National University of Mongolia Scientific Journals
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Engineering geomorphological study to assess the potential for artificial lake construction in the agricultural areas of the Selenge River Basin, northern Mongolia: Сэлэнгэ мөрний сав газрын хөдөө аж ахуйн бүс нутагт хиймэл нуур байгуулах боломжийг тодорхойлох инженер геоморфологийн судалгаа
No full textUnder the intensifying impacts of global climate change and the increasing frequency of droughts and harsh winters, the agricultural regions of the Selenge River Basin in Mongolia are facing persistent water scarcity. This study aims to identify and evaluate geomorphologically suitable sites for artificial lake construction in order to strengthen water supply, ensure environmental balance, and meet domestic water needs within the framework of Mongolia’s national initiative “333 Lakes, One District–One Lake.” A suitability assessment was conducted through spatial analysis based on a 30 m resolution Digital Elevation Model (DEM), employing the Analytical Hierarchy Process (AHP) method. From an engineering geomorphological perspective, the evaluation considered not only topography, hydrology, precipitation, and soil conditions but also additional land-use factors. The results reveal that 10.12% of the study area is classified as highly suitable, 69.45% as suitable, and 13.34% as moderately suitable, while the remaining 7.09% is either unsuitable or restricted by land-use constraints. Based on the comprehensive assessment, nine representative potential sites for artificial lakes were selected. For each site, potential irrigable areas, domestic water supply capacity, and livestock watering availability were estimated, and a general economic evaluation of potential water sources and dam construction costs was conducted. This study emphasizes that incorporating engineering geomorphological analysis and Geographic Information System (GIS)-based approaches provides essential scientific support for site selection of artificial lakes, thereby contributing to sustainable agricultural and pastoral development in the Selenge River Basin
Олон улсын харилцаан дахь цөмийн зэвсгийн хүчин зүйл
No full textAlthough most people think nuclear weapons were created after World War II, scientist of Germany and Japan already knew about fusion matter and something with extraordinary power. Germany and Japan, along with other powers, conducted secret projects to create an unknown weapon of mass destruction. The goal of Germany and Japan was to defeat their enemy with one weapon. Still in 1945, when the U.S. conducted its first nuclear test in Alamogordo, New Mexico, world did not know about a weapon with brutal force. Only after the U.S. dropped nuclear bombs on Japan’s cities of Hiroshima and Nagasaki was the world stunned by the power of nuclear weapons. However, at that time, powers were not scared of nuclear weapons; some of them saw it as a guarantor of their security, and others saw it as an opportunity to strengthen their power and position on the world stage.This paper covers topics such as the history of creation of the nuclear bomb, its role in international relations and international security, world powers’rivalry to gain nuclear technology and the arms race, and how nuclear weapons have shaped world politics
APPLICATION OF MULTI-OBJECTIVE OPTIMIZATION IN AN OLIGOPOLY MARKET
No full textModeling competitive behavior in oligopolistic markets through multiobjective optimization is closely linked to decision-making processes in economic systems. This study proposes an approach for identifying Pareto-optimal solutions using empirical export data of coking coal from Mongolia, Russia, and Australia. The Pareto-efficient equilibrium was obtained by transforming the multi-objective problem into a global optimization problem using the weighted sum scalarization technique based on Theorem 2 and solving it in MATLAB. Two experimental models were constructed using different price–cost function structures. The numerical results indicate that the optimal export quantities of the three countries are highly dependent on the functional form of the price–cost relationship. When the price function exhibits quadratic growth, equilibrium supply levels shift toward higher values. These findings demonstrate the significant influence of price elasticity and cost structure on strategic decision-making in resource-based oligopoly markets. The results may provide useful insights for developing optimal export strategies in markets with oligopolistic characteristics
ANALYZING THE ECONOMIC ENVIRONMENT USING MACHINE LEARNING
No full textStudying and evaluating a country’s trade and business environment ensures economic stability and enhances organizational competitiveness. Business environment assessments serve as a foundation for identifying entrepreneurs’ challenges and determining future development directions. This research aimed to apply machine learning techniques to classify the economic environment data that received the lowest evaluation in the 2020 joint study conducted by the Mongolian National Chamber of Commerce and Industry and the Business School. The study employed machine learning methods, including K-Means clustering, Principal Component Analysis (PCA), and Decision Tree algorithms
Resolving γ-ray overlap of 117mSn, 117Sb, and 123mTe for cross-section measurement
No full textThe production cross-sections of 117mSn, 117Sb, and 123mTe in α-particle induced reactions on ⁿᵃᵗSn were measured up to 50 MeV using the stacked-foil activation technique. A significant analytical challenge arose from the overlapped peak near the 159 keV γ-rays from these nuclides. This overlapped peak was resolved using a time-differential analysis that leveraged the different half-lives (117Sb: 2.8 h, 117mSn: 13.6 d, 123mTe: 119.2 d). Through γ-ray spectrometry at multiple cooling times (0.6 h to 144.9 d), a sequential subtraction method based on the activation formula was used to distinguish the overlapped peak. The resulting independent cross-sections of these 117mSn, 117Sb, and 123mTe isotopes, are in good agreement with literature data, thereby validating the method for resolving complex γ-ray interferences
Contribution of Social Media to Political Polarization Among University Students
