bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deployment of Software-Controlled Distributed Laboratory Complex for a Higher Educational Institution
Authors: Kodolov S D , Klimova A S , Yu Filimonov A , Aksyonova E K 
Published: December 2021

Abstract
The intensive development of information systems and communication infrastructures has led to the emergence of new approaches and new tools for their management. Cloud services, virtualization technologies and software-based management tools are actively used today for building modern information systems which provides additional opportunities for managing components of these systems and for expanding such systems abilities. The use of such approaches and tools can provide a solution to the complex of problems faced by education institutions today, presenting new methods of distance learning and new forms of practical training. The balanced use of virtualization technologies and software-based control tools allows building distributed laboratory complexes of a new generation which will provide new possibilities for using the equipment that is available in educational institutions. The use of such complexes in the educational process allows not only to instill in students the skills of managing the confgura-tions of communication infrastructures that are especially relevant today, but also to organize, in addition to traditional laboratory work, new forms of contactless practical classes. When conducting such classes, students get the opportunity to fully-functional remote access to the virtual and physical components of the complex, which is especially important for organizing the educational process in modern conditions associated with the COVID-19 pandemic.The article discusses modern approaches to the construction of software-controlled communication infrastructures, tools for software-based management of their components and also, an example of the implementation of these approaches and such tools usage in the construction of a distributed laboratory complex for a higher educational institution. The main advantages of the approach based on the use of hypervisors and emulators are presented, the experience of its deployment in the modernization of the laboratory complex for a IRIT-RTF UrFU is considered.
Text-based Recommendation Systems for Software Developers: A Systematic Literature Review
Authors: Gorb Anna 
Published: December 2021

Abstract
Purpose: The aim of this SLR is to look at recommendation systems which receive textual information as an input. By analysing them it is possible to understand how the textual information is preprocessed and which algorithms are then used to generate recommendations. Methods: With the Search Query I frst identifed 487 papers, from which 65 were removed as duplicates. After the IC and EC application, 28 articles remained as relevant. Results: From these articles’ analysis, it was found that the most commonly used pre-processing techniques are tokenization, TF-IDF, and stopwords removal. I also determined that all algorithms for suggestions generation in such systems can be divided into 4 categories: classifcation, ranking, clustering, and heuristic-based algorithms. In the last step I found that the most frequent output of such systems are API, code, and workers suggestions. Conclusion: With this work, I looked at which pre-processing techniques are used in the text-based recommender systems for software developers and which are the most common. I have also looked at the classifcation of algorithms for such recommendation systems. Finally, I considered what kind of objects are recommended by these text-based recommendation systems.
Data-Driven Approaches to User Interface Design: A Case Study
Authors: Pimenov Denis , Solovyov Alexander , Askarbekuly Nursultan , Mazzara Manuel 
Published: December 2021

Abstract
The most common reason for software product failure is misunderstanding user needs. Analysing and validating user needs before developing a product can allow to prevent such failures. This paper investigates several data-driven techniques for user research and product design through prototyping, customer validation, and usability testing. The authors implemented a case study software product using the proposed techniques, and analyses how the application of UX/UI research techniques affected the development process. The case study results indicate that preliminary UX/UI research before the development reduces the cost of product changes. Moreover, the paper proposes a set of metrics for testing the effectiveness of UX/UI design.
Development of a text analysis agent for a logistics company's Q&A system
Authors: Aksyonov K. A. , Ziomkovskaya P. E. , Danwitch Dougandaga , Aksyonova O. P. , Aksyonova E. K. 
Published: December 2021

Abstract
The "Twin" system is an omnichannel communication platform for building voice and chatbots, capable, in particular, of receiving data in one language and transmitting in another. "Twin" can record voice and text, display detailed statistics and analytics for each call or dialog. In this article, using the Twin system, a chatbot was created for the field of cargo transportation, it describes its advantages and disadvantages and the principle of creating of such chatbots.
Spectral efficiency analysis of two-user Downlink PD-NOMA with LTE modulation and coding schemes
Authors: Kryukov Ya. V. , Pokamestov D. A. , Abenov R. R. , Mukhamadiev S. M. , Kanatbekuli I. 
Published: December 2021

