scholarly journals Some statistical inferences regarding population diversity in terms of the hypoentropy measure

1991 ◽  
Vol 6 (2) ◽  
pp. 55-65 ◽  
Author(s):  
D. Morales ◽  
I. J. Taneja ◽  
L. Pardo
Keyword(s):  
Population Diversity ◽  
Statistical Inferences

Business Incubation in Uganda, Services, Processes and Incubatee Perceptions- A case study

10.33117/514 ◽  
2017 ◽  
Vol 13 (1) ◽  
pp. 94-108
Keyword(s):  
Social Enterprise ◽  
Single Case ◽  
Business Incubation ◽  
Entrepreneurial Networks ◽  
Private Sector Development ◽  
Statistical Inferences ◽  
Office Space ◽  
Interview Methods ◽  
Entrepreneurial Training

Purpose-This paper examines the nature of services and processes of business incubation. Its specific objectives are to establish the nature of services offered by business incubation centers in Uganda, examine the incubation process and to establish the perception of business incu- batees about business incubation services using a case of FinAfrica a private social enterprise. Methodology-This paper presents findings from one incubation center FinAfrica as a case study. Ethnographic design is adopted while observation and interview methods are used to collect data. Results-Key services offered by FinAfrica incubation center include entrepreneurial training, provision of office space, legal and accounting services, mentoring, coaching, entrepreneurial networks and general office administration. The centre has a unique business incubation model which starts with motivating people to start businesses, capacity building, business registration, and ends with graduation after attaining capability for self-sustainability. Incubatees perceive the services offered by the incubation centre as helpful through training, affordable office space, entrepreneurial ecosystem and opportunities for a lean startup. Implications- While this study does not offer statistical inferences for generalisation because of the qualitative design and single case, the exploration of FinAfrica provides insights about how Incubation centers need to plan for positive and sustainable entrepreneurial impact for startups. There is need for more Government and other development partners’ involvement in business incubation and post incubation support for competiveness and growth. Originality/value- This study provides insights about the key services offered in the incubation process and provides insights into the perceived benefits of business incubation. It also contributes to literature about business incubation with practical evidence from an emerging economy whose focus is on private sector development and innovation promotion.

Genetic Population Diversity of Aedes caspius in Southern Provinces of Iran

2018 ◽  
Vol 111 (1) ◽  
pp. 31-37 ◽  
Author(s):  
S DOOSTI ◽  
MR YAGHOOBI-ERSHADI ◽  
MM SEDAGHAT ◽  
SH MOOSA-KAZEMI ◽  
K AKBARZADEH ◽  
...  
Keyword(s):  
Population Diversity ◽  
Genetic Population ◽  
Aedes Caspius

AO-BBO: A Novel Optimization Algorithm and Its Application in Plant Drug Extraction

2019 ◽  
Vol 19 (2) ◽  
pp. 139-145 ◽  
Author(s):  
Bote Lv ◽  
Juan Chen ◽  
Boyan Liu ◽  
Cuiying Dong
Keyword(s):  
Optimization Algorithm ◽  
Learning Strategy ◽  
Optimal Solution ◽  
Population Diversity ◽  
Global Optimal Solution ◽  
Plant Medicine ◽  
Suitability Index ◽  
Sensing Model ◽  
Local Optimal Solution ◽  
Global Optimal

<P>Introduction: It is well-known that the biogeography-based optimization (BBO) algorithm lacks searching power in some circumstances. </P><P> Material & Methods: In order to address this issue, an adaptive opposition-based biogeography-based optimization algorithm (AO-BBO) is proposed. Based on the BBO algorithm and opposite learning strategy, this algorithm chooses different opposite learning probabilities for each individual according to the habitat suitability index (HSI), so as to avoid elite individuals from returning to local optimal solution. Meanwhile, the proposed method is tested in 9 benchmark functions respectively. </P><P> Result: The results show that the improved AO-BBO algorithm can improve the population diversity better and enhance the search ability of the global optimal solution. The global exploration capability, convergence rate and convergence accuracy have been significantly improved. Eventually, the algorithm is applied to the parameter optimization of soft-sensing model in plant medicine extraction rate. Conclusion: The simulation results show that the model obtained by this method has higher prediction accuracy and generalization ability.</P>

Variant origin of Common Interosseous Artery from Brachial Artery

2017 ◽  
Vol 2 (3) ◽  
Author(s):  
Pralhad D. Subbannavar
Keyword(s):  
Brachial Artery ◽  
The Body ◽  
Dead Body ◽  
Invasive Procedures ◽  
Arterial Variations ◽  
Statistical Inferences ◽  
Individual Variations ◽  
Interosseous Artery ◽  
Cubital Fossa ◽  
Dissection Techniques

Acharya Sushruta has emphasized the method and importance of dissection to study anatomy practically. Perfect knowledge of anatomy is vital for practicing surgeons and hence the training of dissecting the dead body was considered as mandatory for surgeons. Though dissection techniques may give the perception of the structure of organs, the pervading and subtle consciousness in the body can be experienced with the eyes of knowledge and penance only. Though the standard anatomy is defined based on statistical inferences on comparing large number of subjects, individual variations and exceptional structural specialties tend to occur quite frequently. Proper recording and publication of such instances would strengthen the knowledge base of the science. Knowledge regarding arterial variations of upper limb is important for surgeons and orthopedicians as they are commonly involved in invasive procedures. We report a case ofvariant origin of right common interosseous artery from brachial artery in cubital fossa. It followed a normal course after the origin.

