Arctic Operational Information and Forecast Systems

1977 ◽  
pp. 874-876
Author(s):  
P. J. Amaria ◽  
A. A. Bruneau ◽  
P. A. Lapp
1995 ◽  
Vol 32 (3) ◽  
pp. 339-348 ◽  
Author(s):  
M. B. Green ◽  
J. Upton

Reed bed treatment is put in the context of a major water company’s need to provide reliable, high quality, effluents from small sewage treatment works whilst seeking to minimise running costs. Design and operational information is given for reed bed applications in Severn Trent Water. Performance details are provided for application to secondary, tertiary and storm overflow treatment. The results give particular confidence in the system’s ability to deliver very high quality effluents when used for tertiary treatment, the company’s biggest application. Reed beds work well against less demanding criteria for secondary treatment at small sites and show great promise for storm overflow treatment.


2019 ◽  
Vol 943 (1) ◽  
pp. 110-118
Author(s):  
A.A. Kadochnikov

Today, remote sensing data are an important source of operational information about the environment for thematic GIS, this data can be used for the development of water, forestry and agriculture management, in the ecology and nature management, with territorial planning, etc. To solve the problem of ensuring the effective use of the space activities’results in the Krasnoyarsk Territory a United Regional Remote Sensing Center was created. On the basis of the Center, a new satellite receiving complex of FRC KSC SB RAS was put into operation. It is currently receiving satellite data from TERRA, AQUA, Suomi NPP and FENG-YUN satellites. Within the framework in cooperation with the Siberian Regional Center for Remote Sensing the Earth, an archive of satellite data from domestic Resource-P and Meteor-M2 satellites was created. The work considers some features of softwaredevelopment and technological support tools for loading, processing and publishing remote sensing data. The product is created in the service-oriented paradigm based on geoportal technologies and interactive web-cartography. The focus in this article is paid to the peculiarities of implementing the software components of the web GIS, the efficient processing and presentation of geospatial data.


Author(s):  
Andrea Bizzego ◽  
Giulio Gabrieli ◽  
Marc H. Bornstein ◽  
Kirby Deater-Deckard ◽  
Jennifer E. Lansford ◽  
...  

Child Mortality (CM) is a worldwide concern, annually affecting as many as 6.81% children in low- and middle-income countries (LMIC). We used data of the Multiple Indicators Cluster Survey (MICS) (N = 275,160) from 27 LMIC and a machine-learning approach to rank 37 distal causes of CM and identify the top 10 causes in terms of predictive potency. Based on the top 10 causes, we identified households with improved conditions. We retrospectively validated the results by investigating the association between variations of CM and variations of the percentage of households with improved conditions at country-level, between the 2005–2007 and the 2013–2017 administrations of the MICS. A unique contribution of our approach is to identify lesser-known distal causes which likely account for better-known proximal causes: notably, the identified distal causes and preventable and treatable through social, educational, and physical interventions. We demonstrate how machine learning can be used to obtain operational information from big dataset to guide interventions and policy makers.


2021 ◽  
Vol 9 (6) ◽  
pp. 596
Author(s):  
Murugan Ramasamy ◽  
Mohammed Abdul Hannan ◽  
Yaseen Adnan Ahmed ◽  
Arun Kr Dev

Offshore vessels (OVs) often require precise station-keeping and some vessels, for example, vessels involved in geotechnical drilling, generally use Spread Mooring (SM) or Dynamic Positioning (DP) systems. Most of these vessels are equipped with both systems to cover all ranges of water depths. However, determining which system to use for a particular operational scenario depends on many factors and requires significant balancing in terms of cost-benefit. Therefore, this research aims to develop a platform that will determine the cost factors for both the SM and DP station-keeping systems. Operational information and cost data are collected for several field operations, and Artificial Neural Networks (ANN) are trained using those data samples. After that, the trained ANN is used to predict the components of cost for any given environmental situation, fieldwork duration and water depth. Later, the total cost is investigated against water depth for both DP and SM systems to determine the most cost-effective option. The results are validated using two operational scenarios for a specific geotechnical vessel. This decision-making algorithm can be further developed by adding up more operational data for various vessels and can be applied in the development of sustainable decision-making business models for OVs operators.


