scholarly journals SAFETY IN WINE CELLARS: THE SITUATION IN FRIULI-VENEZIA GIULIA, ITALY

2009 ◽  
Vol 40 (1) ◽  
pp. 1 ◽  
Author(s):  
Rino Gubiani ◽  
Michela Vello ◽  
Gianfranco Pergher ◽  
Sirio R.C. Cidivino
Keyword(s):  
Working Environment ◽  
Wine Industry ◽  
Check List ◽  
Security Systems ◽  
A Value ◽  
Risk Areas ◽  
Boiler Room ◽  
Set Up ◽  
Friuli Venezia Giulia

The objective of the present work was to set up a method of analysis of the safety levels in the wine industry, using a check list to carry out a survey on 30 wineries located in the Friuli-Venezia Giulia region. The checklist, based on previous studies, included more than 500 items, divided into 5 main areas: A) Buildings and workplaces; B) Machinery; C) Logistics; D) Boiler room, electricity plants and fire prevention systems; E) Noise and vibrations. The classification of each of the items was based on risk frequency and seriousness of damage. In order to obtain a value as a whole, different points were assigned to each of them. The results of this work shows that workers are exposed to a variety of hazards and one of the highest scores is connected to machinery. Some of these accidents occur because machines are used for a purpose for which they are unsuitable; others because security systems have not been provided or have been taken off. Other risk areas are the fuel tank or the exhaust oil stocking room. Indoors, the most hazardous areas are the grape unloading and the workshop one. Another result was that the older wine cellars are the most dangerous. The check list can become an important instrument for prevention and a useful tool to test safety levels of the working environment.

Optimization of K Value in KNN Algorithm for Spam and Ham Email Classification

2020 ◽  
Vol 4 (2) ◽  
pp. 377-383
Author(s):  
Eko Laksono ◽  
Achmad Basuki ◽  
Fitra Bachtiar
Keyword(s):  
Frequency Distribution ◽  
Confusion Matrix ◽  
High Accuracy ◽  
K Value ◽  
A Value ◽  
Optimal Value ◽  
Classification Evaluation ◽  
Email Spam ◽  
Email Classification

There are many cases of email abuse that have the potential to harm others. This email abuse is commonly known as spam, which contains advertisements, phishing scams, and even malware. This study purpose to know the classification of email spam with ham using the KNN method as an effort to reduce the amount of spam. KNN can classify spam or ham in an email by checking it using a different K value approach. The results of the classification evaluation using confusion matrix resulted in the KNN method with a value of K = 1 having the highest accuracy value of 91.4%. From the results of the study, it is known that the optimization of the K value in KNN using frequency distribution clustering can produce high accuracy of 100%, while k-means clustering produces an accuracy of 99%. So based on the results of the existing accuracy values, the frequency distribution clustering and k-means clustering can be used to optimize the K-optimal value of the KNN in the classification of existing spam emails.

scholarly journals Implementation of a deep learning model for automated classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in real time

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Song-Quan Ong ◽  
Hamdan Ahmad ◽  
Gomesh Nair ◽  
Pradeep Isawasan ◽  
Abdul Hafiz Ab Majid
Keyword(s):  
Deep Learning ◽  
Aedes Aegypti ◽  
Real Time ◽  
Aedes Albopictus ◽  
Automated Classification ◽  
Expert Performance ◽  
Deep Convolutional Neural Networks ◽  
Significant Difference ◽  
Set Up

AbstractClassification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using hardware that could regulate the development process. In particular, we constructed a dataset with 4120 images of Aedes mosquitoes that were older than 12 days old and had common morphological features that disappeared, and we illustrated how to set up supervised deep convolutional neural networks (DCNNs) with hyperparameter adjustment. The model application was first conducted by deploying the model externally in real time on three different generations of mosquitoes, and the accuracy was compared with human expert performance. Our results showed that both the learning rate and epochs significantly affected the accuracy, and the best-performing hyperparameters achieved an accuracy of more than 98% at classifying mosquitoes, which showed no significant difference from human-level performance. We demonstrated the feasibility of the method to construct a model with the DCNN when deployed externally on mosquitoes in real time.

