A Formal Two-Phase Method for Decomposition of Complex Design Problems

2005 ◽  
Vol 127 (2) ◽  
pp. 184-195 ◽  
Author(s):  
Li Chen ◽  
Zhendong Ding ◽  
Simon Li
Keyword(s):  
Decomposition Method ◽  
Incidence Matrix ◽  
Phase 1 ◽  
Hierarchical Cluster ◽  
Phase Method ◽  
Phase 2 ◽  
Two Phase ◽  
Design Problems ◽  
Complex Design ◽  
Point Analysis

This paper presents a formal two-phase decomposition method for complex design problems that are represented in an attribute-component incidence matrix. Unlike the conventional approaches, this method decouples the overall decomposition process into two separate, autonomous function components: dependency analysis and matrix partitioning, which are algorithmically achieved by an extended Hierarchical Cluster Analysis (HCA) and a Partition Point Analysis (PPA), respectively. The extended HCA (Phase 1) is applied to convert the (input) incidence matrix, which is originally unorganized, into a banded diagonal matrix. The PPA (Phase 2) is applied to further transform this matrix into a block-angular matrix according to a given set of decomposition criteria. This method provides both flexibility in the choice of the different settings on the decomposition criteria, and diversity in the generation of the decomposition solutions, both taking place in Phase 2 without resort to Phase 1. These features essentially make this decomposition method effective, especially in its application to re-decomposition. A powertrain design example is employed for illustration and discussion.

scholarly journals Surveying vendors of street-vended food: a new methodology applied in two Guatemalan cities

1999 ◽  
Vol 122 (3) ◽  
pp. 409-416 ◽  
Author(s):  
B. E. MAHON ◽  
J. SOBEL ◽  
J. M. TOWNES ◽  
C. MENDOZA ◽  
M. GUDIEL LEMUS ◽  
...  
Keyword(s):  
Health Planning ◽  
Phase 1 ◽  
Water Storage ◽  
Reliable Data ◽  
Phase Method ◽  
Practical Training ◽  
Phase 2 ◽  
Two Phase ◽  
Street Vendors ◽  
New System

Lack of reliable data about street vendors, who are difficult to survey, has hampered efforts to improve the safety of street-vended food. A two-phase method for sampling vendors, surveying first in areas of concentrated vending activity identified by local authorities and second in randomly selected areas, was developed and implemented in two Guatemalan cities where street-vended food had been implicated in cholera transmission. In a 4-day survey in Escuintla, 59 vendors (42 from phase 1, 17 from phase 2) were interviewed. They demonstrated good knowledge of food safety and cholera but unsafe practices, implying that more effective, practical training was needed. In a 6-day survey in Guatemala City, 78 vendors (77 from phase 1, 1 from phase 2) were interviewed. Sixty-eight (87%) vendors stored water, usually in wide-mouthed vessels prone to contamination; this led to a field test of a new system for safe water storage. Useful information for public health planning and intervention can be gathered rapidly with this new method for surveying street vendors.

Extended Hierarchical Cluster Analysis for the Decomposition of Complex Design Problems

2003 ◽  
Author(s):  
Li Chen ◽  
Zhengdong Ding ◽  
Simon Li
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Decomposition Method ◽  
Block Size ◽  
Hierarchical Cluster ◽  
Function Parameter ◽  
Design Problems ◽  
Post Process ◽  
Complex Design ◽  
The Matrix

This paper presents a new decomposition method for partitioning complex design problems based on an extended Hierarchical Cluster Analysis (HCA). After a complex design problem is represented using a function-parameter incidence matrix, this new decomposition method allows transforming the originally unorganized matrix into a block-angular form matrix. By means of the resulting matrix, a coordination part and design blocks can be further identified and obtained. In particular, the extended HCA plays an important role in this method, contributive to aligning all non-zero elements, also known as 1s elements, of the matrix along its main diagonal as compactly as possible. As such, a post process, called Partition Point Analysis (PPA), can be further applied to the matrix to finally form the coordination part and the related design blocks, subject to such decomposition criteria as block size and coordination size limits. A powertrain design example is employed for illustration of the decomposition method newly developed.

