bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Big Data Information System in the Field of Public Utilities Management
Authors: Yu Qianqian 
Published: February 2021

AbstractWith the continuous development of information technology, the management of social issues has entered a new era, and a series of management activities in the field of public service management are also facing new issues. Based on the above background, the purpose of this article is the application of big data information system in the field of public utilities management. This article first discusses the relevant theories of public information resources, including the concepts of public information resources, public information resource integration, public information big data platform, etc., and summarizes and summarizes them; secondly, it focuses on the current status of the integration and application of public information resources And the existing problems, and analyzed the advantages of using big data technology to promote the integration and application of public information resources; then, combining the current status of the integration and application of public information resources and the actual needs of the construction of public information big data platforms, the positioning of the public information big data platform is explained. And the construction content, built the overall construction framework of the public information big data platform, and carried out the functional analysis and design of the various subsystems of the platform; finally, discussed the performance evaluation index system of the public information big data platform, using the analytic hierarchy process and fuzzy The comprehensive evaluation method builds a public information big data platform performance evaluation model. When the number of folds is 2, its prediction accuracy is the highest, reaching 96.91%, which evaluates the construction and operation of the platform.
Full Convolutional Network Algorithm Improves the Accuracy of the Boundary of Orthographic Composite Images
Authors: Xiong Jia , Hu Jianxin 
Published: February 2021

Abstract
In the past several “five-year plans”, China has basically established the national, provincial and regional streets of basic geographic information database, and on this basis has carried on a certain degree of improvement. Based on deep learning, this paper aims at improving the boundary accuracy of the orthographic composite image based on the convolutional neural network algorithm. It mainly compares the effects of different parameters on the performance of the network model, and describes the training and testing performance of the model through the corresponding performance evaluation method. In the research and test, the detection accuracy statistics of internal industry encryption points and field control points with different scale accuracy were adopted. The results showed that the error in the DOM detection of new aerial images and satellite images was less than 3m and 9m, which met the technical requirements and improved the boundary accuracy compared with the plane accuracy of existing digital orthophoto images. Thus, it can be seen that the new production technical scheme of aerial image/satellite shadow DOM generated by enhancing the precision of the orthographic composite image boundary based on the full convolutional network algorithm under deep learning is efficient and feasible. The study not only improves the relevant theories, but also has some practical inspirations for future research.
Research on Efficient and Intelligent Regulation of Nutrients in Protected Soilless Culture
Authors: Peng Xiuyuan , Miao Yu , Wang Feng 
Published: February 2021

Abstract
Green plants can effectively purify the air, release negative ions, and form a green field of vision to promote human physical and mental health. Nowadays, with the acceleration of the pace of life and the increase in the pressure of life, people do not have enough time and energy to take care of plants grown indoors in homes. Plants in large office places need to hire professionals to plant them. Raw intelligent control of flower pots can reduce energy consumption, save resources, and realize a smart life of health, environmental protection and low-carbon energy saving. At present, the effective combination of smart flowerpots and the Internet of Things makes smart flowerpots more distinctive and more obvious than traditional flowerpots. The purpose of this article is to study the efficient and intelligent regulation of nutrients in protected soil-less cultivation. In terms of methods, this paper first proposes fuzzy control and fuzzy self-tuning PID control. When the PID parameters of temperature and humidity are controlled by this control system, fuzzy rules, fuzzy reasoning and non-fuzzy processes are also used. In the soil-less cultivation control system, when the humidity in the greenhouse is too low for plant growth, you can choose to adjust the humidity in the greenhouse by starting the spray device or natural ventilation. As for the nutrient liquid level sensor, a light-weight, convenient, simple-to-use, and highly cost-effective water level recognition sensor is manufactured using the characteristics of liquid conductivity. In terms of experiments, between traditional soil-grown lettuce and container-less cabin-grown lettuce under the intelligent control system of soil-less cultivation yields comparative data and results. It is found that intelligent soilless cultivation is superior to traditional soil cultivation in terms planting effects, which reflects the effectiveness of the intelligent soil-less cultivation proposed in this paper.
Classification of Baby Cry Sound Using Higuchi’s Fractal Dimension with K-Nearest Neighbor and Support Vector Machine
Authors: Widhyanti D , Juniati D 
Published: February 2021

