Improvements in the selection of real components forming a substitute mixture for petroleum fractions

2009 ◽  
Vol 63 (4) ◽  
Author(s):  
Egon Eckert ◽  
Tomáš Vaněk
Keyword(s):  
Chemical Engineering ◽  
Complex Mixtures ◽  
Second Phase ◽  
Liquid Density ◽  
Bulk Properties ◽  
Aromatic Carbon ◽  
Original Mixture ◽  
Petroleum Fractions ◽  
Selection Of ◽  
Carbon Analysis

AbstractComplex mixtures, particularly petroleum fractions, usually need to be suitably modeled before providing the simulation and other types of chemical engineering calculations. The most convenient way is to describe the original mixture by a substitute mixture. The formerly published approach based on the employment of substitute mixtures of real components can be improved in order to get a closer match between the behavior of the original and substitute mixtures. In the first phase of the algorithm, a new concept of a band around the characterization curves brings wider possibilities for the selection of real components into the substitute mixture. The second phase, which is used to determine the composition of the substitute mixture, can be also improved by considering the global or bulk properties of the original mixture if available. Typically, some of the properties e.g. liquid density, molecular mass and PNA (Paraffinic/Naphthenic/Aromatic carbon) analysis can be measured and used to improve the adjustment of the composition. The improved algorithm is illustrated by an example.

scholarly journals Obsidian from the Neolithic Layers of “Grotta di San Michele Arcangelo di Saracena” (Cosenza), Italy. A Preliminary Report

2021 ◽  
Vol 7 (1) ◽  
pp. 615-630
Author(s):  
Vincenza Forgia ◽  
Robert H. Tykot ◽  
Andrea Vianello ◽  
Elena Natali
Keyword(s):  
Preliminary Report ◽  
Second Phase ◽  
Early Neolithic ◽  
Late Neolithic ◽  
Resources Management ◽  
Lithic Assemblage ◽  
Wear Analysis ◽  
Selection Of ◽  
Preliminary Selection

Abstract The paper presents the results obtained by techno-typological analysis of a lithic assemblage from the Neolithic layers of Grotta San Michele Arcangelo di Saracena (Cosenza) together with the results of micro-wear analysis obtained from a preliminary selection of obsidian artifacts with different provenances distinguished by pXRF analysis. The site provides one of the best preserved Neolithic sequences in the area, from the earliest Impressed Wares (or Impresse Arcaiche) (early sixth millennium BC) to the Spatarella pottery style (end fifth – early fourth millennium BC). Along the Neolithic sequence, it is possible to observe some major changes within lithic resources management. In particular, it is possible to notice some techno-typological breakages between the Early Neolithic and the further stages, until the second phase of the Late Neolithic, when another rupture, corresponding to the Spatarella facies, is evident.

scholarly journals Self-Adaptive K-Means Based on a Covering Algorithm

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Yiwen Zhang ◽  
Yuanyuan Zhou ◽  
Xing Guo ◽  
Jintao Wu ◽  
Qiang He ◽  
...  
Keyword(s):  
Large Scale ◽  
Clustering Algorithm ◽  
Real Data ◽  
Second Phase ◽  
Data Sets ◽  
Number Of Clusters ◽  
Large Scale Data ◽  
Long Time ◽  
Two Phases ◽  
Selection Of

The K-means algorithm is one of the ten classic algorithms in the area of data mining and has been studied by researchers in numerous fields for a long time. However, the value of the clustering number k in the K-means algorithm is not always easy to be determined, and the selection of the initial centers is vulnerable to outliers. This paper proposes an improved K-means clustering algorithm called the covering K-means algorithm (C-K-means). The C-K-means algorithm can not only acquire efficient and accurate clustering results but also self-adaptively provide a reasonable numbers of clusters based on the data features. It includes two phases: the initialization of the covering algorithm (CA) and the Lloyd iteration of the K-means. The first phase executes the CA. CA self-organizes and recognizes the number of clusters k based on the similarities in the data, and it requires neither the number of clusters to be prespecified nor the initial centers to be manually selected. Therefore, it has a “blind” feature, that is, k is not preselected. The second phase performs the Lloyd iteration based on the results of the first phase. The C-K-means algorithm combines the advantages of CA and K-means. Experiments are carried out on the Spark platform, and the results verify the good scalability of the C-K-means algorithm. This algorithm can effectively solve the problem of large-scale data clustering. Extensive experiments on real data sets show that the accuracy and efficiency of the C-K-means algorithm outperforms the existing algorithms under both sequential and parallel conditions.

scholarly journals Selection of the most adequate trip-modelling tool for integrated transport planning system

2016 ◽  
Vol 37 (1) ◽  
pp. 55-66 ◽  
Author(s):  
Piotr Sawicki ◽  
Marcin Kiciński ◽  
Szymon Fierek
Keyword(s):  
Selection Criteria ◽  
Selection Process ◽  
Regional Scale ◽  
Selection Procedure ◽  
Planning System ◽  
Second Phase ◽  
Transport Planning ◽  
Phase Selection ◽  
Technical Requirements ◽  
Selection Of