scholarly journals Standardizing human brain parcellations

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ross M. Lawrence ◽  
Eric W. Bridgeford ◽  
Patrick E. Myers ◽  
Ganesh C. Arvapalli ◽  
Sandhya C. Ramachandran ◽  
...  
Keyword(s):  
Human Brain ◽  
Coordinate Space ◽  
The Past ◽  
File Storage ◽  
Statistical Inferences ◽  
Standardized Protocol ◽  
Storage Format ◽  
Labeling Scheme ◽  
Selection Of ◽  
Brain Atlases

AbstractUsing brain atlases to localize regions of interest is a requirement for making neuroscientifically valid statistical inferences. These atlases, represented in volumetric or surface coordinate spaces, can describe brain topology from a variety of perspectives. Although many human brain atlases have circulated the field over the past fifty years, limited effort has been devoted to their standardization. Standardization can facilitate consistency and transparency with respect to orientation, resolution, labeling scheme, file storage format, and coordinate space designation. Our group has worked to consolidate an extensive selection of popular human brain atlases into a single, curated, open-source library, where they are stored following a standardized protocol with accompanying metadata, which can serve as the basis for future atlases. The repository containing the atlases, the specification, as well as relevant transformation functions is available in the neuroparc OSF registered repository or https://github.com/neurodata/neuroparc.

scholarly journals Knowledge-guided multiobjective particle swarm optimization with fusion learning strategies

2021 ◽  
Author(s):  
Wei Li ◽  
Xiang Meng ◽  
Ying Huang ◽  
Soroosh Mahmoodi
Keyword(s):  
Particle Swarm Optimization ◽  
Learning Strategies ◽  
Learning Strategy ◽  
Particle Swarm ◽  
Population Diversity ◽  
Selection Strategy ◽  
Rapid Loss ◽  
Solution Quality ◽  
Swarm Optimization ◽  
Multiobjective Particle Swarm Optimization

AbstractMultiobjective particle swarm optimization (MOPSO) algorithm faces the difficulty of prematurity and insufficient diversity due to the selection of inappropriate leaders and inefficient evolution strategies. Therefore, to circumvent the rapid loss of population diversity and premature convergence in MOPSO, this paper proposes a knowledge-guided multiobjective particle swarm optimization using fusion learning strategies (KGMOPSO), in which an improved leadership selection strategy based on knowledge utilization is presented to select the appropriate global leader for improving the convergence ability of the algorithm. Furthermore, the similarity between different individuals is dynamically measured to detect the diversity of the current population, and a diversity-enhanced learning strategy is proposed to prevent the rapid loss of population diversity. Additionally, a maximum and minimum crowding distance strategy is employed to obtain excellent nondominated solutions. The proposed KGMOPSO algorithm is evaluated by comparisons with the existing state-of-the-art multiobjective optimization algorithms on the ZDT and DTLZ test instances. Experimental results illustrate that KGMOPSO is superior to other multiobjective algorithms with regard to solution quality and diversity maintenance.

scholarly journals An Improved Whale Optimization Algorithm for the Traveling Salesman Problem

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 48
Author(s):  
Jin Zhang ◽  
Li Hong ◽  
Qing Liu
Keyword(s):  
Traveling Salesman Problem ◽  
Optimization Algorithm ◽  
Optimization Problems ◽  
Relevant Literature ◽  
Population Diversity ◽  
Traveling Salesman ◽  
Whale Optimization Algorithm ◽  
Neighborhood Search ◽  
Whale Optimization ◽  
The Traveling Salesman Problem

The whale optimization algorithm is a new type of swarm intelligence bionic optimization algorithm, which has achieved good optimization results in solving continuous optimization problems. However, it has less application in discrete optimization problems. A variable neighborhood discrete whale optimization algorithm for the traveling salesman problem (TSP) is studied in this paper. The discrete code is designed first, and then the adaptive weight, Gaussian disturbance, and variable neighborhood search strategy are introduced, so that the population diversity and the global search ability of the algorithm are improved. The proposed algorithm is tested by 12 classic problems of the Traveling Salesman Problem Library (TSPLIB). Experiment results show that the proposed algorithm has better optimization performance and higher efficiency compared with other popular algorithms and relevant literature.

scholarly journals A New Class of Estimators Based on a General Relative Loss Function

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1138
Author(s):  
Tao Hu ◽  
Baosheng Liang
Keyword(s):  
Loss Function ◽  
Asymptotically Normal ◽  
New Class ◽  
Statistical Inferences ◽  
Relative Loss ◽  
Special Cases ◽  
Class Of Estimators ◽  
Box Cox Transformation ◽  
Loss Estimator ◽  
Prostate Cancer Study

Motivated by the relative loss estimator of the median, we propose a new class of estimators for linear quantile models using a general relative loss function defined by the Box–Cox transformation function. The proposed method is very flexible. It includes a traditional quantile regression and median regression under the relative loss as special cases. Compared to the traditional linear quantile estimator, the proposed estimator has smaller variance and hence is more efficient in making statistical inferences. We show that, in theory, the proposed estimator is consistent and asymptotically normal under appropriate conditions. Extensive simulation studies were conducted, demonstrating good performance of the proposed method. An application of the proposed method in a prostate cancer study is provided.

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