scholarly journals A Comparative Study on Classification of Image Pixels

2015 ◽  
Vol 20 (2) ◽  
pp. 128-135
Author(s):  
Santosh Ghimire
Keyword(s):  
Comparative Study ◽  
Science And Technology ◽  
Classification Method ◽  
Image Pixels ◽  
Better Than

In this paper, we perform the comparison between the classification method introduced by Ghimire-Wang and the classification method developed by Liao-Akritas in many images. We show that in all the considered images, the method introduced by Ghimire-Wang works better than the method of Liao-Akritas.Journal of Institute of Science and Technology, 2015, 20(2): 128-135  

scholarly journals A Comparative Study of Machine Learning Methods for Automatic Classification of Academic and Vocational Guidance Questions

2020 ◽  
Vol 14 (08) ◽  
pp. 43 ◽  
Author(s):  
Omar Zahour ◽  
El Habib Benlahmar ◽  
Ahmed Eddaouim ◽  
Oumaima Hourrane
Keyword(s):  
Machine Learning ◽  
Comparative Study ◽  
Automatic Classification ◽  
Vocational Guidance ◽  
Machine Learning Algorithms ◽  
Holland's Theory ◽  
Machine Learning Methods ◽  
The Right ◽  
Better Than

Academic and vocational guidance is a particularly important issue today, as it strongly determines the chances of successful integration into the labor market, which has become increasingly difficult. Families have understood this because they are interested, often with concern, in the orientation of their child. In this context, it is very important to consider the interests, trades, skills, and personality of each student to make the right decision and build a strong career path. This paper deals with the problematic of educational and vocational guidance by providing a comparative study of the results of four machine-learning algorithms. The algorithms we used are for the automatic classification of school orientation questions and four categories based on John L. Holland's Theory of RIASEC typology. The results of this study show that neural networks work better than the other three algorithms in terms of the automatic classification of these questions. In this sense, our model allows us to automatically generate questions in this domain. This model can serve practitioners and researchers in E-Orientation for further research because the algorithms give us good results.

scholarly journals Detection and Classification of Interacting Persons

2010 ◽  
pp. 213-227
Author(s):  
Scott Blunsden ◽  
Robert Fisher
Keyword(s):  
State Of The Art ◽  
New Method ◽  
Classification Method ◽  
Previous State ◽  
New Feature ◽  
Better Than

This chapter presents a way to classify interactions between people. Examples of the interactions we investigate are: people meeting one another, walking together, and fighting. A new feature set is proposed along with a corresponding classification method. Results are presented which show the new method performing significantly better than the previous state of the art method as proposed by Oliver et al. (2000).

Comparative Study Between Clean Intermittent Self-Catheterization (Cisc) and Continuous Indwelling Catheterization (Cidc) in Relieving Acute Refractory Retention of Urine Due to Benign Enlargement of Prostate (Bep)

2020 ◽  
Vol 21 (2) ◽  
pp. 105-110
Author(s):  
Md Shawkat Alam ◽  
Sudip Das Gupta ◽  
Hadi Zia Uddin Ahmed ◽  
Md Saruar Alam ◽  
Sharif Muhammod Wasimuddin
Keyword(s):  
Comparative Study ◽  
Acute Urinary Retention ◽  
Bladder Capacity ◽  
Inclusion Criteria ◽  
College Hospital ◽  
Medical College ◽  
High Incidence ◽  
Group A ◽  
Group B ◽  
Better Than

Objective: To compare the clean intermittent self-catheterization (CISC) with continuous indwelling catheterization (CIDC) in relieving acute urinary retention (AUR) due to benign enlargement of prostate (BEP). Materials and Methods :A total 60 patients attending in urology department of Dhaka Medical college hospital were included according to inclusion criteria ,Patients were randomized by lottery into two groups namely group –A and group –B for CISC and IDC drainage respectively . Thus total 60 patients 30 in each group completed study. Results : Most men can safely be managed as out-patients after AUR due to BPH. The degree of mucosal congestion and inflammation within the bladder was found to be lower in those using CISC and the bladder capacity in these patients was also found higher.Patients with an IDC had a high incidence of UTIs then that of patients with CISC. During the period of catheterization the incidence of UTI was 43.3% in group B in comparison to 40% in group A; before TURP 36% in group B in comparison to 10% incidence in group A.According to patient’s opinion CISC is better than IDC in the management of AUR. Experiencing bladder spasm, reporting blood in urine, management difficulties, incidence and severity of pain were less in CISC group, and the method of CISC was well accepted by patients as well as their family members. Conclusion: From the current study it may be suggested that CISC is better technique for management of AUR patient due to BPH than IDC. It can also be very helpful when surgery must be delayed or avoided due to any reasons in this group of patients. Bangladesh Journal of Urology, Vol. 21, No. 2, July 2018 p.105-110

