Review Article
Totalitarian Art and the Art of Resistance in the Ukraine of the 20th Century According to the Research of Oleksiy Rohotchenko
Karpov Viktor Vasilyevich*
Issue:
Volume 2, Issue 2, April 2026
Pages:
99-104
Received:
30 October 2025
Accepted:
12 November 2025
Published:
20 January 2026
DOI:
10.11648/j.scif.20260202.11
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Abstract: The monograph of art historian Oleksiy Rogotchenko “Sixty Totalitarian Years: Fine Art of Ukraine 1920-1980” emphasizes the important and topical issues of modern art criticism, the issue of the interaction of art and power in the context of the deformation of the artistic space, the issue of the role of the artist and fine art in social communication under the conditions of the proletarian dictatorship. The extremely factual monograph acts as a kind of encyclopedia of “fine” art in the specified period, and beyond this, it encourages reflection and continuation of the discourse about the era of the “Great Fear”. The proposed review of the monograph actualizes the problem of the national in art. It is established that national art, as well as national identity in the totalitarian years, could not be anything other than a reflection and continuation of the policy of the dictatorship of the proletariat. The work of Oleksiy Rogotchenko is important in the context of understanding the anthropology of art of the totalitarian regime and the transformation of the role of the artist from the concept of free creativity to the proletarian artist, a servant of the ideological postulates of the proletarian dictatorship. It is noted that the development of fine art in Ukraine in the sixty totalitarian years took place on the basis of the ideology of proletarian culture in the expression of the method of socialist realism. Oleksiy Rogotchenko explores the phenomenon of resistance of the Ukrainian artistic society to the official doctrine, which is designated in the Ukrainian art historical discourse by the term nonconformism. It is proved that the method of socialist realism in fine art at the end of the dictates of the Soviet government had a tendency towards individuality and free creativity of the artist.
Abstract: The monograph of art historian Oleksiy Rogotchenko “Sixty Totalitarian Years: Fine Art of Ukraine 1920-1980” emphasizes the important and topical issues of modern art criticism, the issue of the interaction of art and power in the context of the deformation of the artistic space, the issue of the role of the artist and fine art in social communicat...
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Research Article
Temporal Analysis of CMIP6 Historical and Projection Emission Scenarios
Gezahegn Mergia Tullu*,
Dagmawit Aman Disaso
Issue:
Volume 2, Issue 2, April 2026
Pages:
105-117
Received:
2 December 2025
Accepted:
22 December 2025
Published:
20 January 2026
DOI:
10.11648/j.scif.20260202.12
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Abstract: Globally, impacts of climate change observed across the sources of water, agricultural planning, and socio-economic factors. Objectives of the study are to analyze historical climate data, focusing on rainfall and temperature trends over the period 1981–2014 and to project future climate scenarios under SSP2-4.5 and SSP5-8.5 for the periods 2015–2040 (near term), 2041–2070 (mid-term), and 2071–2100 (end term), assessing changes in seasonal and annual rainfall and temperature. This study investigates historical and projected climate trends in Tiyo Woreda, Arsi Zone, Ethiopia, using data sources Copernicus and ECMWF and CMIP6 climate models under SSP2-4.5 and SSP5-8.5 scenarios. Ensembles global climate models selected from the five Coupled Model Intercomparison Project (CMIP6) are considered under SSP2-4.5 and SSP5-8.5 socio-economic pathways. The research conducted using multiple software tools, such as Excel for data entry and manipulation, Python for data processing, visualization, Heatmaps and plotting, and ArcGIS and GeoCLIM for location of study area and spatial analysis. The result demonstrated historical climate rainfall is highest during the Kiremt, moderate during Belg, and lowest during Bega. Projections both SSP2-4.5 and SSP5-8.5 scenarios suggest that rainfall will generally increase in the mid- and long term, though slight reductions are observed in the near term compared to the historical baseline. Seasonal trends of Bega and Belg rainfall show small near-term declines and slight increase respectively but recover and increase in later periods. Kiremt rainfall exhibits modest but consistent increases, with higher values under SSP5-8.5. Annual rainfall follows a similar trajectory, with gradual increases across the projection horizon. Scenario comparison across SSP5-8.5 consistently projects greater increases in rainfall than SSP2-4.5, particularly in the mid- to long-term. In general historical analysis show mixed rainfall trends with increases in Kiremt and decreases in Bega and Belg, while minimum and maximum temperatures exhibit a warming trend across all seasons. CMIP6 projections indicate an overall increase in seasonal rainfall and temperature, with more pronounced warming under SSP5-8.5. Projections SSP2-4.5 and SSP5-8.5 scenarios of maximum temperature show an increment across the periods of near-, mid- and end-term with the magnitude of 0.7°C, 1.6°C, 2.1°C and 0.8°C, 1.9°C, 3.6°C respectively. These results highlight the need for adaptive strategies in agricultural planning and water resource management to mitigate the impacts of climate change in the Tiyo Woreda.
Abstract: Globally, impacts of climate change observed across the sources of water, agricultural planning, and socio-economic factors. Objectives of the study are to analyze historical climate data, focusing on rainfall and temperature trends over the period 1981–2014 and to project future climate scenarios under SSP2-4.5 and SSP5-8.5 for the periods 2015–20...
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Research Article
Learning State Prediction and Learning Path Generation Using Hidden Markov Models
Song-Hwan Kwon*,
Jong-Nam Rim,
Yun-Ho Ko,
Yun-Sok Ham,
Ha-Gyong Kim
Issue:
Volume 2, Issue 2, April 2026
Pages:
118-134
Received:
21 September 2025
Accepted:
23 October 2025
Published:
20 January 2026
DOI:
10.11648/j.scif.20260202.13
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Abstract: The main mission of the intelligent tutoring system is to estimate and predict the students’ learning status accurately and to generate a learning path that is inherent to the students. There are many learning state estimation and prediction methods, and there are also many methods to generate learning paths using the results. We propose a method to predict the learning state of a student and generate a learning path using the Hidden Markov Model, a probabilistic reasoning over time. We propose and illustrate in detail how to formalize the Hidden Markov Model using an extended knowledge graph for learning state prediction, how to collect the evidence variable values of the Hidden Markov Model in intelligent tutoring systems, how to predict the learning state using smoothing algorithms, and how to generate the stochastic learning path. The experiment was conducted to compare students using an intelligent tutoring system with those who did not. In addition, a comparison experiment of a method using Hidden Markov model with a multi-dimensional linear prediction model such as PFM and AFM was also carried out. The results showed that the average performance of students using the intelligent tutoring system was much higher than that of students without the intelligent tutoring system. In addition, the experimental results showed that the average performance of students using Hidden Markov models was higher than that of students using other models.
Abstract: The main mission of the intelligent tutoring system is to estimate and predict the students’ learning status accurately and to generate a learning path that is inherent to the students. There are many learning state estimation and prediction methods, and there are also many methods to generate learning paths using the results. We propose a method t...
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