanism.

scholarly journals Long Short-Term Memory with Dynamic Skip Connections

2019 ◽  
Vol 33 ◽  
pp. 6481-6488 ◽  
Author(s):  
Tao Gui ◽  
Qi Zhang ◽  
Lujun Zhao ◽  
Yaosong Lin ◽  
Minlong Peng ◽  
...  
Keyword(s):  
Language Processing ◽  
Short Term Memory ◽  
Training Data ◽  
Sequential Data ◽  
Short Term ◽  
Term Memory ◽  
Transition Functions ◽  
Proposed Model ◽  
Long Short Term Memory

In recent years, long short-term memory (LSTM) has been successfully used to model sequential data of variable length. However, LSTM can still experience difficulty in capturing long-term dependencies. In this work, we tried to alleviate this problem by introducing a dynamic skip connection, which can learn to directly connect two dependent words. Since there is no dependency information in the training data, we propose a novel reinforcement learning-based method to model the dependency relationship and connect dependent words. The proposed model computes the recurrent transition functions based on the skip connections, which provides a dynamic skipping advantage over RNNs that always tackle entire sentences sequentially. Our experimental results on three natural language processing tasks demonstrate that the proposed method can achieve better performance than existing methods. In the number prediction experiment, the proposed model outperformed LSTM with respect to accuracy by nearly 20%.

scholarly journals The Anglican Covenant Proposed by the Lambeth Commission

2005 ◽  
Vol 8 (37) ◽  
pp. 147-161 ◽  
Author(s):  
Norman Doe
Keyword(s):  
Short Term ◽  
Episcopal Church ◽  
Common Concern ◽  
Made In ◽  
The Way

The Lambeth Commission (2004) proposed a number of short-term and long-term solutions to issues raised by recent and highly controversial developments in the Episcopal Church (USA) and the diocese of New Westminster (Canada). From these events have emerged important questions about the nature of communion between, and the autonomy of, each of the forty-four member churches of the Anglican Communion, and the way in which decisions of common concern are made. In order to consolidate this communion, as a long-term project, the Commission proposes the adoption of an Anglican Covenant by all forty-four churches of the Communion. This article describes the terms of the proposed Covenant and identifies their provenance, in order to establish that the proposal is for the most part a restatement of classical Anglicanism. Only in serious cases of disagreement which substantially risk the unity of the Communion is the proposal innovative. The article also describes briefly reactions to and possible implementation of the proposed Covenant.

Is MRI suitable for conclusive work-up of suspicious findings in mammography and ultrasound?

2013 ◽  
Vol 31 (26_suppl) ◽  
pp. 3-3
Author(s):  
Kevin Strobel ◽  
Simone Schrading ◽  
Christiane K. Kuhl
Keyword(s):  
False Positive ◽  
Breast Mri ◽  
Short Term ◽  
Long Term Follow Up ◽  
Mass Lesions ◽  
Work Up ◽  
Suspicious Lesions ◽  
Made In

3 Background: The current ACR practice guidelines discourage use of MRI for work-up of suspicious findings in mammography (Mx) and ultrasound (US). We investigated whether additional breast MRI assessment of suspicious Mx and U.S. findings could improve PPV and thus possibly help reduce the number of biopsies for false positive findings in Mx or U.S. Methods: Between 06/2010 and 04/2012, a total 2,754 patients underwent DCE breast MRI. Of these, 277 underwent MRI for further work-up of suspicious findings made in Mx (n=173, 57 patients with mass lesions, 33 with asymmetries, 12 with architectural distortions, and 71 with suspicious calcifications) or U.S. (n=104, 74 with masses, 30 with miscellaneous U.S. findings such as suspected intraductal pathology, focal acoustic shadowing or architectural distortions) . All lesions categorized as MR-BIRADS 4 and 5 underwent biopsy, lesions categorized as MR-BIRADS 1 or 2 did not proceed to biopsy, except for selected women with mammographic calcifications suggestive of DCIS. Lesions categorized as MR-BIRADS 3 underwent additional short term follow-up by MRI, US and/or Mx. All women who did not undergo biopsy (MR-BIRADS 1-3) underwent long term follow-up for so far 12-24 months. Results: For suspicious lesions in mammography, MRI increased PPV from 19.3% (11/57) to 92.3% (12/13) for masses, from 3% (1/33) to 33.3% (1/3) for asymmetries, from 8.3% (1/12) to 25% (1/4) for architectural distortions and from 21.1% (15/71) to 62.5% (15/24) for calcifications. For suspicious lesions in ultrasound, MRI increased PPV from 13.5% (10/74) to 71.4% (10/14) for masses and from 3.3% (1/30) to 50% (1/2) for non-mass U.S. findings. In 4/277 patients, MRI showed additional suspicious findings, requiring MR-guided biopsy, one of which was histologically proven malignant. So far, none of the patients who, because of an MR-BIRADS 1-3, did not undergo biopsy has been diagnosed with invasive cancer or DCIS or with progressive conventional imaging findings necessitating secondary biopsy. Conclusions: MRI improves PPV for both suspicious Mx and U.S. findings, especially mass lesions. In experienced hands, careful use of MRI can help avoid biopsies for false positive diagnoses made in Mx and U.S.