scholarly journals Wear and Friction Characteristics of 65Mn Steel for Spike-Tooth Harrow

Coatings ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 319
Author(s):  
Zhiguo Lu ◽  
Chuanyu Du ◽  
Qingcai Chen ◽  
Tianying Niu ◽  
Na Wang ◽  
...  
Keyword(s):  
Friction And Wear ◽  
Working Environment ◽  
Manganese Steel ◽  
Wear Loss ◽  
Variable Parameters ◽  
Wear Characteristics ◽  
Before And After ◽  
Set Up ◽  
Worn Surface ◽  
Friction And Wear Characteristics

The friction and wear characteristics of spike-tooth material (65Mn steel) of Spike-Tooth Harrow in a two-stage peanut harvester were studied in this paper. The friction and wear tests of pin and disc on 65 manganese steel were carried out on the tribometer, then the wear loss and the friction coefficient were studied. The wear loss of the pin was acquired by calculating the mass of the pin before and after the experiment using an electronic balance. According to the actual working environment of peanut spring-finger, four variable parameters are set up: load, speed, soil moisture and soil type. The friction and wear characteristics of pins were studied under different loads, speeds and different soil environments. After wearing, the worn surface of the material was observed by scanning microscope and the wear mechanism was studied. The experimental results show that the wear of the pin increases with the increase of load and decreases with the increase of rotational speed in the same rotation number. Especially in the case of the sandy soil with 20% in moisture, a maximum wear loss of the pin is achieved.

scholarly journals Towards a Unified Sentiment Lexicon Based on Graphics Processing Units

2014 ◽  
Vol 2014 ◽  
pp. 1-19
Author(s):  
Liliana Ibeth Barbosa-Santillán ◽  
Inmaculada Álvarez-de-Mon y-Rego
Keyword(s):  
Graphics Processing Units ◽  
Pearson Correlation ◽  
Lexical Entry ◽  
A Value ◽  
Sentiment Lexicon ◽  
Unit Of Measurement ◽  
Time Required ◽  
Graphics Processing ◽  
High Processing

This paper presents an approach to create what we have called a Unified Sentiment Lexicon (USL). This approach aims at aligning, unifying, and expanding the set of sentiment lexicons which are available on the web in order to increase their robustness of coverage. One problem related to the task of the automatic unification of different scores of sentiment lexicons is that there are multiple lexical entries for which the classification of positive, negative, or neutral{P,N,Z}depends on the unit of measurement used in the annotation methodology of the source sentiment lexicon. Our USL approach computes the unified strength of polarity of each lexical entry based on the Pearson correlation coefficient which measures how correlated lexical entries are with a value between 1 and −1, where 1 indicates that the lexical entries are perfectly correlated, 0 indicates no correlation, and −1 means they are perfectly inversely correlated and so is the UnifiedMetrics procedure for CPU and GPU, respectively. Another problem is the high processing time required for computing all the lexical entries in the unification task. Thus, the USL approach computes a subset of lexical entries in each of the 1344 GPU cores and uses parallel processing in order to unify 155802 lexical entries. The results of the analysis conducted using the USL approach show that the USL has 95.430 lexical entries, out of which there are 35.201 considered to be positive, 22.029 negative, and 38.200 neutral. Finally, the runtime was 10 minutes for 95.430 lexical entries; this allows a reduction of the time computing for the UnifiedMetrics by 3 times.