scholarly journals NLOS Multipath Classification of GNSS Signal Correlation Output Using Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2503
Author(s):  
Taro Suzuki ◽  
Yoshiharu Amano
Keyword(s):  
Machine Learning ◽  
Satellite System ◽  
Training Data ◽  
Support Vector ◽  
Positioning Errors ◽  
Automated Method ◽  
Global Navigation Satellite ◽  
Better Than ◽  
Signal Correlation

This paper proposes a method for detecting non-line-of-sight (NLOS) multipath, which causes large positioning errors in a global navigation satellite system (GNSS). We use GNSS signal correlation output, which is the most primitive GNSS signal processing output, to detect NLOS multipath based on machine learning. The shape of the multi-correlator outputs is distorted due to the NLOS multipath. The features of the shape of the multi-correlator are used to discriminate the NLOS multipath. We implement two supervised learning methods, a support vector machine (SVM) and a neural network (NN), and compare their performance. In addition, we also propose an automated method of collecting training data for LOS and NLOS signals of machine learning. The evaluation of the proposed NLOS detection method in an urban environment confirmed that NN was better than SVM, and 97.7% of NLOS signals were correctly discriminated.

scholarly journals Deep Learning Methods for Classification of Certain Abnormalities in Echocardiography

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 495
Author(s):  
Imayanmosha Wahlang ◽  
Arnab Kumar Maji ◽  
Goutam Saha ◽  
Prasun Chakrabarti ◽  
Michal Jasinski ◽  
...  
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Support Vector ◽  
Variational Autoencoder ◽  
Different Types ◽  
Static Images ◽  
Long Short Term Memory ◽  
2D And 3D ◽  
Better Than

This article experiments with deep learning methodologies in echocardiogram (echo), a promising and vigorously researched technique in the preponderance field. This paper involves two different kinds of classification in the echo. Firstly, classification into normal (absence of abnormalities) or abnormal (presence of abnormalities) has been done, using 2D echo images, 3D Doppler images, and videographic images. Secondly, based on different types of regurgitation, namely, Mitral Regurgitation (MR), Aortic Regurgitation (AR), Tricuspid Regurgitation (TR), and a combination of the three types of regurgitation are classified using videographic echo images. Two deep-learning methodologies are used for these purposes, a Recurrent Neural Network (RNN) based methodology (Long Short Term Memory (LSTM)) and an Autoencoder based methodology (Variational AutoEncoder (VAE)). The use of videographic images distinguished this work from the existing work using SVM (Support Vector Machine) and also application of deep-learning methodologies is the first of many in this particular field. It was found that deep-learning methodologies perform better than SVM methodology in normal or abnormal classification. Overall, VAE performs better in 2D and 3D Doppler images (static images) while LSTM performs better in the case of videographic images.

scholarly journals CNN architecture comparison for radio galaxy classification

2021 ◽  
Vol 503 (2) ◽  
pp. 1828-1846
Author(s):  
Burger Becker ◽  
Mattia Vaccari ◽  
Matthew Prescott ◽  
Trienko Grobler
Keyword(s):  
Comparative Study ◽  
Galaxy Evolution ◽  
Radio Galaxy ◽  
Recognition Performance ◽  
Model Complexity ◽  
Great Promise ◽  
Radio Sources ◽  
Morphological Classification ◽  
Computational Performance

ABSTRACT The morphological classification of radio sources is important to gain a full understanding of galaxy evolution processes and their relation with local environmental properties. Furthermore, the complex nature of the problem, its appeal for citizen scientists, and the large data rates generated by existing and upcoming radio telescopes combine to make the morphological classification of radio sources an ideal test case for the application of machine learning techniques. One approach that has shown great promise recently is convolutional neural networks (CNNs). Literature, however, lacks two major things when it comes to CNNs and radio galaxy morphological classification. First, a proper analysis of whether overfitting occurs when training CNNs to perform radio galaxy morphological classification using a small curated training set is needed. Secondly, a good comparative study regarding the practical applicability of the CNN architectures in literature is required. Both of these shortcomings are addressed in this paper. Multiple performance metrics are used for the latter comparative study, such as inference time, model complexity, computational complexity, and mean per class accuracy. As part of this study, we also investigate the effect that receptive field, stride length, and coverage have on recognition performance. For the sake of completeness, we also investigate the recognition performance gains that we can obtain by employing classification ensembles. A ranking system based upon recognition and computational performance is proposed. MCRGNet, Radio Galaxy Zoo, and ConvXpress (novel classifier) are the architectures that best balance computational requirements with recognition performance.