Abstract
Non-orthogonal multiple access (NOMA) is a promising user multiplexing technique for future wireless networks that allows increasing their spectral efficiency (SE). Power-Domain NOMA (PD-NOMA) is one of the most perspective techniques in the NOMA group. It makes it possible to perform the transmission of information symbols of several users within the same time-frequency resource segment (RS) without a spreading code. Many research works show the high efficiency of PD-NOMA compared to the orthogonal multiple access (OMA). However, these results are obtained analytically using Shannon’s formula and not taking into account the real performance of existing modulation and coding schemes (MCS). The issue is that it is impossible to obtain the achievable practical performance of PD-NOMA systems in this way. We obtain the SE in RS of a PD-NOMA system with Long Term Evolution (LTE) MCS’s and compare it with OMA. As a result, we conclude that PD-NOMA gains the system SE when the multiplexed user’s signal-to-noise ratio (SNR) outreaches the threshold of the highest performing MCS provided for the transmission by a MCS table.
Hardware Phase Shift Hybrid Precoding Designs For Multi-User Massive MIMO Systems
Authors: Ayad H , Bendimerad M Y , Bendimerad F T 
Published: December 2021

Abstract
Hybrid precoding is a challenging design for massive MIMO systems that involves a combination of analog and digital processing, aiming to maximize the spectral efficiency (SE). Most works on hybrid precoding focus on the single phase shifter (SPS) implementation to adapt the phase from RF chains to antennas. In this paper we propose to develop the double phase shifter (DPS) and the fixed phase shifter (FPS) in both single-path and multi-path configuration. Simulation results certify a significant improvement for both proposed implementations with high hardware efficiency (HE) and high spectral efficiency especially in multi-path environment.
Radiation patterns of patch antennas on coated conducting cylinders
Authors: Chechetkin V A , Shabunin S N , Korotkov A N 
Published: December 2021

Abstract
The development of the Internet of Things and communication systems of the fifth generation leads to the need to place many antenna elements in a limited volume. Therefore, wearable electronics antennas are often located directly on the device body. Such surfaces can often be thought of as a conducting cylinder covered with a dielectric material. The task of analysing the radiation patterns of antennas located on such surfaces becomes urgent. This paper shows a method for analysing antenna directivity diagrams using the Green’s functions method of cylindrical layered media. This method allows to obtain in an analytical form the expressions for the analysis of such structures, which makes it possible to reduce the cost of computer time in modelling. The presented results show what kind of distortions are introduced into the radiation pattern of antennas located on a cylinder compared to an antenna located on a flat surface.
Classification Method of Rape Root Swelling Disease Based on Convolution Neural Network
Authors: Gao Yuan , Liu Changhua , Wu Xiaoming 
Published: December 2021

AbstractBoth the seedling stage and the adult plant stage of rape can be infected with root edema, and the damaged roots swell to form tumors of different sizes and shapes. The incidence of rape root swelling at the seedling stage reached 17%, and the average incidence at the adult plant stage was 15%, resulting in a 10.2% reduction in rape production. The average plant height, number of siliques, number of kernels per horn, 1000-seed weight and yield per plant of healthy plants were significantly higher than those of diseased plants. Grading root lesions can help trace the root causes of root lesions. However, the method of grading is often performed manually by professionals at present, which has the problems of low speed and low efficiency. In order to solve this problem, a method for grading rape root swelling based on deep convolutional neural network is proposed in this paper. Firstly, a rape root swelling model based on convolutional neural network and regional candidate network was established, and then implement it on the deep learning Tensorflow framework Model, and finally compare and analyze the results. The rape root swelling model uses the VGG16 network to extract the characteristics of the rape root swelling image. The regional candidate network generates the preliminary position candidate frame of the rape root swelling, and Fast-RCNN realizes the classification and positioning of the candidate frame. The results show that this method can achieve rapid and accurate detection of healthy, first-level tumors, second-level tumors, and third-level tumors of four-level rape root swelling, with an average accuracy rate of 84.12%. The experimental results show that the accuracy rate can reach more than 90%.
Plant root PET: visualization of photosynthate translocation to roots in rice plant
Authors: Miyoshi Y. , Nagao Y. , Yamaguchi M. , Suzui N. , Yin Y.-G. , Kawachi N. , Yoshida E. , Takyu S. , Tashima H. , Yamaya T. , Kuya N. , Teramoto S. , Uga Y. 
Published: December 2021

