scholarly journals Evaluation and Validation of a Semiautomatic Image Analysis Method: Quantification of Nares Cell Proliferation of Rhinella arenarum (Anura) Detected with the Avidin-Biotin Complex/Peroxidase, DAB

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Javier Eduardo Diaz Zamboni ◽  
Daniela Osella ◽  
Enrique Valentín Paravani ◽  
Víctor Hugo Casco
Keyword(s):  
Gold Standard ◽  
Visual Analysis ◽  
Methodological Approach ◽  
Image Features ◽  
Analysis Method ◽  
New Approach ◽  
Image Characteristics ◽  
Microscopy Image ◽  
Computer Based ◽  
Current Report

The current report presents the development and application of a novel methodological approach for computer-based methods of processing and analysis of proliferative tissues labeled by ABC-peroxidase method using 3, 3′-diaminobenzidine (DAB) as chromogen. This semiautomatic method is proposed to replace the classical manual approach, widely accepted as gold standard. Our method is based on a visual analysis of the microscopy image features from which a computational model is built to generate synthetic images which are used to evaluate and validate the methods of image processing and analysis. The evaluation allows knowing whether the computational methods applied are affected by the change of the image characteristics. Validation allows determining the method’s reliability and analyzing the concordance between the proposed method and a gold standard one. Additional strongness of this new approach is that it may be a framework adaptable to other studies made on any kind of microscopy.

scholarly journals Tumor imaging diagnosis analysis based on improved KNN algorithm

2021 ◽  
Vol 2132 (1) ◽  
pp. 012018
Author(s):  
Cailing Wang ◽  
LeiChao Li ◽  
SuQiang He ◽  
Jing Zhang
Keyword(s):  
Tumor Imaging ◽  
Image Features ◽  
Parameter Analysis ◽  
Analysis Method ◽  
Abnormality Detection ◽  
Practical Applications ◽  
Classification Image ◽  
Image Characteristics ◽  
Training Samples

Abstract As a simple, effective and non-parameter analysis method, knn is widely used in text classification, image recognition, etc. [1]. However, this method requires a lot of calculations in practical applications, and the uneven distribution of training samples will directly lead to a decrease in the accuracy of tumor image classification. To solve this problem, we propose a method based on dynamic weighted KNN to improve the accuracy of classification, which is used to solve the problem of automatic prediction and classification of medical tumor images based on image features and automatic abnormality detection. According to the classification of tumor image characteristics, it can be divided into two categories: benign and malignant. This method can assist doctors in making medical diagnosis and analysis more accurately. The experimental results show that this method has certain advantages compared with the traditional KNN algorithm.

Scientific-methodological approach to the substantiation of the rational seasonal scenario of using combine harvesters by large-scale agricultural producers

2020 ◽  
pp. 205-217
Author(s):  
V. Skibchyk ◽  
V. Dnes ◽  
R. Kudrynetskyi ◽  
O. Krypuch
Keyword(s):  
Large Scale ◽  
System Analysis ◽  
Methodological Approach ◽  
Production Unit ◽  
Agricultural Producers ◽  
New Approach ◽  
Rational Use ◽  
Road Map ◽  
Analysis And Synthesis ◽  
Combine Harvesters

Аnnotation Purpose. To increase the efficiency of technological processes of grain harvesting by large-scale agricultural producers due to the rational use of combine harvesters available on the farm. Methods. In the course of the research the methods of system analysis and synthesis, induction and deduction, system-factor and system-event approaches, graphic method were used. Results. Characteristic events that occur during the harvesting of grain crops, both within a single production unit and the entire agricultural producer are identified. A method for predicting time intervals of use and downtime of combine harvesters of production units has been developed. The roadmap of substantiation the rational seasonal scenario of the use of grain harvesters of large-scale agricultural producers is developed, which allows estimating the efficiency of each of the scenarios of multivariate placement of grain harvesters on fields taking into account influence of natural production and agrometeorological factors on the efficiency of technological cultures. Conclusions 1. Known scientific and methodological approaches to optimization of machine used in agriculture do not take into account the risks of losses of crops due to late harvesting, as well as seasonal natural and agrometeorological conditions of each production unit of the farmer, which requires a new approach to the rational use of rational seasonal combines of large agricultural producers. 2. The developed new approach to the substantiation of the rational seasonal scenario of the use of combined harvesters of large-scale agricultural producers allows taking into account the costs of harvesting of grain and the cost of the lost crop because of the lateness of harvesting at optimum variants of attraction of additional free combine harvesters. provides more profit. 3. The practical application of the developed road map will allow large-scale agricultural producers to use combine harvesters more efficiently and reduce harvesting costs. Keywords: combine harvesters, use, production divisions, risk, seasonal scenario, large-scale agricultural producers.

