ADMINISTRATIVE-TERRITORIAL DIVISION IN THE RSFSR (1920s–1930s)

The article discusses the process of changes in the administrative-territorial division of the RSFSR in the 20s–30s of the XX century. The article distinguishes several stages. Relying on historiography and sources, the author tries to analyze and summarize the historical experience in reorganization of the RSFSR administrative-territorial system from the “spontaneous” emergence of new administrative-territorial units against the background of the existing old-regime administrative-territorial units to the first consolidation reform, when governorates, volosts, uyezds were finally liquidated, as well as the second reform of the Soviet government, the essence of which was fragmentation. The study shows that all the transformations of the young Soviet republic in the studied area took place in connection with changes in the form of power organization, as well as with a change in the principles of regional policy and the direction of economic development of the country’s territories. At the present stage, opinions on the return to the governorate administration began to appear more and more often in the research literature, which became the subject of a detailed analysis by the author of this work. The article suggests and substantiates possible directions for improving the administrative-territorial division of the RSFSR after the reform in the 1920s–1930s in order to implement the policy of the Bolsheviks and further territorial development of the country. The main approaches to the formation of the RSFSR administrative-territorial division, identification of local socio-economic systems, determination of the optimal size of administrative-territorial entities are highlighted. The interrelation between the administrative-territorial division and economic zone division in Russia is substantiated.

Hough Transform-Based Angular Features for Learning-Free Handwritten Keyword Spotting

Handwritten keyword spotting (KWS) is of great interest to the document image research community. In this work, we propose a learning-free keyword spotting method following query by example (QBE) setting for handwritten documents. It consists of four key processes: pre-processing, vertical zone division, feature extraction, and feature matching. The pre-processing step deals with the noise found in the word images, and the skewness of the handwritings caused by the varied writing styles of the individuals. Next, the vertical zone division splits the word image into several zones. The number of vertical zones is guided by the number of letters in the query word image. To obtain this information (i.e., number of letters in a query word image) during experimentation, we use the text encoding of the query word image. The user provides the information to the system. The feature extraction process involves the use of the Hough transform. The last step is feature matching, which first compares the features extracted from the word images and then generates a similarity score. The performance of this algorithm has been tested on three publicly available datasets: IAM, QUWI, and ICDAR KWS 2015. It is noticed that the proposed method outperforms state-of-the-art learning-free KWS methods considered here for comparison while evaluated on the present datasets. We also evaluate the performance of the present KWS model using state-of-the-art deep features and it is found that the features used in the present work perform better than the deep features extracted using InceptionV3, VGG19, and DenseNet121 models.

The Effect of Serpent 2 Calculation Parameters on Evaluated Spent Nuclear Fuel Source Term

The estimation of spent nuclear fuel source term (decay heat, reactivity, nuclide inventory etc.) has several sources of uncertainty such as uncertainties in nuclear data, uncertainties in the operation history, choice of calculation parameters etc. In this work the effect of calculation parameters is studied by estimating the source term with the built-in burnup capability of Serpent. The effect of the following parameters is considered: depletion zone division, burnup steps, unresolved resonance probability table sampling, Doppler-Broadening Rejection Correction (DBRC) and energy dependent branching ratios. As a test case a 2D BWR fuel assembly was modelled by first running a burnup calculation followed by a decay calculation. The following source term components were considered when investigating the effect of the studied parameters: total decay heat, photon emission rate and spontaneous fission rate. In general the differences resulting from the use of different parameter variations were small for all three studied source term components. For the decay heat largest absolute relative difference was approximately 0.6 % and for the photon emission rate approximately 1.1 %. For the spontaneous fission rate maximum absolute relative difference of nearly 8 % was observed. For all three components the variation of the depletion zone division resulted in the largest relative differences. Clear differences were also observed for burnup step length and DBRC variations. The use of unresolved resonance probability table sampling and energy dependent branching ratios had an insignificant effect on the studied source term components.

