scholarly journals Model of baddeleyite recovery from dump products of an apatite-baddeleyite processing plant using a CVD6 concentrator

2021 ◽  
Vol 248 ◽  
pp. 281-289
Author(s):  
Vladislav Pelikh ◽  
Valery Salov ◽  
Alexander Burdonov ◽  
Nikita Lukyanov
Keyword(s):  
Regression Analysis ◽  
Main Idea ◽  
Continuous Variable ◽  
Coarse Grained ◽  
Group Method ◽  
Processing Plant ◽  
Technological Parameters ◽  
Fine Grained ◽  
Processing Plants ◽  
Valve Opening

The paper is devoted to developing a model of baddeleyite recovery from dump products of an apatite-baddeleyite processing plant using centrifugal concentrators. The relevance of the work arises from the acquisition of new knowledge on the optimization of technological parameters of centrifugal concentrators using Knelson CVD (continuous variable discharge) technology – in particular, setting the frequency of valve opening and the duration of valves remaining open. The purpose of the research was to assess the applicability of CVD technology in the treatment of various dump products of the processing plant and to build a model of dependencies between the concentrate and tailings yields and the adjustable parameters, which will allow to perform preliminary calculations of the efficiency of implementing this technology at processing plants. The research objects are middling and main separation tailings of the coarse-grained stream and combined product of main and recleaner separation tailings of the fine-grained stream. The study uses general methods of mathematical statistics: methods of regression analysis, aimed at building statistically significant models, describing dependence of a particular variable on a set of regressors; group method of data handling, the main idea of which is to build a set of models of a given class and choose the optimal one among them. Authors proposed an algorithm for processing experiment results based on classical regression analysis and formulated an original criterion for model selection. Models of dependencies between the concentrate and tailings yields and the adjustable parameters were built, which allowed to establish a relationship between the concentrate yield and the valve opening time, as well as a relationship between the tailings yield and the G-force of the installation.

scholarly journals Smelting options for carbon ferrochrome based on ore raw materials, middlings and their technological evaluation

2022 ◽  
Vol 320 (1) ◽  
pp. 51-59
Author(s):  
S. Baisanov ◽  
◽  
Ye.Zh. Shabanov ◽  
K.V. Grigorovich ◽  
R.T. Toleukadyr ◽  
...  
Keyword(s):  
Large Scale ◽  
Raw Materials ◽  
Main Idea ◽  
Economic Indicators ◽  
Processing Plant ◽  
Technological Parameters ◽  
Gas Cleaning ◽  
Carbon Ferrochrome ◽  
Technological Evaluation ◽  
Technical And Economic Indicators

The article presents the results of large-scale laboratory tests carried out in the conditions of the Chemical and Metallurgical Institute named after V.I. Zh. Abishev on the use of briquetted mono-charge in the smelting of carbon ferrochrome on a 250 kVA furnace. The purpose of these studies was to determine the technological parameters of the use of briquetted mono-charge containing in its composition chrome ore, wastes from the production of high-carbon ferrochrome, middlings and various carbonaceous reducing agents. The main idea of using these briquettes was to multiply the contact surface of the reductant and ore, which should speed up the technological process. The principal possibility of smelting a standard alloy using briquetted mono-charge is shown. The alloy for individual charge options meets the requirements of the standards. In comparison with the technology without the use of briquettes, the mono-charge technology has shown advantages in all main parameters. The technology with the use of briquettes from the dust of the AktZF gas cleaning system is distinguished by a low yield of non-standard metal and slag, the bulk of the material goes into the gas collection system. Technologies from briquettes from fines pellet production area of Donskoy ore mining and processing plant and flash have very low specific technical and economic indicators and cannot be recommended for industrial use. Improvement of briquetting modes and technology of their smelting is required. The technical and economic indicators were higher than the current one, showed briquettes from ore and coke of the People's Republic of China, briquettes of ore from borlin and shubarkol coals of Kazakhstan.