Abstract
Roots are essential to plants for uptake of water and nutrients. For the improvement of crop production, it is necessary to understand the elucidation of the root development and its function under the ground. Especially, photosynthate translocation from plant leaves to roots is an important physiological function that affects the root elongation, adaptation to the soil environment and nutrients uptake. To evaluate the translocation dynamics to roots, positron emission tomography (PET) and 11C tracer have been used. However, the spatial resolution is degraded at roots that develop around the peripheral area of field of view (FOV) due to parallax errors. In this study, to overcome this problem, we developed a small OpenPET prototype applying four-layer depth-of-interaction detectors. We demonstrated the imaging capability of 11C-photosynthate translocation to rice roots that develop throughout the entire PET field. We also tried to obtain structural information of roots by high-throughput X-ray computerized tomography (CT) system using the same test plant. As a result, we succeeded in visualizing the root structure that developed around the peripheral region of FOV and imaging the accumulation of 11C-photosynthate to the roots in those areas without degrading the spatial resolution. From obtained images, we also succeeded in evaluating the translocation dynamics varied by roots. The combined use of the high-throughput CT system and the OpenPET prototype was demonstrated to be appropriate for structural and functional analysis of roots.
Neutron energy spectrum measurement using CLYC7-based compact neutron emission spectrometer in the Large Helical Device
Authors: Sangaroon S. , Ogawa K. , Isobe M. , Kobayashi M.I. , Fujiwara Y. , Kamio S. , Yamaguchi H. , Seki R. , Nuga H. , Toyama S. , Miwa M. , Matsuyama S. , Takada E. , Murakami S. , Zhong G.Q. , Osakabe M. 
Published: December 2021

Abstract
Tangential compact neutron emission spectrometer (CNES) based on the Cs2LiYCl6:Ce with 7Li-enrichment (CLYC7) scintillator is newly installed in the Large Helical Device (LHD). Measurement of neutron energy spectrum was performed using CNES in tangential neutral beam (NB) heated deuterium plasma discharges. The Doppler shift of neutron energy according to the direction of tangential NB injection has been obtained. When the fast ions moving away from the CNES, lower shifted neutron energy is obtained, whereas the upper shifted neutron energy is obtained when the fast ions moving toward the CNES. The obtained neutron energy is almost consistent with the virgin deuterium-deuterium neutron energy evaluated by the simple two-body kinematic calculation.
Plasma diagnostic systems and methods used on the stellarator TJ-II
Authors: McCarthy K.J. 
Published: December 2021

Abstract
The TJ-II is a heliac-type stellarator device with major radius of 1.5 m and averaged minor radius ⩽0.22 m that has been operated at CIEMAT, Madrid since 1998. Its full magnetic field is created by a system of poloidal, central, toroidal and vertical field coils, thus it possesses a fully 3-dimensional plasma structure and a bean-shaped plasma cross-section. Although this results in a complicated vacuum-vessel layout, it has excellent port access for diagnostics (96 portholes). During its initial operational phase, it was equipped with a limited set of essential diagnostics. Since then, a broad variety and large number of both passive and active diagnostics have been installed. The former include Hα monitors, light spectrometers, an electron cyclotron emission radiometer, X-ray filter monitors, neutral particle analysers, magnetic diagnostics, as well as cameras, among others, while the latter include various laser, atomic and ion beam based diagnostics, microwave probe beams, Langmuir probes plus impurity injection techniques. In this paper, after describing the TJ-II stellarator, its heating and fuelling systems, the diagnostic systems employed are outlined and discussed briefly here. Finally, results obtained with selected systems are highlighted.
Large-scale forest conservation and restoration programs significantly contributed to land surface greening in China
Authors: Zhao Haiwei , Wu Chaoyang , Wang Xiaoyue 
Published: December 2021

