scholarly journals Effect of material ageing and dirt on the behaviour of greenhouse insect-proof screens

2019 ◽  
Vol 16 (4) ◽  
pp. e0205 ◽  
Author(s):  
Alejandro López ◽  
Francisco D. Molina-Aiz ◽  
Diego L. Valera ◽  
Araceli Peña ◽  
Karlos Espinoza
Keyword(s):  
Image Processing ◽  
Natural Ventilation ◽  
Discharge Coefficient ◽  
Aerodynamic Characteristics ◽  
The Other ◽  
Subsequent Decrease ◽  
Thread Diameter ◽  
Pressure Water ◽  
Material Ageing ◽  
Cleaning Treatment

The present work examines the variations in the aerodynamic characteristics of four insect-proof screens by means of wind tunnel tests and digital image processing. The tested insect-proof screens were examined in three different conditions: (i) in their new, unused state; (ii) under conditions of accumulated dust and dirt after a period of 3 to 4 years of use; and (iii) under clean conditions after a period of 3 to 4 years of use and a cleaning treatment with high-pressure water. The deterioration of the screens caused the mesh to become less tense, therefore increasing its thickness and improving its aerodynamic behaviour despite a slight increase of the thread diameter and a subsequent decrease of the 2-dimensional porosity. The pressure drop coefficient, Fφ, of the used but clean screens was 1.5% to 8.8% lower (for u=1.0 m/s) than that of the new ones, thus increasing the discharge coefficient, Cd,φ, by between 0.8% and 4.8% as a result of the presence of the screens. On the other hand, comparison of the used screens in their clean and unclean states showed that the accumulation of dirt has a major bearing on their aerodynamic characteristics: Fφ increased by between 16.5% and 61.2% (for u=1.0 m/s) for the unclean screens, resulting in a Cd,φ reduction of between 7.5% and 21.3% and therefore a lower natural ventilation capacity of the greenhouse. A regular cleaning treatment of the insect-proof screens is a simple measure that improves the natural ventilation capacity of the greenhouse.

Computer Vision and robotics in postal automation

1999 ◽  
Vol 18 (3-4) ◽  
pp. 265-273
Author(s):  
Giovanni B. Garibotto
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Pattern Recognition ◽  
Material Handling ◽  
State Of The Art ◽  
Short Description ◽  
The Other ◽  
Functional Requirements ◽  
Postal Automation ◽  
And Robotics

The paper is intended to provide an overview of advanced robotic technologies within the context of Postal Automation services. The main functional requirements of the application are briefly referred, as well as the state of the art and new emerging solutions. Image Processing and Pattern Recognition have always played a fundamental role in Address Interpretation and Mail sorting and the new challenging objective is now off-line handwritten cursive recognition, in order to be able to handle all kind of addresses in a uniform way. On the other hand, advanced electromechanical and robotic solutions are extremely important to solve the problems of mail storage, transportation and distribution, as well as for material handling and logistics. Finally a short description of new services of Postal Automation is referred, by considering new emerging services of hybrid mail and paper to electronic conversion.

scholarly journals Analysis of the Nosema Cells Identification for Microscopic Images

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3068
Author(s):  
Soumaya Dghim ◽  
Carlos M. Travieso-González ◽  
Radim Burget
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Image Processing ◽  
Deep Learning ◽  
The Other ◽  
Support Vector ◽  
Learning Approaches ◽  
Microscopic Images ◽  
Trained Neural Network ◽  
Nosema Disease

The use of image processing tools, machine learning, and deep learning approaches has become very useful and robust in recent years. This paper introduces the detection of the Nosema disease, which is considered to be one of the most economically significant diseases today. This work shows a solution for recognizing and identifying Nosema cells between the other existing objects in the microscopic image. Two main strategies are examined. The first strategy uses image processing tools to extract the most valuable information and features from the dataset of microscopic images. Then, machine learning methods are applied, such as a neural network (ANN) and support vector machine (SVM) for detecting and classifying the Nosema disease cells. The second strategy explores deep learning and transfers learning. Several approaches were examined, including a convolutional neural network (CNN) classifier and several methods of transfer learning (AlexNet, VGG-16 and VGG-19), which were fine-tuned and applied to the object sub-images in order to identify the Nosema images from the other object images. The best accuracy was reached by the VGG-16 pre-trained neural network with 96.25%.