Prevalence and Typing of Listeria monocytogenes in Raw Catfish Fillets†

2006 ◽  
Vol 69 (4) ◽  
pp. 815-819 ◽  
Author(s):  
CHUNG-HSI CHOU ◽  
JUAN L. SILVA ◽  
CHINLING WANG
Keyword(s):  
Listeria Monocytogenes ◽  
Repetitive Element ◽  
Group Method ◽  
Processing Plant ◽  
Natural Habitats ◽  
Listeria Species ◽  
Pair Group ◽  
Catfish Fillets ◽  
Processing Plants ◽  
Different Seasons

Raw channel catfish fillets collected from three processing plants during four time periods were tested for the presence of Listeria species. Listeria monocytogenes was the predominant Listeria species found in these catfish fillets, with 25 to 47% prevalence. Other Listeria species, such as L. welshimeri, L. innocua, L. ivanovii, L. grayi, and L. seeligeri, were also found. L. monocytogenes isolates were further fingerprinted by a repetitive element PCR. Forty distinctive electrophoretic types (ETs) and three genetic clusters were determined by Dice coefficient analysis and UPGMA (unweighted pair group method using arithmetic averages). Twenty of 40 ETs were represented by a single isolate, and the other 20 ETs were represented by 2 to 11 isolates. Thirty-five ETs, represented by 76 isolates, were found in processing plant A, B, or C and designated plant-specific types. The remaining five ETs, represented by 21 isolates, were found in multiple plants and designated nonplant-specific types. In addition, 10 ETs from 52 isolates were found repeatedly during different seasons. Plant-specific and nonplant-specific L. monocytogenes coexisted in processed catfish fillets. Some isolates were persistently found in processed fillets, suggesting that either the current sanitation procedures used by these plants are inadequate or that these isolates originated from the natural habitats of the catfish. The results also suggest that the repetitive element PCR is a useful tool for differentiating L. monocytogenes subtypes and can be used for tracing the source of a contamination.

scholarly journals A Strategy of Data Synchronization in Distributed System with Read Separating from Write

2020 ◽  
Vol 38 (1) ◽  
pp. 209-215 ◽  
Author(s):  
Jintao Gao ◽  
Wenjie Liu ◽  
Zhanhuai Li
Keyword(s):  
Main Idea ◽  
Distributed Database ◽  
Coarse Grained ◽  
Data Synchronization ◽  
Space Utilization ◽  
Relation Database ◽  
Fine Grained ◽  
Network Cost ◽  
Nosql Database ◽  
Better Than

Read separating from write is a strategy that NewSQL adopts to incorporate the advantages of traditional relation database and NoSQL database. Under this architecture, baseline data is split into multiple partitions stored at distributed physical nodes, while delta data is stored at single transaction node. For reducing the pressure of transaction node and improving the query performance, delta data needs to be synchronized into storage nodes. The current strategies trigger the procedure of data synchronization per partition, meaning that unchanged partitions will also participate in data synchronization, which consumes extra network cost, local IO and space resources. For improving the efficiency of data synchronization meanwhile mitigating space utilization, the fine-grained data synchronization strategy is proposed, whose main idea includes that fine-grained logical partitions upon original coarse-grained partitions is established, providing more correct synchronized unit; the delta data sensing strategy is introduced, which records the mapping between changed partitions and its delta data; instead of partition driven, the data synchronization through the delta-broadcasting mechanism is driven, constraining that only changed partitions can participate in data synchronization. The fine-grained data synchronization strategy on Oceanbase is implemented, which is a distributed database with read separating from write, and the results show that our strategy is better than other strategies in efficiency of data synchronizing and space utilization.

scholarly journals OPTIMIZATION OF CONCRETE COMPOSITIONS WITH SECONDARY INDUSTRIAL PRODUCTS

2021 ◽  
pp. 51-61
Author(s):  
M. I. NETESA ◽  
A. V. KRASNYUK ◽  
A. M. NETESA ◽  
N. A. NIKIFOROVA
Keyword(s):  
Grain Size ◽  
Iron Ore ◽  
Concrete Mixture ◽  
Processing Plant ◽  
Fine Aggregate ◽  
Iron Ores ◽  
Industrial Products ◽  
Fine Grained ◽  
Processing Plants ◽  
Ore Dressing

