scholarly journals Review on automated follicle identification for polycystic ovarian syndrome

2020 ◽  
Vol 9 (2) ◽  
Author(s):  
A A Nazarudin ◽  
Noraishikin Zulkarnain ◽  
A. Hussain ◽  
S. S. Mokri ◽  
I. N. A. M. Nordin
Keyword(s):  
Performance Evaluation ◽  
Ultrasound Imaging ◽  
Polycystic Ovarian Syndrome ◽  
Speckle Noise ◽  
Future Research ◽  
Health Treatment ◽  
Time Consumption ◽  
Non Invasive ◽  
And Performance ◽  
Ovarian Syndrome

Polycystic Ovarian Syndrome (PCOS), is a condition of the ovary consisting numerous follicles. Accurate size and number of follicles detected are crucial for treatment. Hence the diagnosis of this condition is by measuring and calculating the size and number of follicles existed in the ovary. For diagnosis, ultrasound imaging has become an effective tool as it is non-invasive, inexpensive and portable. However, the presence of speckle noise in ultrasound imaging has caused an obstruction for manual diagnosis which are high time consumption and often produce errors. Thus, image segmentation for ultrasound imaging is critical to identify follicles for PCOS diagnosis and proper health treatment. This paper presents different methods proposed and applied in automated follicle identification for PCOS diagnosis by previous researchers. In this paper, the methods and performance evaluation are identified and compared. Finally, this paper also provided suggestions in developing methods for future research.

scholarly journals Metabolomics Biomarkers for Detection of Colorectal Neoplasms: A Systematic Review

Cancers ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 246 ◽  
Author(s):  
Vanessa Erben ◽  
Megha Bhardwaj ◽  
Petra Schrotz-King ◽  
Hermann Brenner
Keyword(s):  
Early Detection ◽  
Colorectal Neoplasms ◽  
Literature Search ◽  
Web Of Science ◽  
Current Knowledge ◽  
External Validation ◽  
Performance Characteristics ◽  
Future Research ◽  
Non Invasive ◽  
And Performance

Background: Several approaches have been suggested to be useful in the early detection of colorectal neoplasms. Since metabolites are closely related to the phenotype and are available from different human bio-fluids, metabolomics are candidates for non-invasive early detection of colorectal neoplasms. Objectives: We aimed to summarize current knowledge on performance characteristics of metabolomics biomarkers that are potentially applicable in a screening setting for the early detection of colorectal neoplasms. Design: We conducted a systematic literature search in PubMed and Web of Science and searched for biomarkers for the early detection of colorectal neoplasms in easy-to-collect human bio-fluids. Information on study design and performance characteristics for diagnostic accuracy was extracted. Results: Finally, we included 41 studies in our analysis investigating biomarkers in different bio-fluids (blood, urine, and feces). Although single metabolites mostly had limited ability to distinguish people with and without colorectal neoplasms, promising results were reported for metabolite panels, especially amino acid panels in blood samples, as well as nucleosides in urine samples in several studies. However, validation of the results is limited. Conclusions: Panels of metabolites consisting of amino acids in blood and nucleosides in urinary samples might be useful biomarkers for early detection of advanced colorectal neoplasms. However, to make metabolomic biomarkers clinically applicable, future research in larger studies and external validation of the results is required.

scholarly journals 6 Polycystic ovarian syndrome in adolescents: discovery proteomics and the search for novel non-invasive biomarkers

2019 ◽  
Author(s):  
HM Gunn ◽  
VS Forsyth ◽  
J Hällqvist ◽  
R Viner ◽  
K Mills ◽  
...  
Keyword(s):  
Polycystic Ovarian Syndrome ◽  
Non Invasive ◽  
Ovarian Syndrome

scholarly journals OC45 Polycystic ovarian syndrome in adolescents: utilising discovery proteomics to identify novel non-invasive biomarkers

2019 ◽  
Author(s):  
Harriet Gunn ◽  
Vhari Forsyth ◽  
Russell Viner ◽  
Kevin Mills ◽  
Katharine Steinbeck
Keyword(s):  
Polycystic Ovarian Syndrome ◽  
Non Invasive ◽  
Ovarian Syndrome

Structure, mechanism, and performance evaluation of natural gas hydrate kinetic inhibitors

2018 ◽  
Vol 38 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Sheida Shahnazar ◽  
Samira Bagheri ◽  
Amin TermehYousefi ◽  
Javad Mehrmashhadi ◽  
Mohd Sayuti Abd Karim ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Gas Hydrates ◽  
Oil And Gas ◽  
Future Research ◽  
Water Molecules ◽  
Natural Gas Hydrate ◽  
The Past ◽  
Thermodynamic Conditions ◽  
Gas Molecules ◽  
And Performance

AbstractIce-like crystal compounds, which are formed in low-temperature and high-pressure thermodynamic conditions and composed of a combination of water molecules and guest gas molecules, are called gas hydrates. Since its discovery and recognition as the responsible component for blockage of oil and gas transformation line, hydrate has been under extensive review by scientists. In particular, the inhibition techniques of hydrate crystals have been updated in order to reach the more economically and practically feasible methods. So far, kinetic hydrate inhibition has been considered as one of the most effective techniques over the past decade. This review is intended to classify the recent studies regarding kinetic hydrate inhibitors, their structure, mechanism, and techniques for their performance evaluation. In addition, this communication further analyzes the areas that are more in demand to be considered in future research.