This paper deals with the problem of selection the most suitable trip-modelling tool (TMT), which is a part of the more complex integrated transport planning system (ITPS) at the regional scale. Since an application of TMT is not autonomous and several different users exist the selection problem is not a trivial. In this paper, an original five-phase selection procedure is presented. The first phase consists in specifica¬tion of both, detailed expectations of all identified users and technical requirements of ITPS. Second phase deals with research on available TMT while a third one is concentrated on defining a comprehensive set of criteria. In this phase critical criteria as well as selection criteria are defined. First one is utilised to eliminate unacceptable TMTs in phase four and second one to evaluate and select most adequate TMT in phase five. In the paper an exemplary application of this procedure is presented. The authors have defined 2 critical criteria and a set of 19 selection criteria. The last one is divided into 3 main subsets, i.e. functional, technical and financial contexts of selection process. All the selection criteria are characterised by 43 sub-criteria and some of them are more detailed extended. Using this procedure 3 out of 6 alternative TMTs including Emme, Aimsun and Visum have been initially accepted and next evaluated. Finally, Visum has been selected and recommended for application into ITPS.

scholarly journals Estudio de la enseñanza de ecosistemas amazónicos a través de la metodología de aprendizaje basada en la resolución de problemas (ABRP)

2018 ◽  
Vol 22 ◽  
pp. 9
Author(s):  
Carlos Henrique Nascimento ◽  
Ires Paula de Andrade Miranda
Keyword(s):  
Problem Solving ◽  
Data Collection ◽  
Primary School ◽  
School Environment ◽  
Problem Based Learning ◽  
Problem Formulation ◽  
Teaching Methodology ◽  
Second Phase ◽  
Two Phases ◽  
Selection Of

The purpose was to analyze the Problem-based learning (PBL) as a methodological alternative for primary school that favor learning about Amazonian ecosystems. This research is descriptive with a qualitative-quantitative approach. The study was carried out with students from the 9th year of primary school. The teaching methodology based on the PBL was applied in two phases: In the first phase, a test of previous conceptions was carried out in order to know the perception of the students on topics related to some units of landscapes of the Amazonian ecosystems. The second phase consisted of the implementation of the learning methodology in the school environment. Four different phases were established in the application: i) selection of topics; ii) problem formulation; iii) problem solving; iv) synthesis and evaluation. The data collection instruments used were: preconceptions test and skills chart. The results showed that after the application of the ABRP methodology, the cognitive recognition of the Amazonian ecosystems can be perceived in the students, reaching additional goals that the PCN establish.

Intelligent Symbiotic Relay Selection Technique for 5G Networks

2019 ◽  
Vol 43 ◽  
pp. 84-100
Author(s):  
Maryleen U. Ndubuaku ◽  
Kennedy Chinedu Okafor ◽  
Chidiebele Chinwendu Udeze ◽  
Omar Salih
Keyword(s):  
Relay Selection ◽  
Network Capacity ◽  
The Other ◽  
Link Quality ◽  
Support Vector ◽  
Second Phase ◽  
Signal To Noise ◽  
Relay Nodes ◽  
Geographical Locations ◽  
Selection Of

The growing demand for bandwidth and spectrum has inspired the ongoing efforts to establish the future 5G network supporting vertical sectors such as cyber-physical systems (CPS). Cooperative communication is one of the requisite techniques to improve coverage, network capacity and reduce power consumption in the network. In this paper, a symbiotic two-phase intelligent transmission is considered. The first phase occurs between the source and the candidate relays, and involves the selection of a set of “reliable relays”. The second phase occurs between the reliable relays and the destination, and involves the selection of the “best relay” for transmission. Dynamic relay selection using k-means clustering is used to detect the most significant correlation between all the channel state information (CSI) attributes in the system. The work identified the reliable relays while reducing the number of relay nodes for the second transmission phase. Contextual scenarios are created with typical network configuration using three geographical locations Coventry, Birmingham and London. An experimental validation is done with Omnet++ environment for the scenarios of three geographical locations. A natural grouping of mobile users is carried out leveraging the relay capabilities. The results are validated using support vector machine (SVM) classification algorithm. Considering urban environment deployment of relay nodes, metrics such as signal-to-noise-plus-interference ratio (SINR), attenuation, signal to noise ratio (SNR), link quality, k-means clustering, accuracy, and root mean square error (RMSE) are investigated for the Direct-2-Direct (D2D) capable relays. It was observed that the proposed technique both outperforms the other fixed-parameter relay selection techniques and improves with larger datasets unlike the other techniques.