Abstract
China has implemented a portfolio of large-scale forest conservation and restoration programs (FCRPs) to advance the sustainable management of forests. However, the contributions of these programs to forest recovery and land surface greening were generally evaluated on a local scale, which hindered the systematic planning of FCRPs. In this study, we analyzed the spatiotemporal patterns of tree cover (TC) change before and after the intensification of FCRPs using the Mann-Kendall test and the Theil–Sen slope estimator. With the improved phenology-based residual trend analysis (P-RESTREND) method, we derived the spatiotemporal patterns of human-induced tree cover (TCH) change on the national scale. Then, we calculated the effectiveness index of FCRPs at the provincial level, based on which the effectiveness levels for the 31 provinces of mainland China were classified. Our study showed that the area of forested lands with a significant greening trend was almost five times larger in the post-intensification phase (1999–2015) than in the pre-intensification phase of FCRPs (1982–1998). More than 29.9% of the forested lands were significantly improved in TC by human activities in the post-intensification phase. Provinces with high effectiveness levels were generally distributed in humid areas, whereas the majority of provinces with low and moderately low effectiveness levels were spread in arid and semi-arid regions. We concluded that the implementation of FCRPs had contributed greatly to the land surface greening in China. Moreover, the effectiveness of FCRPs in forest recovery was heterogeneous at the provincial level and was driven by multiple natural and socioeconomic factors.
On the attribution of the impacts of extreme weather events to anthropogenic climate change
Authors: Perkins-Kirkpatrick S E , Stone D A , Mitchell D M , Rosier S , King A D , Lo Y T E , Pastor-Paz J , Frame D , Wehner M 
Published: December 2021

Abstract
Investigations into the role of anthropogenic climate change in extreme weather events are now starting to extend into analysis of anthropogenic impacts on non-climate (e.g. socio-economic) systems. However, care needs to be taken when making this extension, because methodological choices regarding extreme weather attribution can become crucial when considering the events’ impacts. The fraction of attributable risk (FAR) method, useful in extreme weather attribution research, has a very specific interpretation concerning a class of events, and there is potential to misinterpret results from weather event analyses as being applicable to specific events and their impact outcomes. Using two case studies of meteorological extremes and their impacts, we argue that FAR is not generally appropriate when estimating the magnitude of the anthropogenic signal behind a specific impact. Attribution assessments on impacts should always be carried out in addition to assessment of the associated meteorological event, since it cannot be assumed that the anthropogenic signal behind the weather is equivalent to the signal behind the impact because of lags and nonlinearities in the processes through which the impact system reacts to weather. Whilst there are situations where employing FAR to understand the climate change signal behind a class of impacts is useful (e.g. ‘system breaking’ events), more useful results will generally be produced if attribution questions on specific impacts are reframed to focus on changes in the impact return value and magnitude across large samples of factual and counterfactual climate model and impact simulations. We advocate for constant interdisciplinary collaboration as essential for effective and robust impact attribution assessments.
Forest Fire Mapping using Normalized Burned Ratio and Cloud Computing to Calculate the Losses Incurred in Mount Lawu, Magetan Regency
Authors: Sukojo Bangun Muljo , Arimurti Adinda Sitaresmi Putri 
Published: December 2021