Endometrial Adenocarcinoma in SurePath™ Cervical Samples: Cytological Features Revisited

2016 ◽  
Vol 60 (1) ◽  
pp. 46-52 ◽  
Author(s):  
Nalini Gupta ◽  
John Crossley ◽  
Nick Dudding ◽  
John H.F. Smith
Keyword(s):  
Phase 1 ◽  
Endometrial Adenocarcinoma ◽  
Nuclear Chromatin ◽  
Phase 2 ◽  
Cervical Lesions ◽  
Two Phase ◽  
Endometrial Cells ◽  
Phase Study ◽  
Cytological Features ◽  
Liquid Based Cytology

Objective: The cytomorphological criteria of malignant endometrial lesions in cervical samples are less well described than those of cervical lesions. We wished to investigate if there were features in SurePath™ liquid-based cytology samples that would facilitate more accurate differentiation between benign and malignant endometrial cells. Study Design: This was a two-phase study, with a review of all SurePath™ samples reported as endometrial adenocarcinoma (n = 42) evaluating 12 cytological features in the first phase. In phase 2 (test set), all initial cases plus an additional 83 cases were reviewed using these 12 cytological features to predict the outcome. Results: Out of 12 cytological features evaluated in phase 1 (training set), nuclear chromatin pattern, apoptotic bodies and tingible body macrophages were found to be the most significant features determining malignant histological outcome. These 12 cytological features were re-evaluated in phase 2 (n = 125). Of 125 cases, 54 had a benign and 71 had a malignant or premalignant histological outcome, with a positive predictive value of 56.8%. Conclusion: Granular nuclear chromatin, tingible body macrophages and apoptosis in the background are the most significant factors in determining whether endometrial cells present in cervical samples represent malignancy or are benign. Using these features, relatively accurate predictions of endometrial pathology can be made.

scholarly journals Developing a realist theory of psychosocial rehabilitation: the Clubhouse model

2021 ◽  
Author(s):  
Christina Mutschler ◽  
Jen Rouse ◽  
Kelly McShane ◽  
Criss Habal-Brosek
Keyword(s):  
Phase 1 ◽  
Psychosocial Rehabilitation ◽  
Theory Development ◽  
Realist Evaluation ◽  
Self Determination ◽  
Phase 2 ◽  
Two Phase ◽  
Realist Theory ◽  
Clubhouse Model ◽  
Two Phases

Background Psychosocial rehabilitation is a service that supports recovery from mental illness by providing opportunities for skill development, self-determination, and social interaction. One type of psychosocial rehabilitation is the Clubhouse model. The purpose of the current project was to create, test, and refine a realist theory of psychosocial rehabilitation at Progress Place, an accredited Clubhouse. Method Realist evaluation is a theory driven evaluation that uncovers contexts, mechanisms, and outcomes, in order to develop a theory as to how a program works. The current study involved two phases, encompassing four steps: Phase 1 included (1) initial theory development and (2) initial theory refinement; and Phase 2 included (3) theory testing and (4) refinement. Results The data from this two-phase approach identified three demi-regularities of recovery comprised of specific mechanisms and outcomes: the Restorative demi-regularity, the Reaffirming demi-regularity, and the Re-engaging demi-regularity. The theory derived from these demi-regularities suggests that there are various mechanisms that produce outcomes of recovery from the psychosocial rehabilitation perspective, and as such, it is necessary that programs promote a multifaceted, holistic perspective on recovery. Conclusions The realist evaluation identified that Progress Place promotes recovery for members. Additional research on the Clubhouse model should be conducted to further validate that the model initiates change and promotes recovery outcomes.

scholarly journals Whole system approaches to health in higher education

2019 ◽  
Vol 119 (4) ◽  
pp. 246-258
Author(s):  
Mark Dooris ◽  
Alan Farrier ◽  
Susan Powell ◽  
Maxine Holt
Keyword(s):  
Higher Education ◽  
Phase 1 ◽  
International Perspective ◽  
Phase 2 ◽  
Structured Interviews ◽  
Two Phase ◽  
Content Type ◽  
Key Issues ◽  
Strategic Influence ◽  
The Uk