The needs of siblings of children with a life-threatening illness, part 1: Conceptualization and development of a measure

2017 ◽  
Vol 15 (6) ◽  
pp. 644-664 ◽  
Author(s):  
Marianne Olivier-D'Avignon ◽  
Serge Dumont ◽  
Pierre Valois ◽  
S. Robin Cohen
Keyword(s):  
Qualitative Methodology ◽  
Critically Ill Children ◽  
Second Phase ◽  
Difficult Situation ◽  
Promising Tool ◽  
Third Phase ◽  
Life Threatening Illness ◽  
Preliminary Version ◽  
Life Threatening ◽  
Selection Of

ABSTRACTObjective:The presence of a child afflicted with a life-threatening illness is a difficult situation for the child's siblings, especially when their own needs are left unmet. The present article describes the first three phases of research involved in the conceptualization, development, and content validation of an initial version of the Inventaire des Besoins de la Fratrie d'Enfants Malades Sévèrement (IBesFEMS) [Needs Inventory for Siblings of Critically ill Children].Method:The first phase of the development of this instrument was conducted using qualitative methodology (focus groups: 6 siblings, 8 parents). The second phase consisted of validating the content of a pool of items developed according to the needs identified in the first phase. Some 21 participants (3 psychometricians, 3 researchers, 9 clinicians, and 6 siblings) evaluated each item for relevance and clarity. Finally, during the third phase, the acceptability and administration procedures of the preliminary version of the instrument were assessed qualitatively by five siblings.Results:The first phase led to production of a typology made up of 43 needs in 10 different environments. The second phase allowed for selection of the items that were clearest and most relevant, based on expert opinion. This procedure gave rise to a first version of the IBesFEMS, which consisted of 48 items.Significance of results:The IBesFEMS appears to be a promising tool for specifically assessing the needs of the adolescent siblings of seriously ill children.

Comparison of Two Anti-Depressant Drugs (Imipramine and Pheniprazine) In Endogenous Depressive Illnesses in Female In-Patients

1961 ◽  
Vol 107 (451) ◽  
pp. 1000-1002 ◽  
Author(s):  
Donald P. Oakley
Keyword(s):  
Placebo Group ◽  
Therapeutic Agent ◽  
Endogenous Depression ◽  
Controlled Trials ◽  
Second Phase ◽  
Full Dosage ◽  
Selection Of Patients ◽  
Selection Of

The following study was designed to compare the effectiveness of imipramine (Tofranil) and pheniprazine (Cavodil) in the treatment of endogenous depression. Controlled trials have shown the value of imipramine (Holdway, 1960) and therefore no placebo group was included. The theoretical advantages of a cross-over technique were considered to be outweighed by such disadvantages as the tendency for the effects of the first therapeutic agent to continue into the second phase of the experiment; and the tendency for rapid remissions to occur with anti-depressive drugs and to persist for a period despite withdrawal. Thus two similar groups of patients, each treated with full dosage of their respective drugs, were compared. The selection of patients was randomized, and the trial was blind throughout.

Research on the Jet Flow Control Technology in LNG Liquid Charging Process

2014 ◽  
Vol 511-512 ◽  
pp. 1044-1047
Author(s):  
Yun Yang ◽  
Gong Sheng Yang ◽  
Jie Jiang ◽  
Wen Da Zhu ◽  
Bing Li ◽  
...  
Keyword(s):  
Flow Control ◽  
Jet Flow ◽  
Liquid Density ◽  
Control Technology ◽  
Number Range ◽  
Tank Bottom ◽  
Lng Tank ◽  
Liquid Flows ◽  
Selection Of ◽  
The Way

Due to LNG liquid density is uneven, traditional LNG tank bottom discharge way produces layering and rolling phenomenon, in this paper, the way of charging LNG liquid in a circle is put forward. 30,000 square tank is taken as an example, the nozzle jet angle and nozzle number range are calculated. Through the selection of reasonable nozzle jet angle and nozzle number, the new charged LNG liquid flows circularly and mixes with original liquid automatically, the probability of layering and rolling phenomenon reduced greatly.

scholarly journals A Novel Granularity Optimal Feature Selection based on Multi-Variant Clustering for High Dimensional Data

2021 ◽  
Vol 12 (3) ◽  
pp. 5051-5062
Author(s):  
Srinivas Kolli Et. al.
Keyword(s):  
Feature Selection ◽  
High Dimensional Data ◽  
Classification Performance ◽  
High Dimensional ◽  
Second Phase ◽  
Data Sets ◽  
Aggressive Approach ◽  
Related Data ◽  
Optimal Feature ◽  
Selection Of

Clustering is the most complex in multi/high dimensional data because of sub feature selection from overall features present in categorical data sources. Sub set feature be the aggressive approach to decrease feature dimensionality in mining of data, identification of patterns. Main aim behind selection of feature with respect to selection of optimal feature and decrease the redundancy. In-order to compute with redundant/irrelevant features in high dimensional sample data exploration based on feature selection calculation with data granular described in this document. Propose aNovel Granular Feature Multi-variant Clustering based Genetic Algorithm (NGFMCGA) model to evaluate the performance results in this implementation. This model main consists two phases, in first phase, based on theoretic graph grouping procedure divide features into different clusters, in second phase, select strongly  representative related feature from each cluster with respect to matching of subset of features. Features present in this concept are independent because of features select from different clusters, proposed approach clustering have high probability in processing and increasing the quality of independent and useful features.Optimal subset feature selection improves accuracy of clustering and feature classification, performance of proposed approach describes better accuracy with respect to optimal subset selection is applied on publicly related data sets and it is compared with traditional supervised evolutionary approaches

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