Abstract
Forest and land fires in Indonesia are one of the most common disasters. Over time, Indonesia’s forests have experienced a decline, one of which is the result of forest and land fires. Forest and land fires can occur due to temperatures in the dry season that continue to increase. Utilization of remote sensing technology can be used for mapping forest and fire areas, and can also be used as a reference for the government to carry out reforestation or reforestation processes in fire areas. The use of Multispectral Sensors in Sentinel 2 satellite imagery can be used to produce this research. This research takes a case study on Mount Lawu, Magetan Regency. Mount Lawu is one of the climbing tourist destinations that almost every year experiences forest and land fires. And the use of the Google Earth Engine platform that supports cloud computing to facilitate this research in accessing high data sources to process large geospatial data sets. For processing satellite images using the Normalized Burned Ratio (NBR) vegetation index processing algorithm. This research was conducted in 2018 and 2019. By using the Random Forest method, which is one of the applications of Machine Learning, it will produce several accurate results from the calculation results. The results of the calculation of the area of fire in 2018 were 284.88 hectares with a total loss of Rp 42,732,000.00 and in 2019 it was 146.03 hectares with a total loss of Rp 21,904,500. The results of this study are displayed on GEE Apps so that users can directly access the resulting data.
Tank Modeling and Its Condition Assessment using Terrestrial Laser Scanner
Authors: Gumilar Irwan , Gaol Samuel Van Livtrik Lumban , Munarda Made , Bramanto Brian , Lukmanulhakim Agus 
Published: December 2021

Abstract
Condition assessment of the tank must be carried out since it is related to Health, Safety, and Environment (HSE). Assessment is carried out by referring to the applicable standards. This study aims to create a 3D (Dimension) model and assess the tank using Terrestrial Laser Scanner technology. This includes planning, data acquisition, data processing, and data visualization. The data processing process starts with the registration stage with the cloud-to-cloud method, georeferencing, 3D modeling using point cloud, and tank assessment filtered point cloud data. Assessment includes analysis of volume, verticality/slope (in terms of the difference between upper and lower tank), and roundness calculations. The 3D model of the tank was generated with a registration error of less than 1 cm. The volume of tank I and tank II were calculated to 134.108 m3 and 134.067 m3, respectively. The difference between the upper and lower radius for each tank ranges from 2 to 10 mm. Considering the results and recalling the API 650 standard (American Petroleum Institute), each tank is considered reliable and in a good condition.
Identification of Land Criticality with the Application of Deep Learning in West Lahat District Using Sentinel-2A Imagery
Authors: Izzaty Atika , Sukojo Bangun Muljo 
Published: December 2021

Abstract
Land is an important factor in human life. In addition of land use that continue to increase every year. Land use is an element of meeting needs. This situation often makes the condition of the land around it questionable the content and level of land productivity. Land whose productivity level is lost can cause critical land to occur. Coupled with the occurrence of uncontrolled development, land productivity has decreased. By using the application of remote sensing, it is able to monitor land conditions, one of which is by using Sentinel-2A data. Sentinel-2A image data was selected to identify the condition or distribution of critical land and critical land parameters that has the most influence on criticality level of the land with Sentinel-2A imagery with a spatial resolution of 10 meters for Red, Green, Blue, and Near-Infrared canals to perform NDVI classification processing. closely related to vegetation. Based on the Regulation of the Director General of Watershed Management and Social Forestry Number: P.4/V-SET/2013 concerning the Technical Guidelines for the Preparation of Spatial Data for Critical Lands, there are 5 parameters for determining the criticality of the processed land as indicators, including the level of erosion distribution, productivity land, land management, slope, and vegetation density. Based on the results of the study, the researchers found that the distribution of critical land in Lahat Regency was 19 hectares or 0.56%, the critical class was 36,090 hectares or 10.1%, the critical potential class was 142,140 hectares or 42.1%, the class which was slightly critical is 156,860 hectares or 46.5%, and non critical class is 3 hectares or 0.074%. for very critical class. These results can be seen with the parameter that most affects the criticality of the land is vegetation density.