Purpose The purpose of this paper is to report on an evaluation of the UK Healthy Universities Network (UKHUN), which explored engagement of network members; identified what members value about the network; examined facilitators and barriers to engagement; and informed the network’s future development. Design/methodology/approach The study was a two phase mixed-method study, with participants being staff from Higher Education institutions. Phase 1 involved a documentary review and an online 14-question survey (n=32). Phase 2 comprised follow-up semi-structured interviews and focus groups, conducted using Skype (n=11). These were audio recorded and transcripts were thematically analysed in a two-stage process. Findings A number of key themes emerged from the thematic analysis: value of network meetings and events; popularity of the network website; increased communication and collaboration; sense of leadership offered by the network; interest and inclusion of an international perspective; importance of institutional support. Research limitations/implications Only six universities who are involved in the network took part in Phase 2. Although a range of organisations were chosen purposively, it is possible that additional key issues at other universities were excluded. Originality/value The UKHUN is valued by its membership, particularly its biannual meetings, online presence, leadership, ethos and communication methods. Key barriers include the capacity of staff to attend meetings and contribute to the network, influenced by a lack of institutional commitment and prioritisation. Findings from the evaluation have informed a “refresh” of the network’s website and a revision of its membership structure, as well as guiding its positioning to achieve greater strategic influence.

A computationally fast approach to maximum‐likelihood deconvolution

Geophysics ◽  
1984 ◽  
Vol 49 (5) ◽  
pp. 550-565 ◽  
Author(s):  
Chong‐Yung Chi ◽  
Jerry M. Mendel ◽  
Dan Hampson
Keyword(s):  
Maximum Likelihood ◽  
Initial Conditions ◽  
Phase 1 ◽  
Real Data ◽  
Phase 2 ◽  
Statistical Parameters ◽  
Two Phase ◽  
Nonminimum Phase ◽  
Fast Approach ◽  
Fine Adjustment

In this paper we derive and implement a maximum‐likelihood deconvolution (MLD) algorithm, based on the same channel and statistical models used by Kormylo and Mendel (1983a), that leads to many fewer computations than their MLD algorithm. Both algorithms can simultaneously estimate a nonminimum phase wavelet and statistical parameters, detect locations of significant reflectors, and deconvolve the data. Our MLD algorithm is implemented by a two‐phase block component method (BCM). The phase‐1 block functions like a coarse adjustment of unknown quantities and provides a set of good initial conditions for the phase‐2 block, which functions like a fine adjustment of unknown quantities. We demonstrate good performance of our algorithm for both synthetic and real data.

scholarly journals Early Diagnostic Marker Panel Determination for Microarray Based Clinical Studies

2005 ◽  
Vol 4 (1) ◽  
Author(s):  
Jochen Jaeger ◽  
Dieter Weichenhan ◽  
Boris Ivandic ◽  
Rainer Spang
Keyword(s):  
Phase 1 ◽  
Classification Model ◽  
Marker Genes ◽  
Phase 2 ◽  
Two Phase ◽  
Marker Panel ◽  
Performance Loss ◽  
Genome Wide ◽  
Number Of Patients ◽  
Cost Efficient

We present a novel, cost efficient two-phase design for predictive clinical gene expression studies: early marker panel determination (EMPD). In Phase-1, genome-wide microarrays are used only for a small number of individual patient samples. From this Phase-1 data a panel of marker genes is derived. In Phase-2, the expression values of these marker panel genes are measured for a large group of patients and a predictive classification model is learned from this data. Phase-2 does not require the use of expensive whole genome microarrays, thus making EMPD a cost efficient alternative for current trials. The expected performance loss of EMPD is compared to designs which use genome-wide microarrays for all patients. We also examine the trade-off between the number of patients included in Phase-1 and the number of marker genes required in Phase-2. By analysis of five published datasets we find that in Phase-1 already 16 patients per group are sufficient to determine a suitable marker panel of 10 genes, and that this early decision compromises the final performance only marginally.

scholarly journals Stem cell factor amplifies newborn and sickle erythropoiesis in liquid cultures

Blood ◽  
1993 ◽  
Vol 81 (10) ◽  
pp. 2591-2599 ◽  
Author(s):  
RS Weinberg ◽  
JC Thomson ◽  
R Lao ◽  
G Chen ◽  
BP Alter
Keyword(s):  
Stem Cell ◽  
Progenitor Cells ◽  
Stem Cell Factor ◽  
Mononuclear Cells ◽  
Phase 1 ◽  
Newborn Infants ◽  
Cell Number ◽  
Phase 2 ◽  
Two Phase ◽  
Erythroid Progenitor