DETERMINATION AERODYNAMIC CHARACTERISTICS OF ELEMENTS OF BUILDING VENTILATION SYSTEMS IN LABORATORY CONDITIONS

2021 ◽  
Vol 3 (1) ◽  
pp. 049-053
Author(s):  
M. A. KRIVOSHEIN ◽  
◽  
K. D. SMIRNOV ◽  
K. V. MESHKO ◽  
◽  
...  
Keyword(s):  
Natural Ventilation ◽  
Check Valve ◽  
Aerodynamic Characteristics ◽  
Laboratory Conditions ◽  
Building Ventilation ◽  
Ventilation Systems

The article presents the layout and appearance of the stand, developed to determine the aerodynamic characteristics of the elements of ventilation systems. The technique of determining the aerodynamic characteristics of ventilation elements using the developed stand is considered. The results of tests of a check valve used in natural ventilation systems of buildings are presented. The obtained characteristic of the check valve is proposed to be used in calculating and predicting the operation of ventilation systems in buildings in which the check valves under consideration will be installed

An Analysis of the Aerodynamic Characteristics of Split Flaps

1940 ◽  
Vol 44 (352) ◽  
pp. 338-349
Author(s):  
A. P. West
Keyword(s):  
Experimental Data ◽  
Aerodynamic Characteristics ◽  
Full Scale ◽  
The Other ◽  
Aircraft Industry ◽  
The Past ◽  
The Many ◽  
Lift And Drag ◽  
Scale Data

During the past few years an extensive amount of experimental data on split flaps has been made available to the aircraft industry, through the publications of aeronautical research laboratories, both in this country and abroad. In general, each publication deals with one particular aspect of the problem, and when the effect of wing flaps on the performance of an aircraft is being estimated a certain amount of difficulty may be experienced in deciding which of the many reports available gives results most readily applicable to the case being considered ; and what allowances, if any, should be made for wing taper, flap cut-out, fuselage, etc.In this report the available data has been analysed with a view to answering these questions, and presented in such a form that it may be readily applied to determine the most probable change in the aerodynamic characteristics of a wing that may be expected from the use of this type of flap.From the appendix an estimate of the accuracy of the method can be obtained, as a comparison with full-scale data is given for lift and drag, and for the other flap characteristics the original curves have been reproduced.

Soft-Computing-Based Approaches for Plant Leaf Disease Detection

2019 ◽  
pp. 100-113
Author(s):  
Vivek K. Verma ◽  
Tarun Jain
Keyword(s):  
Image Processing ◽  
Leaf Area ◽  
Soft Computing ◽  
Environmental Conditions ◽  
The Other ◽  
Disease Detection ◽  
Plant Leaves ◽  
Plant Leaf ◽  
Disease Occurrence ◽  
Plant Image

The disease occurrence phenomena in plants are season-based which is dependent on the presence of the pathogen, crops, environmental conditions, and varieties grown. Some plant varieties are particularly subject to outbreaks of diseases; on the other hand, some are opposite to them. Huge numbers of diseases are seen on the plant leaves and stems. Diseases management is a challenging task. Generally, diseases are seen on the leaves or stems of the plant. Image processing is the best way for the detection of plant leaf diseases. Different kinds of diseases occur because of the attack of bacteria, fungi, and viruses. The monitoring of leaf area is an important tool in studying physiological capabilities associated with plant boom. Plant disorder is usually an unusual growth or dysfunction of a plant. Sometimes diseases damage the leaves of plants.

PERFORMANCE COMPARISON OF DENOISING METHODS FOR HISTORICAL DOCUMENTS

2015 ◽  
Vol 77 (22) ◽  
Author(s):  
Sayed Muchallil ◽  
Fitri Arnia ◽  
Khairul Munadi ◽  
Fardian Fardian
Keyword(s):  
Image Processing ◽  
Processing Technique ◽  
Performance Comparison ◽  
The Other ◽  
Historical Documents ◽  
Median Filtering ◽  
Document Images ◽  
Post Processing ◽  
Binary Images ◽  
Complete Procedure

Image denoising plays an important role in image processing.  It is also part of the pre-processing technique in a binarization complete procedure that consists of pre-processing, thresholding, and post-processing.  Our previous research has confirmed that the Discrete Cosine Transform (DCT)-based filtering as the new pre-processing process improved the performance of binarization output in terms of recall and precision. This research compares three classical denoising methods; Gaussian, mean, and median filtering with the DCT-based filtering. The noisy ancient document images are filtered using those classical filtering methods. The outputs of this process are used as the input for Otsu, Niblack, Sauvola and NICK binarization methods. Then the resulted binary images of the three classical methods are compared with those of DCT-based filtering. The performance of all denoising algorithms is evaluated by calculating recall and precision of the resulted binary images.  The result of this research is that the DCT based filtering resulted in the highest recall and precision as compared to the other methods. 

