scholarly journals Efficient Processing of Image Processing Applications on CPU/GPU

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Najia Naz ◽  
Abdul Haseeb Malik ◽  
Abu Bakar Khurshid ◽  
Furqan Aziz ◽  
Bader Alouffi ◽  
...  
Keyword(s):  
Image Processing ◽  
Heterogeneous Systems ◽  
Image Data ◽  
Machine Learning Algorithms ◽  
Phase Image ◽  
Second Phase ◽  
Healthcare Applications ◽  
Big Visual Data ◽  
Workload Distribution ◽  
Two Phases

Heterogeneous systems have gained popularity due to the rapid growth in data and the need for processing this big data to extract useful information. In recent years, many healthcare applications have been developed which use machine learning algorithms to perform tasks such as image classification, object detection, image segmentation, and instance segmentation. The increasing amount of big visual data requires images to be processed efficiently. It is common that we use heterogeneous systems for such type of applications, as processing a huge number of images on a single PC may take months of computation. In heterogeneous systems, data are distributed on different nodes in the system. However, heterogeneous systems do not distribute images based on the computing capabilities of different types of processors in the node; therefore, a slow processor may take much longer to process an image compared to a faster processor. This imbalanced workload distribution observed in heterogeneous systems for image processing applications is the main cause of inefficient execution. In this paper, an efficient workload distribution mechanism for image processing applications is introduced. The proposed approach consists of two phases. In the first phase, image data are divided into an ideal split size and distributed amongst nodes, and in the second phase, image data are further distributed between CPU and GPU according to their computation speeds. Java bindings for OpenCL are used to configure both the CPU and GPU to execute the program. The results have demonstrated that the proposed workload distribution policy efficiently distributes the images in a heterogeneous system for image processing applications and achieves 50% improvements compared to the current state-of-the-art programming frameworks.

Accurate Detection and Quantization of Leaf- Diseases through Soft Computing

2018 ◽  
Vol 1 (1) ◽  
pp. 236-247
Author(s):  
Divya Srivastava ◽  
Rajitha B. ◽  
Suneeta Agarwal
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Agricultural Production ◽  
Bacterial Blight ◽  
Early Stage ◽  
Second Phase ◽  
Computationally Efficient ◽  
Stage Of Disease ◽  
Accurate Detection ◽  
Two Phases

Diseases in leaves can cause the significant reduction in both quality and quantity of agricultural production. If early and accurate detection of disease/diseases in leaves can be automated, then the proper remedy can be taken timely. A simple and computationally efficient approach is presented in this paper for disease/diseases detection on leaves. Only detecting the disease is not beneficial without knowing the stage of disease thus the paper also determine the stage of disease/diseases by quantizing the affected of the leaves by using digital image processing and machine learning. Though there exists a variety of diseases on leaves, but the bacterial and fungal spots (Early Scorch, Late Scorch, and Leaf Spot) are the most prominent diseases found on leaves. Keeping this in mind the paper deals with the detection of Bacterial Blight and Fungal Spot both at an early stage (Early Scorch) and late stage (Late Scorch) on the variety of leaves. The proposed approach is divided into two phases, in the first phase, it identifies one or more disease/diseases existing on leaves. In the second phase, amount of area affected by the disease/diseases is calculated. The experimental results obtained showed 97% accuracy using the proposed approach.

scholarly journals Analysis of Machine Learning Algorithms for Opinion Mining in Different Domains

2018 ◽  
Vol 1 (1) ◽  
pp. 224-234 ◽  
Author(s):  
Donia Gamal ◽  
Marco Alfonse ◽  
El-Sayed M. El-Horbaty ◽  
Abdel-Badeeh M. Salem
Keyword(s):  
Machine Learning ◽  
Language Processing ◽  
Opinion Mining ◽  
Machine Learning Algorithms ◽  
Stochastic Gradient Descent ◽  
Support Vector ◽  
Second Phase ◽  
Adaptive Boosting ◽  
Two Phases ◽  
Textual Content

Sentiment classification (SC) is a reference to the task of sentiment analysis (SA), which is a subfield of natural language processing (NLP) and is used to decide whether textual content implies a positive or negative review. This research focuses on the various machine learning (ML) algorithms which are utilized in the analyzation of sentiments and in the mining of reviews in different datasets. Overall, an SC task consists of two phases. The first phase deals with feature extraction (FE). Three different FE algorithms are applied in this research. The second phase covers the classification of the reviews by using various ML algorithms. These are Naïve Bayes (NB), Stochastic Gradient Descent (SGD), Support Vector Machines (SVM), Passive Aggressive (PA), Maximum Entropy (ME), Adaptive Boosting (AdaBoost), Multinomial NB (MNB), Bernoulli NB (BNB), Ridge Regression (RR) and Logistic Regression (LR). The performance of PA with a unigram is the best among other algorithms for all used datasets (IMDB, Cornell Movies, Amazon and Twitter) and provides values that range from 87% to 99.96% for all evaluation metrics.