Abstract
The crying baby sound is a way to express their physical and psychological conditions. For most people, it is difficult to distinguish the meaning of the sound of a baby’s cry because they are almost all similar. In fact, sometimes parents still lack knowledge of understanding their baby’s condition from the sound of crying. Therefore, research to classify the types of baby crying sounds mathematically becomes very interesting. This study aimed to classify the types of crying sounds for babies using fractal dimensions, particularly the Higuchi Fractal dimension. The data used in this study were 80 data consisting of 4 types of cries, namely hunger cries, tired cries, stomach ache cries, and uncomfortable cries. In this study k-max values of 10, 16, and 50 were selected as experiments. The results of the fractal dimension value of each sound signal were carried out in the data grouping process. The k-fold cross validation data distribution method with values of k = 5 and 10 were used. The classification process was carried out using the K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) methods. Based on the research results, the best accuracy was 78.75% at level 5 decomposition with 5-fold cross validation, k-max value = 10, and K = 9 value on the KNN method. Whereas with the SVM method, the best accuracy was 80% at level 5 decomposition with 10-fold cross validation, k-max value = 10 and c = 10 and using RBF kernel with γ = 10. So in this study, the Support Vector Machine (SVM) method was slightly better than the K-Nearest Neighbor (KNN) method.
Connected Floating Balls Dynamics for Harvesting Energy of Sinusoidal Water Wave
Authors: Viridi Sparisoma , Irwanto Dwi , Hariyanto Nanang , Sasmono Sudarmono 
Published: February 2021

Abstract
Dynamics of connected balls floating on surface of fluid oscillating sinusoidally has reported. In this work a simple electrical generator is simply modeled based on the change of distance between connected balls from its initial value or Δl. By considering only one-dimensional motion of each ball, all the changes Δl are positive, that makes the system easier to be predicted. Sum of all Δl as function of initial initial distance between balls or l is discussed. Water wave wavelength λ is also varied to see how it influences the sum of all Δl.
Static Structural Analysis of Ceramic Internals Experimental Power Reactor (RDE)
Authors: Sulistyo Farisy Yogatama , Himawan Roziq , Nugroho Ari , Bakhri Syaiful 
Published: February 2021

Abstract
In 2018, BATAN propose detail engineering design of Experimental Power Reactor (RDE). An important issue of RDE is Ceramic Internals or Reactor Pressure Vessel (RPV). Ceramic Internals is pathway of helium gas, control rod, absorber ball and also pebble fuel. Its structural component must sustain by the load of 27000 pebbles fuel. A preliminary static structural analysis of bottom reflector, a part of Ceramic Internals, has been studied before, the result was satisfying and could be scale-up to analyse the Ceramic Internals with same methods. Design and static structural simulation are performed by using Solidworks software to study the factor of safety distribution in Ceramic Internals. The design was made in 16 layers with small dowel as the component to endure the movement. Factor of safety was obtained in static simulation using single simplified parts. The preliminary result show that the minimum factor of safety can handle the load of Ceramic Internals structural. This result show that the model is suitable for RDE design.
Development of Monitoring and Control Systems in Cavity Cooling System Test Loop for The Experimental Power Reactor
Authors: Budiman Arif Adtyas , Haryanto Dedy , Santosa Kussigit , Bakhri Syaiful 
Published: February 2021