scholarly journals The Use of UV Spectroscopy and SIMCA for the Authentication of Indonesian Honeys According to Botanical, Entomological and Geographical Origins

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 915
Author(s):  
Diding Suhandy ◽  
Meinilwita Yulia
Keyword(s):  
Spectral Data ◽  
Uv Spectroscopy ◽  
Moving Average ◽  
Food Product ◽  
Classification Method ◽  
Economic Losses ◽  
Food Fraud ◽  
Authentication System ◽  
Uv Visible

As a functional food, honey is a food product that is exposed to the risk of food fraud. To mitigate this, the establishment of an authentication system for honey is very important in order to protect both producers and consumers from possible economic losses. This research presents a simple analytical method for the authentication and classification of Indonesian honeys according to their botanical, entomological, and geographical origins using ultraviolet (UV) spectroscopy and SIMCA (soft independent modeling of class analogy). The spectral data of a total of 1040 samples, representing six types of Indonesian honey of different botanical, entomological, and geographical origins, were acquired using a benchtop UV-visible spectrometer (190–400 nm). Three different pre-processing algorithms were simultaneously evaluated; namely an 11-point moving average smoothing, mean normalization, and Savitzky–Golay first derivative with 11 points and second-order polynomial fitting (ordo 2), in order to improve the original spectral data. Chemometrics methods, including exploratory analysis of PCA and SIMCA classification method, was used to classify the honey samples. A clear separation of the six different Indonesian honeys, based on botanical, entomological, and geographical origins, was obtained using PCA calculated from pre-processed spectra from 250–400 nm. The SIMCA classification method provided satisfactory results in classifying honey samples according to their botanical, entomological, and geographical origins and achieved 100% accuracy, sensitivity, and specificity. Several wavelengths were identified (266, 270, 280, 290, 300, 335, and 360 nm) as the most sensitive for discriminating between the different Indonesian honey samples.

Study on Effect of Spheroidization on Hazardous Classification of ADN

2021 ◽  
Vol 881 ◽  
pp. 71-76
Author(s):  
Jian Yang ◽  
Hong Bin Li ◽  
Song Tao Ren ◽  
Peng Gang Jin ◽  
Zan Gao
Keyword(s):  
Temperature Stability ◽  
Impact Sensitivity ◽  
Classification Method ◽  
Ammonium Dinitramide ◽  
Classification Procedure ◽  
Research Results ◽  
Before And After ◽  
Hazard Classification ◽  
Friction Sensitivity

In order to determine the influence of spheroidization process of Ammonium dinitramide’s hazard grade, the hazardous division of Ammonium dinitramide before and after spheroidization is studied by using hazard classification procedure for combustible and explosive substances and articles standard (WJ20405) and hazard classification method and criterion for combusitible and explosive substances and articles standard (WJ20404). The research results show that spheroidization process can significantly improve the temperature stability of Ammonium dinitramide and significantly reduce friction sensitivity and impact sensitivity of Ammonium dinitramide. So spheroidization process can reduce the hazardous of Ammonium dinitramide and improve the safe character of Ammonium dinitramide.

Structure and Semantics of Tactile Verbs in a Comparative Aspect (On the Material of the English, German and Russian Languages)

2021 ◽  
pp. 58-63
Author(s):  
Yu. A. Sakhno
Keyword(s):  
Comparative Study ◽  
Semantic Features ◽  
Semantic Classification ◽  
Comparative Aspect ◽  
Similarities And Differences ◽  
The Comparative Study ◽  
Linguistic Units

This article deals with the study of the structural and semantic features of tactile verbs (hereinafter TVs) in English, German and Russian. Particular attention is paid to the comparative study of TVs, which allows us to identify structural and semantic similarities and differences of linguistic units studied. The structural and semantic classification of TVs in the compared languages is also provided.

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