Increased Wall-to-Wall Curing Contraction in Thin Bonded Resin Layers

1989 ◽  
Vol 68 (1) ◽  
pp. 48-50 ◽  
Author(s):  
A.J. Feilzer ◽  
A.J. De Gee ◽  
C.L. Davidson
Keyword(s):  
Polymerization Shrinkage ◽  
A Value ◽  
Set Up

Wall-to-wall (WTW) polymerization contraction of filled and unfilled chemically and photo-initiated resins was studied in relation to the WTW distance. In an experimental set-up, the resins were bonded to two opposing disks, and the axial (WTW) displacement resulting from the polymerization shrinkage was measured continuously. It was found that the WTW contraction increased with decreasing WTW distance and ultimately reached a value of almost three times the linear polymerization shrinkage.

scholarly journals Determination of the Value of Intangible Assets in the Companies of Lithuania

2017 ◽  
Vol 14 (2) ◽  
pp. 55-68 ◽  
Author(s):  
Rita Bužinskienė
Keyword(s):  
Financial Management ◽  
Intangible Assets ◽  
Fair Value ◽  
Financial Information ◽  
Financial Accounting ◽  
True Value ◽  
A Value ◽  
The Impact

AbstractIn accordance with generally accepted accounting standards, most intangibles are not accounted for and not reflected in the traditional financial accounting. For this reason, most companies account intangible assets (IAs) as expenses. In the research, 57 sub-elements of IAs were applied, which are grouped into eight main elements of IAs. The classification of IAs consists in two parts of assets: accounting and non-accounting. This classification can be successfully applied in different branches of enterprises, to expand and supplement the theoretical and practical concepts of the company's financial management. The article proposes to evaluate not only the value of financial information for IAs (accounted) but also the value of non-financial information for IAs (non-accounted), thus revealing the true value of IAs that is available to the companies of Lithuania. It names a value of general IAs. The results of the research confirmed the IA valuation methodology, which allows companies to calculate the fair value of an IA. The obtained extended IAs valuation information may be valuable to both the owners of the company and investors, as this value plays an important practical role in assessing the impact of IAs on the market value of companies.

scholarly journals Rapid Classification of Clostridioides difficile Strains Using MALDI-TOF MS Peak-Based Assay in Comparison with PCR-Ribotyping

2021 ◽  
Vol 9 (3) ◽  
pp. 661
Author(s):  
Adriana Calderaro ◽  
Mirko Buttrini ◽  
Monica Martinelli ◽  
Benedetta Farina ◽  
Tiziano Moro ◽  
...  
Keyword(s):  
Ionization Time ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Flight Mass Spectrometry ◽  
Clostridioides Difficile ◽  
Pcr Ribotyping ◽  
Typing Methods ◽  
Set Up ◽  
Tof Ms

Typing methods are needed for epidemiological tracking of new emerging and hypervirulent strains because of the growing incidence, severity and mortality of Clostridioides difficile infections (CDI). The aim of this study was the evaluation of a typing Matrix-Assisted Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS (T-MALDI)) method for the rapid classification of the circulating C. difficile strains in comparison with polymerase chain reaction (PCR)-ribotyping results. Among 95 C. difficile strains, 10 ribotypes (PR1–PR10) were identified by PCR-ribotyping. In particular, 93.7% of the isolates (89/95) were grouped in five ribotypes (PR1–PR5). For T-MALDI, two classifying algorithm models (CAM) were tested: the first CAM involved all 10 ribotypes whereas the second one only the PR1–PR5 ribotypes. Better performance was obtained using the second CAM: recognition capability of 100%, cross-validation of 96.6% and agreement of 98.4% (60 correctly typed strains, limited to PR1–PR5 classification, out of 61 examined strains) with PCR-ribotyping results. T-MALDI seems to represent an alternative to PCR-ribotyping in terms of reproducibility, set up time and costs, as well as a useful tool in epidemiological investigation for the detection of C. difficile clusters (either among CAM included ribotypes or out-of-CAM ribotypes) involved in outbreaks.

Using transfer learning for diabetic retinopathy stage classification

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Enas M.F. El Houby
Keyword(s):  
Diabetic Retinopathy ◽  
Transfer Learning ◽  
Grade Level ◽  
Design Methodology ◽  
Content Type ◽  
Stage Classification ◽  
Set Up ◽  
Retinal Fundus ◽  
Automated Methods

