scholarly journals Short-Term Economic Forecasting by Complex-Valued Autoregressions

2021 ◽  
pp. 35-48
Author(s):  
Sergey G. Svetunkov
Keyword(s):  
Mathematical Modeling ◽  
Complex Variable ◽  
Complex Variables ◽  
Autoregressive Models ◽  
Theoretical Level ◽  
Short Term ◽  
Economic Forecasting ◽  
Complex Valued ◽  
Use Of Models

One of the directions that can expand the instrumental base for modeling the economy is complex-valued economics – ​a section of economic and mathematical modeling devoted to the use of models and methods of the theory of the function of a complex variable in economics. The article discusses the possibility of short-term economic forecasting using autoregressive models of complex variables. A classification of possible modifications of complex-valued autoregressive models is given, and the main properties of each of the classes of these models are shown. One of the varieties of these complex-valued models uses current and past errors of approximation, which means that it can be compared with the widely used model of autoregressive real variables ARIMA(p, d, q). The article makes such a comparison, both on a theoretical level and on a practical example.

scholarly journals Multiplicative automatic sequences

2021 ◽  
Author(s):  
Jakub Konieczny ◽  
Mariusz Lemańczyk ◽  
Clemens Müllner
Keyword(s):  
Complete Classification ◽  
Automatic Sequences ◽  
Complex Valued

AbstractWe obtain a complete classification of complex-valued sequences which are both multiplicative and automatic.

scholarly journals Pressure Algometry Evaluation of Two Occlusal Splint Designs in Bruxism Management-Randomized, Controlled Clinical Trial

2021 ◽  
Vol 10 (11) ◽  
pp. 2342
Author(s):  
Bartosz Dalewski ◽  
Agata Kamińska ◽  
Paweł Kiczmer ◽  
Krzysztof Węgrzyn ◽  
Łukasz Pałka ◽  
...  
Keyword(s):  
Pain Threshold ◽  
Pressure Pain Threshold ◽  
Controlled Clinical Trial ◽  
Randomized Controlled Clinical Trial ◽  
Occlusal Splint ◽  
Short Term ◽  
Randomized Controlled ◽  
Canine Guidance ◽  
Medical University

The aim of this pilot study was to evaluate the short-term effectiveness of two different occlusal devices and their impact on the pressure pain threshold (PPT) values among patients who reported to the Dental Prosthetics Outpatient Clinic of Pomeranian Medical University (Szczecin, Poland) and who were diagnosed with probable bruxism. Two groups were formed (A and B) to which patients were assigned randomly. Each group used a different occlusal splint for bruxism management. The occlusal appliance by Okeson, or the bimaxillary splint, was used overnight by each patient for 30 days of the study. The PPT was measured twice, at the first visit and after 30 days of using each occlusal device, with Wagner Paintest FPX 25 algometer. Bruxism was diagnosed based on data from the patient’s medical history and from the physical examination. Nocturnal Bruxism Criteria according to the International Classification of Sleep Disorders (Third Edition) was used for the patient’s evaluation. Results: similar pain factor (PF) reduction was observed in both the examined groups, regardless of the device used; canine guidance and no guidance were similarly effective in terms of increasing pain resilience.

scholarly journals Time-frequency time-space long short-term memory networks for image classification of histopathological tissue

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tuan D. Pham
Keyword(s):  
Image Analysis ◽  
Short Term Memory ◽  
Disease Diagnosis ◽  
Short Term ◽  
Term Memory ◽  
Time Frequency ◽  
Time Space ◽  
Histopathological Images ◽  
Long Short Term Memory

AbstractImage analysis in histopathology provides insights into the microscopic examination of tissue for disease diagnosis, prognosis, and biomarker discovery. Particularly for cancer research, precise classification of histopathological images is the ultimate objective of the image analysis. Here, the time-frequency time-space long short-term memory network (TF-TS LSTM) developed for classification of time series is applied for classifying histopathological images. The deep learning is empowered by the use of sequential time-frequency and time-space features extracted from the images. Furthermore, unlike conventional classification practice, a strategy for class modeling is designed to leverage the learning power of the TF-TS LSTM. Tests on several datasets of histopathological images of haematoxylin-and-eosin and immunohistochemistry stains demonstrate the strong capability of the artificial intelligence (AI)-based approach for producing very accurate classification results. The proposed approach has the potential to be an AI tool for robust classification of histopathological images.