scholarly journals A Bibliometric and Visual Analysis of Rural Development Research

2021 ◽  
Vol 13 (11) ◽  
pp. 6136
Author(s):  
Ying Lu ◽  
Walter Timo de Vries
Keyword(s):  
Rural Development ◽  
Visual Analysis ◽  
Empirical Studies ◽  
Development Research ◽  
Knowledge Domains ◽  
Research Fields ◽  
Literature Reviews ◽  
Collection Data ◽  
Computer Based ◽  
Changing Knowledge

Rural development research integrates numerous theoretical and empirical studies and has evolved over the past few decades. However, few systematic literature reviews have explored the changing landscape. This study aims to obtain an overview of rural development research by applying a bibliometric and visual analysis. In this paper, we introduce four computer-based software tools, including HistCite™, CiteSpace, VOSviewer, and Map and Alluvial Generator, to help with data collection, data analysis, and visualization. The dataset consists of 6968 articles of rural development research, which were downloaded from the database Web of Science. The period covers 1957 to 2020 and the analysis units include journals, categories, authors, references, and keywords. Co-occurrence and co-citation analysis are conducted, and the results are exported in the format of networks. We analyze the trends of publications and explore the discipline distribution and identify the most influential authors and articles at different times. The results show that this field of study has attracted progressively more scholars from a variety of research fields and has become multidisciplinary and interdisciplinary. The changing knowledge domains of rural development research also reflect the dynamics and complexity of rural contexts.

ASSESSMENT OF OSTEOARTHRITIS INITIATIVE–KELLGREN AND LAWRENCE SCORING PROJECTS QUALITY USING COMPUTER ANALYSIS

2010 ◽  
Vol 13 (04) ◽  
pp. 197-201 ◽  
Author(s):  
Lior Shamir ◽  
David T. Felson ◽  
Luigi Ferrucci ◽  
Ilya G. Goldberg
Keyword(s):  
Image Analysis ◽  
Gold Standard ◽  
Population Studies ◽  
Detection Accuracy ◽  
X Rays ◽  
Analysis Method ◽  
Image Analysis Method ◽  
X Ray ◽  
Osteoarthritis Initiative ◽  
Kellgren And Lawrence

The detection of knee osteoarthritis (OA) is a subjective task, and even two highly experienced and well-trained readers might not always agree on a specific case. This problem is noticeable in OA population studies, in which different scoring projects provide significantly different scores for the same knee X-rays. Here we propose a method for quantitative assessment and comparison of knee X-ray scoring projects in OA population studies. The method works by applying an image analysis method that automatically detects OA in knee X-ray images, and comparing the consistency of the scores when using each of the scoring projects as "gold standard." The method was applied to compare the osteoarthritis initiative (OAI) clinic reading derived Kellgren and Lawrence (K&L) scores to central reading, and showed that when using the derived K&L scores the automatic image analysis method was able to accurately differentiate between healthy joints and moderate OA joints in ~70% of the cases. When the OAI central reading scores were used as gold standard, the detection accuracy was elevated to ~77%. These results show that the OAI central readings scores are more consistent with the X-rays, indicating that the central reading better reflects the radiographic features associated with OA, compared to the OAI K&L scores derived from clinic readings.

scholarly journals Reliability and Validity of Composite Scores from the NIH Toolbox Cognition Battery in Adults

2014 ◽  
Vol 20 (6) ◽  
pp. 588-598 ◽  
Author(s):  
Robert K. Heaton ◽  
Natacha Akshoomoff ◽  
David Tulsky ◽  
Dan Mungas ◽  
Sandra Weintraub ◽  
...  
Keyword(s):  
Cognitive Abilities ◽  
Gold Standard ◽  
Reliability And Validity ◽  
Epidemiologic Studies ◽  
Memory Processing ◽  
Significant Relationships ◽  
Gender Education ◽  
Computer Based ◽  
Composite Scores ◽  
Test Retest Reliability