2021 ◽  
Author(s):  
Gabriela Chaves ◽  
Danielle Monteiro ◽  
Virgilio José Martins Ferreira

Abstract Commingle production nodes are standard practice in the industry to combine multiple segments into one. This practice is adopted at the subsurface or surface to reduce costs, elements (e.g. pipes), and space. However, it leads to one problem: determine the rates of the single elements. This problem is recurrently solved in the platform scenario using the back allocation approach, where the total platform flowrate is used to obtain the individual wells’ flowrates. The wells’ flowrates are crucial to monitor, manage and make operational decisions in order to optimize field production. This work combined outflow (well and flowline) simulation, reservoir inflow, algorithms, and an optimization problem to calculate the wells’ flowrates and give a status about the current well state. Wells stated as unsuited indicates either the input data, the well model, or the well is behaving not as expected. The well status is valuable operational information that can be interpreted, for instance, to indicate the need for a new well testing, or as reliability rate for simulations run. The well flowrates are calculated considering three scenarios the probable, minimum and maximum. Real-time data is used as input data and production well test is used to tune and update well model and parameters routinely. The methodology was applied using a representative offshore oil field with 14 producing wells for two-years production time. The back allocation methodology showed robustness in all cases, labeling the wells properly, calculating the flowrates, and honoring the platform flowrate.


2021 ◽  
Vol 16 (1) ◽  
pp. 208-225
Author(s):  
D.N. NECHAEV ◽  
◽  
T.N. BUKREEVA ◽  

The purpose of the article is to determine the main prerequisites for the development of Russian-Chinese anti-terrorist cooperation, to study the international treaty base that determines the priority areas of bilateral interaction, based on the dynamics of joint anti-terrorist activities, to propose a periodization of interaction between the two countries in the area under study. The research methodology is based on a systematic analysis of bilateral cooperation between Russia and China in countering terrorism. In the course of the study, the authors analyzed the treaty base within the framework of this topic, the UN reports on terrorism and the FATF recommendations for Russia and China. As a result, on the basis of the proposed periodization, it is demonstrated that Russian-Chinese bilateral cooperation in the fight against terrorism is of an applied systemic nature and is fine-tuned in the areas of holding consultative meetings, countering the financing of terrorist activities and organizing joint military exercises. The authors revealed that the problematic area of interaction is the exchange of operational information in the framework of terrorist financing, associated with the unwillingness of the Chinese side to provide relevant information at their disposal. In conclusion, it is proved that it is advisable to expand cooperation between Russia and China in the fight against international terrorism in the direction of countering non-standard challenges and threats to the information space, biological origin, chemical impact and environmental nature.


2018 ◽  
Vol 2 (2) ◽  
pp. 059-075
Author(s):  
Nailul Awalia ◽  
Ni Nyoman Yuliati ◽  
Agus Khazin Fauzi

This study aims to examine the understanding of SMEs actors on accounting information and to know empirically the application of information for small and medium enterprises (MSMEs) in Sekarbela Subdistrict. This research used descriptive approach by interview and survey method. Data collection was done by distributing questionnaires to respondents. The sample of this research is food business MSMEs in Sekarbela Sub district with total of 68 UMKM. However, from 68 MSME samples only 50 samples can be processed. The data is processed by using the frequency distribution then made the average analysis and proportion. The results showed that MSMEs in Sekarbela Subdistrict have applied accounting information although in a simple form. Accounting information most widely applied is the purchase record with the number of 27 respondents or 54% and cash records 28 respondents or 56%. Then MSMEs in Sekarbela Subdistrict have used accounting information, the most widely used is the type of goods sold based on profit or profit of each type of goods with the number of 28 respondents or 56%. Furthermore, MSME also need operational information record about the number of goods sold per day with the number of 31 respondents or 62% and types of goods sold per day with the number of 31 respondents or 62%, records management information that is the production cost report with the number of 32 respondents or 64% financial information is the amount of profit each day with the number 46 respondents or 92%


2021 ◽  
pp. 034-041
Author(s):  
A.Y. Gladun ◽  
◽  
K.A. Khala ◽  

It is becoming clear with growing complication of cybersecurity threats, that one of the most important resources to combat cyberattacks is the processing of large amounts of data in the cyber environment. In order to process a huge amount of data and to make decisions, there is a need to automate the tasks of searching, selecting and interpreting Big Data to solve operational information security problems. Big data analytics is complemented by semantic technology, can improve cybersecurity, and allows you to process and interpret large amounts of information in the cyber environment. Using of semantic modeling methods in Big Data analytics is necessary for the selection and combination of heterogeneous Big Data sources, recognition of the patterns of network attacks and other cyber threats, which must occur quickly to implement countermeasures. Therefore to analyze Big Data metadata, the authors propose pre-processing of metadata at the semantic level. As analysis tools, it is proposed to create a thesaurus of the problem based on the domain ontology, which should provide a terminological basis for the integration of ontologies of different levels. To build a thesaurus of the problem, it is proposed to use the standards of open information resources, dictionaries, encyclopedias. The development of an ontology hierarchy formalizes the relationships between data elements that will be used in future for machine learning and artificial intelligence algorithms to adapt to changes in the environment, which in turn will increase the efficiency of big data analytics for the cybersecurity domain.


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