Purpose. Analyze scientific publications on the existing problems of environmental pollution by secondary industrial products. Search for ways to solve these issues through the rational use of concrete in construction with additives of secondary industrial products, especially fine-grained ones. Determination of rational compositions of medium-strength concrete with the minimum required consumption of cement and filler from iron ore dressing wastes of mining and processing plants. Methodology. To achieve this goal, the experience of improving the structure and properties of concrete by introducing complex additives based on secondary industrial products into its composition is analyzed. The following materials were used for the research: Portland cement CEM 41.7 from Krivoy Rog; as a large aggregate – crushed granite with a maximum grain size of 20 mm; fine aggregate – river quartz sand; mineral additives – products of concentration of iron ores of the Southern Mining and Processing Plant. The experiment was carried out on certified equipment. Control specimens with a side of 10 cm were formed. The compressive strength of concrete was determined according to a standard procedure. Based on the results of the mathematical analysis, graphical dependences of the change in the optimized characteristics on the variable parameters – the consumption of cement, the products of concentration of iron ores and the plasticizer – were built. Findings. Based on the results of testing the samples, the calculation of mathematical models of the experiment was carried out and polynomials of the third degree were obtained for the optimized parameters – the average strength of the samples and the coefficient of efficiency of using cement. The following patterns can be distinguished. The strength of concrete depends to the greatest extent on the consumption of cement in the composition of the concrete mixture and increases significantly with an increase in its content within the studied limits. With an increase in the filler content in the studied range, the strength of concrete, and, accordingly, the coefficient of efficiency of using cement increases with a decrease in the content of cement in the composition of the concrete mixture. Originality. The studies carried out make it possible to determine the main regularities of increasing the efficiency of cement use when utilizing local secondary industrial products in concrete, namely, the introduction of iron ore dressing waste from mining and processing plants as a fine-grained additive in concrete. It was found that it is possible to obtain the required low concrete strength with a significantly lower cement consumption by ensuring a rational grain size composition of the concrete mixture components. Practical value. When designing concrete compositions with a high coefficient of cement utilization, it is necessary to use the obtained research results, providing cement savings and utilizing a significant amount of fine-grained secondary industrial products.

scholarly journals Learning fine-grained estimation of physiological states from coarse-grained labels by distribution restoration

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Zengyi Qin ◽  
Jiansheng Chen ◽  
Zhenyu Jiang ◽  
Xumin Yu ◽  
Chunhua Hu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Learning Community ◽  
Physiological State ◽  
Continuous Variable ◽  
Machine Learning Algorithms ◽  
Coarse Grained ◽  
Fine Grained ◽  
True Value ◽  
Approximate Order ◽  
Pathological Tremor

AbstractDue to its importance in clinical science, the estimation of physiological states (e.g., the severity of pathological tremor) has aroused growing interest in machine learning community. While the physiological state is a continuous variable, its continuity is lost when the physiological state is quantized into a few discrete classes during recording and labeling. The discreteness introduces misalignment between the true value and its label, meaning that these labels are unfortunately imprecise and coarse-grained. Most previous work did not consider the inaccuracy and directly utilized the coarse labels to train the machine learning algorithms, whose predictions are also coarse-grained. In this work, we propose to learn a precise, fine-grained estimation of physiological states using these coarse-grained ground truths. Established on mathematical rigorous proof, we utilize imprecise labels to restore the probabilistic distribution of precise labels in an approximate order-preserving fashion, then the deep neural network learns from this distribution and offers fine-grained estimation. We demonstrate the effectiveness of our approach in assessing the pathological tremor in Parkinson’s Disease and estimating the systolic blood pressure from bioelectrical signals.