AbstractThis study describes psychometric properties of the NIH Toolbox Cognition Battery (NIHTB-CB) Composite Scores in an adult sample. The NIHTB-CB was designed for use in epidemiologic studies and clinical trials for ages 3 to 85. A total of 268 self-described healthy adults were recruited at four university-based sites, using stratified sampling guidelines to target demographic variability for age (20–85 years), gender, education, and ethnicity. The NIHTB-CB contains seven computer-based instruments assessing five cognitive sub-domains: Language, Executive Function, Episodic Memory, Processing Speed, and Working Memory. Participants completed the NIHTB-CB, corresponding gold standard validation measures selected to tap the same cognitive abilities, and sociodemographic questionnaires. Three Composite Scores were derived for both the NIHTB-CB and gold standard batteries: “Crystallized Cognition Composite,” “Fluid Cognition Composite,” and “Total Cognition Composite” scores. NIHTB Composite Scores showed acceptable internal consistency (Cronbach’s alphas=0.84 Crystallized, 0.83 Fluid, 0.77 Total), excellent test–retest reliability (r: 0.86–0.92), strong convergent (r: 0.78–0.90) and discriminant (r: 0.19–0.39) validities versus gold standard composites, and expected age effects (r=0.18 crystallized, r=−0.68 fluid, r=−0.26 total). Significant relationships with self-reported prior school difficulties and current health status, employment, and presence of a disability provided evidence of external validity. The NIH Toolbox Cognition Battery Composite Scores have excellent reliability and validity, suggesting they can be used effectively in epidemiologic and clinical studies. (JINS, 2014, 20, 1–11)

APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN MS. PAC-MAN GAME: A REVIEW

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Tse Guan Tan ◽  
Jason Teo
Keyword(s):  
Artificial Intelligence ◽  
Content Analysis ◽  
Video Games ◽  
Analysis Method ◽  
Engineering Economics ◽  
Game Ai ◽  
Content Analysis Method ◽  
Wide Range ◽  
Computer Based ◽  
Future Direction

AbstrakTeknik Kecerdasan Buatan (AI) berjaya digunakan dan diaplikasikan dalam pelbagai bidang, termasukpembuatan, kejuruteraan, ekonomi, perubatan dan ketenteraan. Kebelakangan ini, terdapat minat yangsemakin meningkat dalam Permainan Kecerdasan Buatan atau permainan AI. Permainan AI merujukkepada teknik yang diaplikasikan dalam permainan komputer dan video seperti pembelajaran, pathfinding,perancangan, dan lain-lain bagi mewujudkan tingkah laku pintar dan autonomi kepada karakter dalampermainan. Objektif utama kajian ini adalah untuk mengemukakan beberapa teknik yang biasa digunakandalam merekabentuk dan mengawal karakter berasaskan komputer untuk permainan Ms Pac-Man antaratahun 2005-2012. Ms Pac-Man adalah salah satu permainan yang digunakan dalam siri pertandinganpermainan diperingkat antarabangsa sebagai penanda aras untuk perbandingan pengawal autonomi.Kaedah analisis kandungan yang menyeluruh dijalankan secara ulasan dan sorotan literatur secara kritikal.Dapatan kajian menunjukkan bahawa, walaupun terdapat berbagai teknik, limitasi utama dalam kajianterdahulu untuk mewujudkan karakter permaianan Pac Man adalah kekurangan Generalization Capabilitydalam kepelbagaian karakter permainan. Hasil kajian ini akan dapat digunakan oleh penyelidik untukmeningkatkan keupayaan Generalization AI karakter permainan dalam Pasaran Permainan KecerdasanBuatan. Abstract Artificial Intelligence (AI) techniques are successfully used and applied in a wide range of areas, includingmanufacturing, engineering, economics, medicine and military. In recent years, there has been anincreasing interest in Game Artificial Intelligence or Game AI. Game AI refers to techniques applied incomputer and video games such as learning, pathfinding, planning, and many others for creating intelligentand autonomous behaviour to the characters in games. The main objective of this paper is to highlightseveral most common of the AI techniques for designing and controlling the computer-based charactersto play Ms. Pac-Man game between years 2005-2012. The Ms. Pac-Man is one of the games that used asbenchmark for comparison of autonomous controllers in a series of international Game AI competitions.An extensive content analysis method was conducted through critical review on previous literature relatedto the field. Findings highlight, although there was various and unique techniques available, the majorlimitation of previous studies for creating the Ms. Pac-Man game characters is a lack of generalizationcapability across different game characters. The findings could provide the future direction for researchersto improve the Generalization A.I capability of game characters in the Game Artificial Intelligence market.

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