No full textThis study investigates the contribution of social media to political polarization among university students from the United States and Mongolia. Data was collected using an online survey distributed to currently active students at the University of Southern Indiana (USI) and the National University of Mongolia (NUM).The findings of this study reveal that social media platforms such as Facebook, Instagram, YouTube, TikTok, and X (formerly known as Twitter) are social media platforms used among students the most. Students spend approximately 2-5 hours per day on social media on average. While respondents perceive social media to be an efficient tool for political engagement such as getting news, the data report suggests selective exposure behaviors in students, such as muting, blocking or unfollowing individuals who had differing views from them, which contribute to the creation of echo chambers.The study highlights the role of social media in strengthening ideological divergence while encouraging civic involvement. These findings emphasize the nuanced relationship between social media and political polarization
Temporal and spatial variation of gross primary productivity and its response to extreme climate in Mongolia: Монгол орны ургамлын нийт анхдагч бүтээгдэхүүний орон зай, цаг хугацааны өөрчлөлт, эрс тэс уур амьсгалын үзүүлэх нөлөө
No full textMongolia has extremely fragile ecosystems and rich vegetation resources in arid and semi-arid zones. It is highly affected by extreme climatic events and is important in the global carbon cycle. In global warming, it is important to study its vegetation changes for ecological security. In this paper, based on the gross primary productivity (GPP) data with daily maximum temperature, daily minimum temperature and daily precipitation data of Mongolia from 2000 to 2023, the characteristics of spatial and temporal changes in GPP and its response to climate extremes were analyzed by using Sen Slope + Mann-Kendall trend analysis, MK mutation test, Pearson's correlation analysis method, and structural equation modeling (SEM). The main findings of the study are as follows: (1) GPP shows an overall increasing trend, especially in the northern Mongolia, with 61% of the study area experiencing significant growth. (2) Extreme temperature indices (SU, TNx, TNn) and precipitation index R20 are increasing at most stations, while R95P and SDII are declining. (3) Extreme precipitation indices generally support GPP, though they suppress it in Western Mongolia. R20 is identified as the primary driver of vegetation growth. (4) TNx and SU inhibit GPP, except in North Mongolia, where warmer summers enhance productivity. R20 and R95P have opposing effects on GPP, highlighting the dual role of precipitation type and intensity
A NEW PARADIGM OF BIG DATA–BASED RISK ASSESSMENT: EVIDENCE FROM A METAL MINING COMPANY
No full textIn recent years, mining companies have been increasingly exposed to a wide range of environmental, social, economic, and technological risks, which have adversely affected operational sustainability. Conventional risk assessment approaches have limited capacity to incorporate real-time data and to adapt to dynamic operating conditions. In contrast, artificial intelligence and machine learning methods offer new opportunities to address these shortcomings. This study applies GRU, BiLSTM, XGBoost, and Random Forest models to three primary data sources: a copper price series covering 1960 to 2024, more than 700,000 hours of industrial process data, and over 188,000 recorded occupational accident cases. Overall, the findings demonstrate that AI and ML-based approaches can transform mining risk management from a reactive framework into a proactive, real-time, and data-driven integrated system
A STUDY ON FACTORS INFLUENCING THE DECISION MAKING BEHAVIOR IN PURCHASING VEHICLE INSURANCE SERVICES
No full textDespite the experienced significant growth of the insurance sector in Mongolia, particularly in motor vehicle insurance, there remains a paucity of comprehensive research examining the key factors influencing consumers’ (drivers and vehicle owners) purchase intentions in selecting and purchasing insurance services, as well as the interrelationships among these factors. This study aims to identify the determinants affecting consumers’ decision-making regarding motor vehicle insurance purchases. A total of 340 respondents participated in the study, and six hypotheses were tested using SPSS 27.0. The results indicate that an insurance company’s reputation, consumer trust, and advertising exert a positive influence on consumers’ purchase intentions. Conversely, the hypothesized positive effects of compensation processing time, ease of obtaining insurance, and perceived insurance benefits on purchase intention were not supported. These findings provide valuable insights for insurers seeking to enhance consumer engagement and inform strategic marketing decisions in the Mongolian insurance market
Assessment of Agricultural Suitability Using Surface Morphometric Indicators: A Case Study of the Western Soums of Selenge Province, Northern Mongolia: Гадаргын морфометрийн үзүүлэлтэд суурилсан газар тариалангийн тохиромжтой байдлын үнэлгээ: Сэлэнгэ аймгийн баруун сумдын жишээн дээр
No full textThis study identifies and characterizes territories suitable for agricultural production in the western soums of Selenge Province, Mongolia. The western soums cover 19,900 km², representing 44.8% of the province’s total area. The study area lies within the Selenge River basin, which, compared to other river basins in Mongolia, is distinguished by fertile soils, favorable thermal and moisture conditions, abundant water resources, and relatively flat terrain dominated by floodplains—making it a particularly suitable region for agricultural development.According to 2024 statistics, the western soums contain 67% of the province’s agricultural land and 68% of its arable land, with 15.37% of the agricultural land currently under crop cultivation. To assess land suitability, surface morphometric indicators were derived from the HydroSHEDS (Hydrological Data and Maps Based on Shuttle Elevation Derivatives at Multiple Scales) 90 m resolution digital elevation model. Three key factors—elevation, slope, and aspect—were extracted and classified using a reclassification method. To improve accuracy, pairwise interactions among these factors (elevation–aspect, elevation–slope, and aspect–slope) were evaluated using combinational matrices. This approach provided a more realistic and multidimensional representation of morphological conditions than single-factor analyses. Land suitability was quantified on a five-point scale, ranging from highly suitable to highly unsuitable. The results indicate that areas classified as highly suitable and suitable account for 45.72% of the total, moderately suitable areas comprise 19.83%, while unsuitable and highly unsuitable areas make up 38.16%. Considering the spatially uneven distribution of croplands in Mongolia, regionally differentiated evaluations that account for land surface characteristics are essential to support effective agricultural land-use planning. In the future, this methodology can be applied to assess agricultural lands in other regions of Mongolia, with adjustments made for their specific surface characteristics