scholarly journals Convolutional-Neural Network-Based Image Crowd Counting: Review, Categorization, Analysis, and Performance Evaluation

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 43 ◽  
Author(s):  
Naveed Ilyas ◽  
Ahsan Shahzad ◽  
Kiseon Kim
Keyword(s):  
Neural Network ◽  
Performance Evaluation ◽  
Convolutional Neural Network ◽  
Smart Cities ◽  
Future Research ◽  
Crowd Counting ◽  
Crowd Management ◽  
Adaptive Monitoring ◽  
Potential Applications ◽  
And Performance

Traditional handcrafted crowd-counting techniques in an image are currently transformed via machine-learning and artificial-intelligence techniques into intelligent crowd-counting techniques. This paradigm shift offers many advanced features in terms of adaptive monitoring and the control of dynamic crowd gatherings. Adaptive monitoring, identification/recognition, and the management of diverse crowd gatherings can improve many crowd-management-related tasks in terms of efficiency, capacity, reliability, and safety. Despite many challenges, such as occlusion, clutter, and irregular object distribution and nonuniform object scale, convolutional neural networks are a promising technology for intelligent image crowd counting and analysis. In this article, we review, categorize, analyze (limitations and distinctive features), and provide a detailed performance evaluation of the latest convolutional-neural-network-based crowd-counting techniques. We also highlight the potential applications of convolutional-neural-network-based crowd-counting techniques. Finally, we conclude this article by presenting our key observations, providing strong foundation for future research directions while designing convolutional-neural-network-based crowd-counting techniques. Further, the article discusses new advancements toward understanding crowd counting in smart cities using the Internet of Things (IoT).

scholarly journals Decision making and performance of Malaysian rugby sevens referees

2015 ◽  
Vol 4 ◽  
Author(s):  
Mohamad Nizam
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Significant Relationship ◽  
Field Performance ◽  
Rugby Union ◽  
Future Research ◽  
Experience Level ◽  
Research Findings ◽  
And Performance ◽  
One Way Anova

<p>This study aims to examine the decision making by rugby sevens referees, and its relationship with the referees’ performance. The instruments used in this study are the Rugby Referee Decision Making Test (α=.74) and the Referee Sevens Field Performance Evaluation (α=.94). It was administered to 132 rugby sevens referees (mean age 33.4 + 1.5 years; 132 males) from the Malaysian Rugby Union (MRU), which have been refereeing in 10 rugby sevens tournaments in Malaysia. Descriptive and Inferential statistics (one way ANOVA and Pearson’s Correlation) were employed to analyse the data. Decision Making ( = 24.13, SD= 5.24) and performance ( = 136.45, SD = 4.47) were identified at a moderate level. The findings indicated no significant differences [F= (3, 128) =.246, p&gt;0.05] in the decision making across age level, but there were significant differences [F= (3, 128) =63.159, p&lt;0.05] across experience level. Highly experienced referees scored significantly higher in all decision making constructs compared to less experienced referees. The research findings have revealed a positive and significant relationship between decision making (r= .61, p&lt;.05) and referee performance. In conclusion, the decision making can help rugby sevens referees’ performance, and it is recommended that referees should increase<strong> </strong>the use of decision making in future<strong> </strong>training and assessment. Future research should investigate the effectiveness of decision making interventions in enhancing referees’ performance in the future.</p>

Endocrinology: Transvaginal ultrasound imaging, histopathology and endocrinopathy in patients with polycystic ovarian syndrome

1994 ◽  
Vol 9 (7) ◽  
pp. 1231-1236 ◽  
Author(s):  
Kentaro Takahashi ◽  
Yoshimi Eda ◽  
Antoine Abu-Musa ◽  
Saori Okada ◽  
Kazuo Yoshino ◽  
...  
Keyword(s):  
Ultrasound Imaging ◽  
Polycystic Ovarian Syndrome ◽  
Transvaginal Ultrasound ◽  
Ovarian Syndrome

scholarly journals Quantitative Analysis and Performance Evaluation of Target-Oriented Replication Strategies in Cloud Computing

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 672
Author(s):  
Quadri Waseem ◽  
Wan Isni Sofiah Wan Din ◽  
Sultan S. Alshamrani ◽  
Abdullah Alharbi ◽  
Amril Nazir
Keyword(s):  
Cloud Computing ◽  
Performance Evaluation ◽  
Quantitative Analysis ◽  
Performance Indicator ◽  
Data Replication ◽  
Future Research ◽  
Dynamic Data ◽  
Advantages And Disadvantages ◽  
Dynamic Data Replication ◽  
And Performance

Data replications effectively replicate the same data to various multiple locations to accomplish the objective of zero loss of information in case of failures without any downtown. Dynamic data replication strategies (providing run time location of replicas) in clouds should optimize the key performance indicator parameters, like response time, reliability, availability, scalability, cost, availability, performance, etc. To fulfill these objectives, various state-of-the-art dynamic data replication strategies has been proposed, based on several criteria and reported in the literature along with advantages and disadvantages. This paper provides a quantitative analysis and performance evaluation of target-oriented replication strategies based on target objectives. In this paper, we will try to find out which target objective is most addressed, which are average addressed, and which are least addressed in target-oriented replication strategies. The paper also includes a detailed discussion about the challenges, issues, and future research directions. This comprehensive analysis and performance evaluation based-work will open a new door for researchers in the field of cloud computing and will be helpful for further development of cloud-based dynamic data replication strategies to develop a technique that will address all attributes (Target Objectives) effectively in one replication strategy.

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