Abstract
The Experimental Power Reactor as a fourth type of reactor currently being developed in Indonesia is high temperature gas cooled reactor which has a passive cooling system. This passive cooling system uses the principle of natural circulation through changes in water density and called as reactor cavity cooling system. To study the reactor cavity cooling system, a test facility will be created at BATAN which is called the Cavity Cooling Test Loop. This test facility consists of mechanical systems, piping and instrumentation. The instrumentation are includes temperature measurement, flow rate, pressure and heating control. Measurement and control monitoring systems that are needed in order to get data effectively and efficiently have not been made. Therefore, in this study, LabVIEW was used to create monitoring and control programs. A program to monitor temperature, flow rate and pressure has been made with a measurement point of 60 thermocouples, 1 flowmeter, and 1 pressure sensor. The heaters control program is made for 10 units with control of each heater ranging from 200°C to 900°C. Simulation has been done to test the performance of the program using DAQ simulator. Based on the simulation results, the program can be applied to the test facility by paying attention to the input type in the DAQ module.
Design And Analysis Development Of RL Component On Power Use In 3 Phase Motor Loads With Virtual Instrument
Authors: Sumarno Edy , Sunardi Ariyawan , Yunines  , Rubiyanto  
Published: February 2021

Abstract
The development of science and technology must be accompanied by the development of human resources. With reliable human resources and understanding the technology, it will certainly be easier for them to apply their knowledge to the rapid development of the technological world. Understanding of a component is very necessary can analyze the use of each component in an electric power system. Among these components are Resistors and Inductors, the electrical power system components need to know their characteristics so that they can be applied properly to the equipment. The purpose of this study is to obtain the characteristics of the R load and L load on the performance of the 3 phase motor and its effect on the power consumption of the 3 phase motor, so that the power consumption and maintenance costs of the 3 phase motor can be minimized. The research methodology is by installing resistor and inductor circuits in the R, S and T phases that lead to 3 phase motor as the main motor coupled with a 3 phase delta motor which is given DC voltage as a load, while for current and voltage measurement using current transformers and voltage transformers are then analyzed with Data Acquisition System (DAS). On the current vs power of the 0.014 Henry inductor, the load is 0 to 80 VDC averaging 782 mA of current. At a load of 0 to 80 VDC shows a power of 299 watts.
PyChart – A Python module for analysis and visual view of 2D/3D Charts
Authors: Nedelcu D , Latinovic T 
Published: February 2021

Abstract
The paper describes the PyChart module (aimed at analysis and visual view of 2D/3D Charts), which was created with the help of free and Open Source resources, using Python as a programming language and wx.Python as a graphical user interface toolkit. The chart data is imported from a Excel/CSV file with a template structure and is drawn in the PyChart module as XY or XYZ curves similar with Excel scatter with smooth lines and markers style. The main functions of the charts are activated using the toolbar. The module is provided with zooming instruments (fit, pan, zoom in, zoom out), cubic spline curves interpolation, chart intersection with constant X, Y or Z values, visual follow of the 2D chart points to view coordinates, export of data in Windows Clipboard, Excel or Microsoft Word format and saving the chart as a image file.
Spatial Mapping of Diphtheria Vulnerability Level in East Java, Indonesia, using Analytical Hierarchy Process – Natural Break Classification
Authors: Fariza A , Basofi A , Aryani M D 
Published: February 2021

Abstract
Diphtheria is a serious infectious disease induced by the Corynebacterium Diphtheriae bacteria and often causes outbreaks (extraordinary events) in various regions. Based on data from the Ministry of Health, East Java is the biggest benefactor to diphtheria cases in Indonesia. Diphtheria cases in East Java tend to increase, especially in 2018 there were 753 diphtheria cases in 38 districts. Efforts made to prevent, treat, and control diphtheria outbreaks by the government are to analyze the level of susceptibility to diphtheria. This paper proposes a new approach to analyze the level of diphtheria susceptibility using the analytical hierarchy process (AHP) and natural breaks classification in East Java Province, Indonesia. AHP method is used to obtain diphtheria susceptibility values based on seven criteria, such as the number of sufferers, number of deaths, DPT 1, DPT 2, DPT 3 immunization, population density, and humidity. Natural break classification is used to classify the vulnerability values from AHP into three levels of vulnerability, consisting of low, medium, and high. The results of the grouping are displayed in the form of spatial mapping in the form of a web-based geographic information system (web-GIS) on the determination of the diphtheria vulnerability level using the AHP-natural breaks classification. The GVF evaluation for 2016, 2017, and 2018 are respectively 0.66, 0.67, and 0.65 (more than 0.5), which means that the proposed method achieved accurate and significant classification. Spatial-temporal analysis for 2013-2018 also achieves accurate and significant with a GVF value of 0.77. The spatial-temporal analysis can predict the high potential for vulnerability.
Design and Deployment of Fixture on Assembly Line to Improve Productivity
Authors: Aphale S , Nandurdikar V , Desale S 
Published: February 2021