A low-PDAP and high-PSNR approximate 4:2 compressor cell in CNFET technology

Circuit World ◽  
2019 ◽  
Vol 45 (3) ◽  
pp. 156-168 ◽  
Author(s):  
Yavar Safaei Mehrabani ◽  
Mehdi Bagherizadeh ◽  
Mohammad Hossein Shafiabadi ◽  
Abolghasem Ghasempour
Keyword(s):  
Image Processing ◽  
Design Methodology ◽  
Figure Of Merit ◽  
Signal To Noise Ratio ◽  
Monte Carlo Analysis ◽  
The Other ◽  
Threshold Logic ◽  
Signal To Noise ◽  
Content Type ◽  
Power Delay Product

Purpose This paper aims to present an inexact 4:2 compressor cell using carbon nanotube filed effect transistors (CNFETs). Design/methodology/approach To design this cell, the capacitive threshold logic (CTL) has been used. Findings To evaluate the proposed cell, comprehensive simulations are carried out at two levels of the circuit and image processing. At the circuit level, the HSPICE software has been used and the power consumption, delay, and power-delay product are calculated. Also, the power-delaytransistor count product (PDAP) is used to make a compromise between all metrics. On the other hand, the Monte Carlo analysis has been used to scrutinize the robustness of the proposed cell against the variations in the manufacturing process. The results of simulations at this level of abstraction indicate the superiority of the proposed cell to other circuits. At the application level, the MATLAB software is also used to evaluate the peak signal-to-noise ratio (PSNR) figure of merit. At this level, the two primary images are multiplied by a multiplier circuit consisting of 4:2 compressors. The results of this simulation also show the superiority of the proposed cell to others. Originality/value This cell significantly reduces the number of transistors and only consists of NOT gates.

scholarly journals Gender Classification Based on Geometry Features of Palm Image

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Ming Wu ◽  
Yubo Yuan
Keyword(s):  
Image Processing ◽  
Support Vector Machine ◽  
The Other ◽  
Classification Method ◽  
Support Vector ◽  
Gender Classification ◽  
Gender Recognition ◽  
Classification Rate ◽  
Classification Approach ◽  
Smooth Support Vector Machine

This paper presents a novel gender classification method based on geometry features of palm image which is simple, fast, and easy to handle. This gender classification method based on geometry features comprises two main attributes. The first one is feature extraction by image processing. The other one is classification system with polynomial smooth support vector machine (PSSVM). A total of 180 palm images were collected from 30 persons to verify the validity of the proposed gender classification approach and the results are satisfactory with classification rate over 85%. Experimental results demonstrate that our proposed approach is feasible and effective in gender recognition.

Structured Sign for Guidance of Mobile Robot

1991 ◽  
Vol 3 (5) ◽  
pp. 379-386
Author(s):  
Hesin Sai ◽  
◽  
Yoshikuni Okawa
Keyword(s):  
Image Processing ◽  
Theoretical Analysis ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Personal Computer ◽  
The Other ◽  
Guidance System ◽  
Fluorescent Light ◽  
Trajectory Following ◽  
Good Coincidence

As part of a guidance system for mobile robots operating on a wide and flat floor, such as an ordinary factory or a gymnasium, we have proposed a special-purpose sign. It consists of a cylinder, with four slits, and a fluorescent light, which is placed on the axis of the cylinder. Two of the slits are parallel to each other, and the other two are angled. A robot obtains an image of the sign with a TV camera. After thresholding, we have four bright sets of pixels which correspond to the four slits of the cylinder. We compute by measuring the relative distances between the four points, the distance and the angle to the direction of the sign can be computed using simple geometrical equations. Using a personal computer with an image processing capability, we have investigated the accuracy of the proposed position identification method and compared the experimental results against the theoretical analysis of measured error. The data shows good coincidence between the analysis and the experiments. Finally, we have built a movable robot, which has three microprocessors and a TV camera, and performed several control experiments for trajectory following.

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