Correlation between dislocation, grain boundary and interface of duplex SS in stress corrosion cracking(SCC)

1990 ◽  
Vol 48 (4) ◽  
pp. 928-929
Author(s):  
Wang Zheng-fang ◽  
Z.F. Wang
Keyword(s):  
Stainless Steel ◽  
Thermal Cycle ◽  
Secondary Phase ◽  
Corrosion Cracking ◽  
Coarse Grained ◽  
Test Environment ◽  
Fine Grained ◽  
Evaluation Test ◽  
Welding Thermal Cycle ◽  
Micro Analysis

The main purpose of this study highlights on the evaluation of chloride SCC resistance of the material,duplex stainless steel,OOCr18Ni5Mo3Si2 (18-5Mo) and its welded coarse grained zone(CGZ).18-5Mo is a dual phases (A+F) stainless steel with yield strength:512N/mm2 .The proportion of secondary Phase(A phase) accounts for 30-35% of the total with fine grained and homogeneously distributed A and F phases(Fig.1).After being welded by a specific welding thermal cycle to the material,i.e. Tmax=1350°C and t8/5=20s,microstructure may change from fine grained morphology to coarse grained morphology and from homogeneously distributed of A phase to a concentration of A phase(Fig.2).Meanwhile,the proportion of A phase reduced from 35% to 5-10°o.For this reason it is known as welded coarse grained zone(CGZ).In association with difference of microstructure between base metal and welded CGZ,so chloride SCC resistance also differ from each other.Test procedures:Constant load tensile test(CLTT) were performed for recording Esce-t curve by which corrosion cracking growth can be described, tf,fractured time,can also be recorded by the test which is taken as a electrochemical behavior and mechanical property for SCC resistance evaluation. Test environment:143°C boiling 42%MgCl2 solution is used.Besides, micro analysis were conducted with light microscopy(LM),SEM,TEM,and Auger energy spectrum(AES) so as to reveal the correlation between the data generated by the CLTT results and micro analysis.

scholarly journals Balanced Sparsity for Efficient DNN Inference on GPU

2019 ◽  
Vol 33 ◽  
pp. 5676-5683 ◽  
Author(s):  
Zhuliang Yao ◽  
Shijie Cao ◽  
Wencong Xiao ◽  
Chen Zhang ◽  
Lanshun Nie
Keyword(s):  
Deep Neural Networks ◽  
General Purpose ◽  
Coarse Grained ◽  
Efficient Computation ◽  
Model Accuracy ◽  
Sparse Model ◽  
Model Inference ◽  
Fine Grained ◽  
Practical Inference ◽  
Speed Up

In trained deep neural networks, unstructured pruning can reduce redundant weights to lower storage cost. However, it requires the customization of hardwares to speed up practical inference. Another trend accelerates sparse model inference on general-purpose hardwares by adopting coarse-grained sparsity to prune or regularize consecutive weights for efficient computation. But this method often sacrifices model accuracy. In this paper, we propose a novel fine-grained sparsity approach, Balanced Sparsity, to achieve high model accuracy with commercial hardwares efficiently. Our approach adapts to high parallelism property of GPU, showing incredible potential for sparsity in the widely deployment of deep learning services. Experiment results show that Balanced Sparsity achieves up to 3.1x practical speedup for model inference on GPU, while retains the same high model accuracy as finegrained sparsity.

scholarly journals Submarine lava deltas of the 2018 eruption of Kīlauea volcano

2021 ◽  
Vol 83 (4) ◽  
Author(s):  
S. Adam Soule ◽  
Michael Zoeller ◽  
Carolyn Parcheta
Keyword(s):  
Grain Size ◽  
Pore Pressure ◽  
Mechanistic Model ◽  
Large Fraction ◽  
Volcanic Hazards ◽  
Lava Flows ◽  
Coarse Grained ◽  
Fine Grained ◽  
Fine Grain ◽  
Delta Formation