Abstract
In this research, fixture was designed and implemented on assembly line to improve ergonomics along with reducing the required time and manpower. It reduced the required manpower in half and subsequently led improvement the productivity. Providing ease in operation, fixture significantly reduced fatigue to the workers. The aim of this paper was to design and development of fixture for engine door assembly. The problem with assembly was analysed and fixture is proposed to tackle the key issues. To eliminate traditional trial and error approach, the fixture was designed using CAFD along with FEA validation. The proposed fixture manufactured and deployed in current assembly line. It improves total profitability and quality of process by achieving significant reduction of 40% in assembly time. Prior to fixture, time needed for assembly was 24 minutes. After the fixture, this assembly time reduces to 14.4 minutes i.e. 40% reduction is observed.
To till or not to till in a temperate ecosystem? Implications for climate change mitigation
Authors: Cooper H V , Sjögersten S , Lark R M , Mooney S J 
Published: February 2021

Abstract
The management of agricultural soils affect the composition and scale of their greenhouse gas (GHG) emissions. There is conflicting evidence on the effect of zero-tillage on carbon storage and GHG emissions. Here we assess the effects of zero-tillage over a range of time frames (1–15 years) on carbon storage and GHG release and their controls in the UK Net global warming potential was 30% lower under zero-tillage systems, due to lower carbon dioxide fluxes, with the greatest impacts after longer periods of zero-tillage management. Simultaneously, in zero-tillage systems, soil carbon stocks and the proportion of sequestered recalcitrant carbon increased while the temperature sensitivity of soil respiration decreased with time, compared to conventionally soils. We conclude that zero-tillage could play a crucial role in both reducing GHG emissions and at the same time increase soil carbon sequestration, therefore contributing to mitigate against climate change. Our findings are particularly important in the context of designing new policies (for example the Environmental Land Management Schemes in the UK) that ensure the sustainability of agricultural production in a changing climate.
Reusing wastewater for agricultural irrigation: a water-energy-food Nexus assessment in the North Western Sahara Aquifer System
Authors: Ramirez C , Almulla Y , Fuso Nerini F 
Published: February 2021

AbstractThe North Western Sahara Aquifer System stands out as one of the water scarcest regions in the world. Moreover, in recent decades agriculture activity has grown exacerbating the pressure on groundwater resources and pumping energy requirements. In this study, a water-energy-food Nexus approach was used to assess the effect of capturing, treating and reusing wastewater for irrigation. GIS-based tools were used to capture the systems spatial dimension, enabling to match wastewater supply and water demand points, identify demand hotspots and evaluate techno-economically viable wastewater treatment options. Moreover, the minimum energy requirements for brackish water desalination were estimated. Seven domestic wastewater treatment technologies and one irrigation tailwater treatment technology were evaluated, making use of a levelized cost of Water methodology to identify the least-cost system. Four scenarios were constructed based on water-consumption behaviour of farmers towards changes in irrigation water pricing. The identified least-cost wastewater treatment technologies showed clear trade-offs, as different technologies were more cost-effective depending on treatment capacity requirements of the spatially distributed agglomerations. The reuse of treated wastewater/tailwater in agricultural irrigation, showed improvement of groundwater stress, reducing on about 49% water abstractions and groundwater stress levels in the best case scenario. However, groundwater stress still fell on the extremely high category, highlighting the critical condition of the aquifer. Furthermore, reuse of wastewater/tailwater decreased dependency on groundwater pumping and the overall energy-for-water requirements, reducing by about 15% the total energy requirements in the best case scenario. However, to effectively preserve water resources and act holistically towards the sustainable development agenda, measures as better water pricing mechanisms, management strategies to improve water productivity and adoption of more efficient irrigation schemes may be needed.
Subseasonal predictability of the North Atlantic Oscillation
Authors: Albers John R , Newman Matthew 
Published: February 2021