PurposeDiabetic retinopathy (DR) is one of the dangerous complications of diabetes. Its grade level must be tracked to manage its progress and to start the appropriate decision for treatment in time. Effective automated methods for the detection of DR and the classification of its severity stage are necessary to reduce the burden on ophthalmologists and diagnostic contradictions among manual readers.Design/methodology/approachIn this research, convolutional neural network (CNN) was used based on colored retinal fundus images for the detection of DR and classification of its stages. CNN can recognize sophisticated features on the retina and provides an automatic diagnosis. The pre-trained VGG-16 CNN model was applied using a transfer learning (TL) approach to utilize the already learned parameters in the detection.FindingsBy conducting different experiments set up with different severity groupings, the achieved results are promising. The best-achieved accuracies for 2-class, 3-class, 4-class and 5-class classifications are 86.5, 80.5, 63.5 and 73.7, respectively.Originality/valueIn this research, VGG-16 was used to detect and classify DR stages using the TL approach. Different combinations of classes were used in the classification of DR severity stages to illustrate the ability of the model to differentiate between the classes and verify the effect of these changes on the performance of the model.

Een slechte start en dan?

2017 ◽  
Vol 33 (3) ◽  
Author(s):  
Henk-Jan Dirven ◽  
Wouter van der Torre ◽  
Seth van den Bossche
Keyword(s):  
Analysis Data ◽  
Working Environment ◽  
Work Situation ◽  
Financial Situation ◽  
Work Related ◽  
Self Employment ◽  
Level Of Satisfaction ◽  
Set Up ◽  
Employment Quality

A bad start and what then? The work situation of self-employed entrepreneurs with negative and positive start motives This article assesses the extent to which the quality of labor varies between solo self-employed who set up a business for negative reasons and those who started for positive reasons. A negative reason is, for example, not being able to find a suitable job as an employee; an example of a positive reason is wanting to be self-employed from the very beginning. Quality of labor is measured according to the person's financial situation, security of employment, quality of the working environment and work satisfaction. In the analysis, data are used from the Self-employment Survey conducted by Statistics Netherlands and TNO. Compared to self-employed persons with a positive motivation, those who were negatively motivated show lower performance in terms of their business's financial situation, income position, work-related mental fatigue (burn-out), self-perceived health status, concern about the business's future and the level of satisfaction. However, in absolute terms, the vast majority appear to be satisfied with their work situation, enthusiastic and not intending to quit self-employment.

scholarly journals Analysis of the coefficient of variation in shear and tensile bond strength tests

2005 ◽  
Vol 13 (3) ◽  
pp. 243-246 ◽  
Author(s):  
Fábio Lourenço Romano ◽  
Gláucia Maria Bovi Ambrosano ◽  
Maria Beatriz Borges de Araújo Magnani ◽  
Darcy Flávio Nouer
Keyword(s):  
Coefficient Of Variation ◽  
Mean Value ◽  
Scientific Article ◽  
A Value ◽  
Statistical Analysis System ◽  
Strength Tests ◽  
Analysis System ◽  
Very High

The coefficient of variation is a dispersion measurement that does not depend on the unit scales, thus allowing the comparison of experimental results involving different variables. Its calculation is crucial for the adhesive experiments performed in laboratories because both precision and reliability can be verified. The aim of this study was to evaluate and to suggest a classification of the coefficient variation (CV) for in vitro experiments on shear and tensile strengths. The experiments were performed in laboratory by fifty international and national studies on adhesion materials. Statistical data allowing the estimation of the coefficient of variation was gathered from each scientific article since none of them had such a measurement previously calculated. Excel worksheet was used for organizing the data while the sample normality was tested by using Shapiro Wilk tests (alpha = 0.05) and the Statistical Analysis System software (SAS). A mean value of 6.11 (SD = 1.83) for the coefficient of variation was found by the data analysis and the data had a normal distribution (p>0.05). A range classification was proposed for the coefficient of variation from such data, that is, it should be considered low for a value lesser than 2.44; intermediate for a value between 2.44 and 7.94, high for a value between 7.94 and 9.78, and finally, very high for a value greater than 9.78. Such classification can be used as a guide for experiments on adhesion materials, thus making the planning easier as well as revealing precision and validity concerning the data.

Sign in / Sign up

Export Citation Format

Share Document