AbstractHawaiian and other ocean island lava flows that reach the coastline can deposit significant volumes of lava in submarine deltas. The catastrophic collapse of these deltas represents one of the most significant, but least predictable, volcanic hazards at ocean islands. The volume of lava deposited below sea level in delta-forming eruptions and the mechanisms of delta construction and destruction are rarely documented. Here, we report on bathymetric surveys and ROV observations following the Kīlauea 2018 eruption that, along with a comparison to the deltas formed at Pu‘u ‘Ō‘ō over the past decade, provide new insight into delta formation. Bathymetric differencing reveals that the 2018 deltas contain more than half of the total volume of lava erupted. In addition, we find that the 2018 deltas are comprised largely of coarse-grained volcanic breccias and intact lava flows, which contrast with those at Pu‘u ‘Ō‘ō that contain a large fraction of fine-grained hyaloclastite. We attribute this difference to less efficient fragmentation of the 2018 ‘a‘ā flows leading to fragmentation by collapse rather than hydrovolcanic explosion. We suggest a mechanistic model where the characteristic grain size influences the form and stability of the delta with fine grain size deltas (Pu‘u ‘Ō‘ō) experiencing larger landslides with greater run-out supported by increased pore pressure and with coarse grain size deltas (Kīlauea 2018) experiencing smaller landslides that quickly stop as the pore pressure rapidly dissipates. This difference, if validated for other lava deltas, would provide a means to assess potential delta stability in future eruptions.

scholarly journals A cooperative DDoS attack detection scheme based on entropy and ensemble learning in SDN

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Shanshan Yu ◽  
Jicheng Zhang ◽  
Ju Liu ◽  
Xiaoqing Zhang ◽  
Yafeng Li ◽  
...  
Keyword(s):  
Ensemble Learning ◽  
Denial Of Service ◽  
Attack Detection ◽  
Coarse Grained ◽  
Communication Overhead ◽  
Detection Scheme ◽  
Fine Grained ◽  
Ddos Attack ◽  
Network Status ◽  
Ddos Attack Detection

AbstractIn order to solve the problem of distributed denial of service (DDoS) attack detection in software-defined network, we proposed a cooperative DDoS attack detection scheme based on entropy and ensemble learning. This method sets up a coarse-grained preliminary detection module based on entropy in the edge switch to monitor the network status in real time and report to the controller if any abnormality is found. Simultaneously, a fine-grained precise attack detection module is designed in the controller, and a ensemble learning-based algorithm is utilized to further identify abnormal traffic accurately. In this framework, the idle computing capability of edge switches is fully utilized with the design idea of edge computing to offload part of the detection task from the control plane to the data plane innovatively. Simulation results of two common DDoS attack methods, ICMP and SYN, show that the system can effectively detect DDoS attacks and greatly reduce the southbound communication overhead and the burden of the controller as well as the detection delay of the attacks.

Rheology of hydrocarbon gels

1950 ◽  
Vol 200 (1061) ◽  
pp. 183-188 ◽  
Keyword(s):  
Mechanical Properties ◽  
Experimental Measurement ◽  
Theoretical Basis ◽  
Continuous Media ◽  
Point Of View ◽  
Coarse Grained ◽  
Testing Instrument ◽  
Fine Grained ◽  
Mineral Oils ◽  
Space And Time

Hydrocarbon gels contain a number of materials, such as rubber, greases, saponified mineral oils, etc., of great interest for various engineering purposes. Specific requirements in mechanical properties have been met by producing gels in appropriately chosen patterns of constituent components of visible, colloidal, molecular and atomic sizes, ranging from coarse-grained aggregates, represented by sponges, foams, emulsions, etc.; to fine-grained and apparently homogeneous ones, represented by optically clear compounds. The engineer who has to deal with the whole range of such materials will adopt a macroscopic point of view, based on an apparent continuity of all the material structures and of the distributions in space and time of the displacements and forces occurring under mechanical actions. It has been possible to determine these distributions in the framework of a comprehensive scheme in which the fundamental principles of the mechanics of continuous media provide the theoretical basis, and a testing instrument of new design, termed Rheogoniometer, the means of experimental measurement (Weissenberg 1931, 1934, 1946, 1947, 1948).

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