AbstractSkillfully predicting the North Atlantic Oscillation (NAO), and the closely related northern annular mode (NAM), on ‘subseasonal’ (weeks to less than a season) timescales is a high priority for operational forecasting centers, because of the NAO’s association with high-impact weather events, particularly during winter. Unfortunately, the relatively fast, weather-related processes dominating total NAO variability are unpredictable beyond about two weeks. On longer timescales, the tropical troposphere and the stratosphere provide some predictability, but they contribute relatively little to total NAO variance. Moreover, subseasonal forecasts are only sporadically skillful, suggesting the practical need to identify the fewer potentially predictable events at the time of forecast. Here we construct an observationally based linear inverse model (LIM) that predicts when, and diagnoses why, subseasonal NAO forecasts will be most skillful. We use the LIM to identify those dynamical modes that, despite capturing only a fraction of overall NAO variability, are largely responsible for extended-range NAO skill. Predictable NAO events stem from the linear superposition of these modes, which represent joint tropical sea-surface temperature-lower stratosphere variability plus a single mode capturing downward propagation from the upper stratosphere. Our method has broad applicability because both the LIM and the state-of-the-art European Centre for Medium-Range Weather Forecasts Integrated Forecast System (IFS) have higher (and comparable) skill for the same set of predicted high skill forecast events, suggesting that the low-dimensional predictable subspace identified by the LIM is relevant to real-world subseasonal NAO predictions.
Optimal covariant quantum measurements
Authors: Haapasalo Erkka , Pellonpää Juha-Pekka 
Published: February 2021

Abstract
We discuss symmetric quantum measurements and the associated covariant observables modelled, respectively, as instruments and positive-operator-valued measures. The emphasis of this work are the optimality properties of the measurements, namely, extremality, informational completeness, and the rank-1 property which contrast the complementary class of (rank-1) projection-valued measures. The first half of this work concentrates solely on finite-outcome measurements symmetric w.r.t. finite groups where we derive exhaustive characterizations for the pointwise Kraus-operators of covariant instruments and necessary and sufficient extremality conditions using these Kraus-operators. We motivate the use of covariance methods by showing that observables covariant with respect to symmetric groups contain a family of representatives from both of the complementary optimality classes of observables and show that even a slight deviation from a rank-1 projection-valued measure can yield an extreme informationally complete rank-1 observable. The latter half of this work derives similar results for continuous measurements in (possibly) infinite dimensions. As an example we study covariant phase space instruments, their structure, and extremality properties.
A statistical mechanism for operator growth
Authors: Cao Xiangyu 
Published: February 2021

Abstract
It was recently conjectured that in generic quantum many-body systems, the spectral density of local operators has the slowest high-frequency decay as permitted by locality. We show that the infinite-temperature version of this ‘universal operator growth hypothesis’ holds for the quantum Ising spin model in d ⩾ 2 dimensions, and for the chaotic Ising chain (with longitudinal and transverse fields) in one dimension. Moreover, the disordered chaotic Ising chain that exhibits many-body localization can have the same high-frequency spectral density asymptotics as thermalizing models. Our argument is statistical in nature, and is based on the observation that the moments of the spectral density can be written as a sign-problem-free sum over paths of Pauli string operators.