A two-phase liquid-culture system was used to substantially amplify and differentiate erythroblasts, starting with mononuclear cells from the blood of normal adults, newborn infants, and patients with sickle cell anemia. After the first 7 days (phase 1), in medium plus fetal bovine serum (FBS) alone, or in combination with stem cell factor (SCF) or conditioned medium (CM), the cell number was unchanged, and the cells all looked like lymphocytes. These cells were then diluted into medium with erythropoietin (Ep) alone, with Ep and either SCF or CM, or in methylcellulose with the same factors (phase 2). After 14 days in liquid phase 2 with SCF and Ep, the cell numbers increased an average of 30-fold in the sickle, 24-fold in the newborn, and 4-fold in the normal adult cultures; almost all the cells were erythroblasts and erythrocytes. SCF in phase 1 increased the number of late progenitors (CFU-E) assayed in methylcellulose, with the largest number in sickle, followed by newborn cultures and then adult cultures. We conclude that erythroid progenitor cells survive for at least 7 days without Ep (but with FBS). Progenitor cells are amplified, particularly with SCF. Later in culture, SCF with Ep increases the final number of differentiated erythroid cells. Both the early and the late effects of SCF are most effective in sickle, followed by newborn cultures and then adult cultures.

scholarly journals Enhancing Label Representations with Relational Inductive Bias Constraint for Fine-Grained Entity Typing

2021 ◽  
Author(s):  
Jinqing Li ◽  
Xiaojun Chen ◽  
Dakui Wang ◽  
Yuwei Li
Keyword(s):  
State Of The Art ◽  
Phase 1 ◽  
Phase 2 ◽  
Two Phase ◽  
Inductive Bias ◽  
Fine Grained ◽  
Wide Range ◽  
Dynamic Experiments ◽  
Novel Method ◽  
Public Datasets

Fine-Grained Entity Typing (FGET) is a task that aims at classifying an entity mention into a wide range of entity label types. Recent researches improve the task performance by imposing the label-relational inductive bias based on the hierarchy of labels or label co-occurrence graph. However, they usually overlook explicit interactions between instances and labels which may limit the capability of label representations. Therefore, we propose a novel method based on a two-phase graph network for the FGET task to enhance the label representations, via imposing the relational inductive biases of instance-to-label and label-to-label. In the phase 1, instance features will be introduced into label representations to make the label representations more representative. In the phase 2, interactions of labels will capture dependency relationships among them thus make label representations more smooth. During prediction, we introduce a pseudo-label generator for the construction of the two-phase graph. The input instances differ from batch to batch so that the label representations are dynamic. Experiments on three public datasets verify the effectiveness and stability of our proposed method and achieve state-of-the-art results on their testing sets.

Sample study protocol for adapting and/or translating the 5C scale to assess the psychological antecedents of vaccination

2019 ◽  
Author(s):  
Cornelia Betsch ◽  
Katrine Habersaat ◽  
Sergei Deshevoi ◽  
Dorothee K. Heinemeier ◽  
Natalia Kostenko ◽  
...  
Keyword(s):  
Study Protocol ◽  
Cultural Context ◽  
Phase 1 ◽  
Collective Responsibility ◽  
Phase 2 ◽  
Two Phase ◽  
Cultural Setting ◽  
Original Group ◽  
Vaccination Confidence ◽  
Item Scale

Background: Published in 2018, the 5C scale is psychometrically validated to assess five psychological antecedents of vaccination (confidence, complacency, constraints, calculation, and collective responsibility). The original version offers a validated English and German scale to assess these determinants with a short 5-item scale (1 item per antecedent) and a long 15-item scale (3-items per antecedent). As the original group of authors has received several requests about how to adapt the scale to another country, language, or cultural context, this sample study protocol provides guidance for this process. Here, we propose a two-phase process of how to adapt the 5C scale to a new country, language, or cultural setting. Methods: Phase 1 comprises the translation and the adaptation to a specific cultural context (if necessary). Phase 2 involves the validation of the translated and potentially expanded scale. Discussion: Following the suggested study protocol will allow better comparability across the data obtained from the scale when used in different countries, languages, and contexts—even if slight changes in the wording of the items are necessary. The data obtained from the 5C scale allows monitoring the antecedents of vaccination, and detecting potentially early warning signals. Consequently, data obtained from the 5C scale can support developing, implementing, and evaluating an intervention. The materials and the syntax for data analysis to support the process described in this protocol are available in https://osf.io/2agxe/.

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