Multi-zone prediction analysis of city-scale travel order demand

Taxi order demand prediction is of tremendous importance for continuous upgrading of an intelligent transportation system to realise city-scale and personalised services. An accurate short-term taxi demand prediction model in both spatial and temporal relations can assist a city pre-allocate its resources and facilitate city-scale taxi operation management in a megacity. To address problems similar to the above, in this study, we proposed a multi-zone order demand prediction model to predict short-term taxi order demand in different zones at city-scale. A two-step methodology was developed, including order zone division and multi-zone order prediction. For the zone division step, the K-means++ spatial clustering algorithm was used, and its parameter k was estimated by the between–within proportion index. For the prediction step, six methods (backpropagation neural network, support vector regression, random forest, average fusion-based method, weighted fusion-based method, and k-nearest neighbour fusion-based method) were used for comparison. To demonstrate the performance, three multi-zone weighted accuracy indictors were proposed to evaluate the order prediction ability at city-scale. These models were implemented and validated on real-world taxi order demand data from a three-month consecutive collection in Shenzhen, China. Experiment on the city-scale taxi demand data demonstrated the superior prediction performance of the multi-zone order demand prediction model with the k-nearest neighbour fusion-based method based on the proposed accuracy indicator.

A Big-Data-Driven Framework for Parking Demand Estimation in Urban Central Districts

Parking planning is a key issue in the process of urban transportation planning. To formulate a high-quality planning scheme, an accurate estimate of the parking demand is critical. Most previous published studies were based primarily on parking survey data, which is both costly and inaccurate. Owing to limited data sources and simplified models, most of the previous research estimates the parking demand without consideration for the relationship between parking demand, land use, and traffic attributes, thereby causing a lack of accuracy. Thus, this study proposes a big-data-driven framework for parking demand estimation. The framework contains two steps. The first step is the parking zone division method, which is based on the statistical information grid and multidensity clustering algorithms. The second step is parking demand estimation, which is extracted by support vector machines posed in the form of a machine learning regression problem. The framework is evaluated using a case in the city center in Cangzhou, China.

Zone Fare System Design in a Rail Transit Line

As a widely existing form of public transit fare structures, zone fare system is traditionally designed in a separate way, which may lead to suboptimal results. This paper aims to concurrently address the zone division and fare calculation issues of the zone fare system design in a rail transit line. It is necessary to consider passengers as well as operators to find an impartial zone fare system. A fair zone fare system is one where the zone fares are as close as possible to the distance-based fares, for the fares of the distance-based fare system are highly correlated with the actual distance of trips. Thus, the fare deviations for the trips between the zone fare system and the distance-based fare system are utilized as the evaluation metric of fairness. To achieve the goal of minimizing fare deviations for all trips, we introduce three indexes: average absolute deviation, average squared deviation, and maximum mileage fare deviation. With the three indexes as the objective functions, we develop a joint optimization algorithm where a novel zone boundary adjustment scheme is proposed as the key technique. Numerical results show that the proposed algorithm can effectively provide a joint optimal scheme and the optimal number of planned zones is 5 for Changsha Metro Line 2. The proposed algorithm can provide guidance for the practical design and adjustment of the zone fare system.

Optimization of Wireless Communication Coverage in Underground Tunnels Based on Zone Division

In order to reduce the path loss of the wireless communication signal in the underground tunnel, a scheme for configuring the antenna polarization of wireless systems based on a zone-division method is proposed. A multimodal method is used to estimate the effect of antenna polarization on the wireless propagation. When the optimal polarization of the antenna leading to low path loss is different in the zones near and far from the transmitting antenna, a dividing point is used to separate the zones. Experiments are conducted in an underground mine. It shows that the results by the multimodal method are consistent with the real data. Compared with the existing coverage schemes, the proposed scheme can obtain better coverage. Meanwhile, zone division has an important influence on the optimized performance of the wireless coverage. The zones divided based on Fresnel zone clearance and system identification are too small or too large, which result in incorrect polarization switching and high path loss.