scholarly journals Grapevine Cultivars, Trellis Systems, and Mechanization of the California Raisin Industry

2014 ◽  
Vol 24 (3) ◽  
pp. 285-289 ◽  
Author(s):  
Matthew W. Fidelibus
Keyword(s):  
Production Systems ◽  
The United States ◽  
Medium Term ◽  
Thompson Seedless ◽  
Short Term ◽  
Breeding Programs ◽  
Early Ripening ◽  
Ct System ◽  
Made In

Growers in California’s San Joaquin Valley produced >25% of the world’s raisins in 2012, with a farm-gate value of >$590 million, making the United States the leading global producer of raisins. California’s traditional raisin-making method is a laborious process in which clusters of grapes (Vitis vinifera) are harvested by hand onto paper trays, which are left in the vineyard to dry. The drying fruit may need to be turned or rolled, tasks requiring manual labor, and the trays of dried raisins are also picked up by hand. Most California raisins continue to be made in this way, but in recent years, the declining availability and increasing cost of labor has prompted many growers to implement one of two mechanized production systems, “continuous tray” (CT) or “dry-on-vine” (DOV). In CT systems, machines are used to pick the berries, lay them onto a tray, and pick up the dried raisins. The CT system could be considered a short-term strategy: it is compatible with existing conventional ‘Thompson Seedless’ raisin vineyards and has been widely adopted. The DOV system could be considered a medium-term strategy: it is best suited for vineyards specifically designed for DOV, with early ripening grapevine cultivars on expansive trellis systems, which ensures timely drying, and capitalizes on the fact that sunlit row middles are not needed for fruit drying. Grapevine breeding programs are currently working toward the development of raisin grape cultivars with fruitful basal nodes, with fruit that dry naturally upon ripening. This is a long-term strategy to further reduce labor needs by enabling mechanical pruning in winter and eliminating the need for cane severance in the summer.

scholarly journals Where to Go Next: Modeling Long- and Short-Term User Preferences for Point-of-Interest Recommendation

2020 ◽  
Vol 34 (01) ◽  
pp. 214-221 ◽  
Author(s):  
Ke Sun ◽  
Tieyun Qian ◽  
Tong Chen ◽  
Yile Liang ◽  
Quoc Viet Hung Nguyen ◽  
...  
Keyword(s):  
State Of The Art ◽  
User Preferences ◽  
Short Term ◽  
Preference Modeling ◽  
Point Of Interest ◽  
Proposed Model ◽  
Poi Recommendation ◽  
Novel Method ◽  
Real World Datasets

Point-of-Interest (POI) recommendation has been a trending research topic as it generates personalized suggestions on facilities for users from a large number of candidate venues. Since users' check-in records can be viewed as a long sequence, methods based on recurrent neural networks (RNNs) have recently shown promising applicability for this task. However, existing RNN-based methods either neglect users' long-term preferences or overlook the geographical relations among recently visited POIs when modeling users' short-term preferences, thus making the recommendation results unreliable. To address the above limitations, we propose a novel method named Long- and Short-Term Preference Modeling (LSTPM) for next-POI recommendation. In particular, the proposed model consists of a nonlocal network for long-term preference modeling and a geo-dilated RNN for short-term preference learning. Extensive experiments on two real-world datasets demonstrate that our model yields significant improvements over the state-of-the-art methods.

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