High Resolution Sequence Stratigraphic Frameworks Research in the XII Group of the Member III of Qing Shankou Formation in the Qian'an Oilfield

2013 ◽  
Vol 339 ◽  
pp. 728-731 ◽  
Author(s):  
Cun Lei Li ◽  
Lei Qin ◽  
Xue Li ◽  
Xi Long Zhang
Keyword(s):  
High Resolution ◽  
Stratigraphic Correlation ◽  
Short Term ◽  
Middle Term ◽  
Sequence Stratigraphic ◽  
Base Level ◽  
Mud Logging ◽  
High Resolution Sequence Stratigraphy ◽  
Symmetric Structures

With the instruction of the high resolution sequence stratigraphy and sedimentology theory, and the comprehensive application of 11 wells core, more than 800 mud logging and log data, high resolution sequence stratigraphic characteristics research in the XII Group of the Member III of Qing Shankou Formation in the Qianan oilfield has been finished. The results show that the study area can be divided into one middle-term base level cycle and five short-term base level cycles. The only sequence structure of middle term cycle is (B type) and the short term cycle mainly consists of B types meanwhile there are small mounts of upward deepening structures (A type) and symmetric structures (C type). Based on the classification of base-level cycles, fine stratigraphic correlation is conducted by using isochronous cycle correlations. In addition, 15 high resolution sequence stratigraphic frameworks are established which unify the study area and provide the solid geological basis for the sandstone distribution, the identification of mainly oil-bearing sand bodies and potential oil reservoirs.

Classification of Technological Development Trends Based on the Analysis of US Patent Time Series. An Empirical Approach

2021 ◽  
pp. 251-278
Author(s):  
Vladimir I. Karnyshev ◽  
◽  
Vladimir I. Avdzeyko ◽  
Evgenia S. Paskal ◽  
◽  
...  
Keyword(s):  
Time Series ◽  
New Technologies ◽  
Practical Interest ◽  
The United States ◽  
Direct Access ◽  
Investment Planning ◽  
Short Term ◽  
Development Trends ◽  
Technical Problems

The forecasting of development trends and the timely revealing of new technical (technological) fields are the key prerequisite for an effective development of modern economy. Only reliable results of technological analysis (forecast) allow identifying new technologies, understanding the evolution of entire industries, carrying out strategic investment planning at the state level, and also planning R&D correctly. The aim of this work is to justify one of the possible approaches to the classification of technical (technological) fields in terms of assessing their relevance, novelty and short-term prospects. This approach is based on patent analysis, in particular, on the study of the time series features of US invention patents (1976-2018) for more than seventy-three thousand main groups (subgroups) of the 17th edition of the International Patent Classification (IPC17). The United States Patent and Trademark Office (USPTO) has been selected as the primary source of information because it is one of the world’s largest and constantly updated patent resources, providing direct access to full-text descriptions. In the authors’ opinion, a feature analysis of the US patent issue dynamics at time intervals (1976-2015, 2009-2018 and 2016-2018) allows dividing the IPC groups (subgroups) into the following three main clusters: “unpromising”, “promising” and “breakthrough”. In terms of the timely revealing of new, previously unknown, technologies or solutions in the technical field, or of the steadily growing technological trends, the “breakthrough” and “promising” subgroups are of the greatest practical interest. The article presents the results of an empirical classification of 71,266 subgroups (with a non-zero number of the issued patents since 1976 to 2018) in eight sections of the IPC17. These data may be useful for developers, researchers and R&D planners in solving complex scientific and technical problems, as well as for making short-term forecast estimates of a specific technical (technological) field development.

THREATS TO NATIONAL SECURITY OF RUSSIA IN THE CONTEXT OF A HYBRID WAR

2021 ◽  
Vol 16 (3) ◽  
pp. 109-130
Author(s):  
A.S. MAKSIMOV ◽  
Keyword(s):  
Synergistic Effect ◽  
National Security ◽  
Negative Impact ◽  
Short Term ◽  
Economic Information ◽  
Hybrid Threats ◽  
Hybrid War ◽  
Political Economic ◽  
Verbal Model

This article is devoted to identifying and characterizing the threat to national security of Russian Federation in the context of a hybrid war. The main aim of the study is to assume that the huge problem for national security of Russia today is the threat of a hybrid nature. This paper proposes the author's classification of hybrid threats, which made it possible to distinguish five functional groups of threats («triads») ‒ in the spiritual and socio-cultural, military-political, economic, information and international legal spheres. The specificity of the «triads» is that each of the three elements of the «triad» is capable of producing the appearance of the second and third elements of the «triad» and maintaining their activity. A variant of ranking «triads» according to the level of their threat intensity is presented, the rates of their intensification in the short term were determined. According to the author's conclusions, the synchronous activity of the «triads» creates a synergistic effect, exerting a complicated negative impact on the state of national security of Russia. The novelty of the research, the results of which are presented in the article, are the classification of hybrid threats and the verbal model of the functioning of the «triads» of threats. The findings of the study can contribute to the development of effective techniques and strategies for countering hybrid threats to national security of Russia.

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