Atomic structure of interface of intermetallic compound TiAl and nitride Ti2AIN using HREM and image processing

1991 ◽  
Vol 49 ◽  
pp. 570-571
Author(s):  
E. Sukedai ◽  
H. Mabuchi ◽  
H. Hashimoto ◽  
Y. Nakayama
Keyword(s):  
Mechanical Properties ◽  
Image Processing ◽  
Composite Material ◽  
Intermetallic Compound ◽  
Side Surface ◽  
High Resolution Electron Microscopy ◽  
Hexagonal Structure ◽  
Second Phase ◽  
Resolution Electron ◽  
Compound Tial

In order to improve the mechanical properties of an intermetal1ic compound TiAl, a composite material of TiAl involving a second phase Ti2AIN was prepared by a new combustion reaction method. It is found that Ti2AIN (hexagonal structure) is a rod shape as shown in Fig.1 and its side surface is almost parallel to the basal plane, and this composite material has distinguished strength at elevated temperature and considerable toughness at room temperature comparing with TiAl single phase material. Since the property of the interface of composite materials has strong influences to their mechanical properties, the structure of the interface of intermetallic compound and nitride on the areas corresponding to 2, 3 and 4 as shown in Fig.1 was investigated using high resolution electron microscopy and image processing.

Digital differential hysteresis iimage processing displays what the microscope acquires but the eye can't see

1995 ◽  
Vol 53 ◽  
pp. 642-643
Author(s):  
Klaus-Ruediger Peters
Keyword(s):  
Image Processing ◽  
Visual System ◽  
High Precision ◽  
Image Data ◽  
Processing Technology ◽  
Output Data ◽  
Contrast Resolution ◽  
Pixel Intensity ◽  
Data Reading ◽  
Hysteresis Properties

Differential hysteresis processing is a new image processing technology that provides a tool for the display of image data information at any level of differential contrast resolution. This includes the maximum contrast resolution of the acquisition system which may be 1,000-times higher than that of the visual system (16 bit versus 6 bit). All microscopes acquire high precision contrasts at a level of <0.01-25% of the acquisition range in 16-bit - 8-bit data, but these contrasts are mostly invisible or only partially visible even in conventionally enhanced images. The processing principle of the differential hysteresis tool is based on hysteresis properties of intensity variations within an image.Differential hysteresis image processing moves a cursor of selected intensity range (hysteresis range) along lines through the image data reading each successive pixel intensity. The midpoint of the cursor provides the output data. If the intensity value of the following pixel falls outside of the actual cursor endpoint values, then the cursor follows the data either with its top or with its bottom, but if the pixels' intensity value falls within the cursor range, then the cursor maintains its intensity value.

Information and estimation in image processing

1987 ◽  
Vol 45 ◽  
pp. 14-17
Author(s):  
B. Roy Frieden
Keyword(s):  
Image Processing ◽  
Optical System ◽  
Large Amplitude ◽  
Communication Theory ◽  
Image Data ◽  
Direct Approach ◽  
Ill Posed

Despite the skill and determination of electro-optical system designers, the images acquired using their best designs often suffer from blur and noise. The aim of an “image enhancer” such as myself is to improve these poor images, usually by digital means, such that they better resemble the true, “optical object,” input to the system. This problem is notoriously “ill-posed,” i.e. any direct approach at inversion of the image data suffers strongly from the presence of even a small amount of noise in the data. In fact, the fluctuations engendered in neighboring output values tend to be strongly negative-correlated, so that the output spatially oscillates up and down, with large amplitude, about the true object. What can be done about this situation? As we shall see, various concepts taken from statistical communication theory have proven to be of real use in attacking this problem. We offer below a brief summary of these concepts.

Representação e simbolismo: artes visuais na fronteira Brasil/Bolívia

2020 ◽  
Vol 4 (3) ◽  
pp. 286
Author(s):  
Paulo César Antonini de Souza ◽  
Derick Trindade Bezerra
Keyword(s):  
Visual Arts ◽  
Social Order ◽  
Research Field ◽  
Border Region ◽  
Second Phase ◽  
Two Dimensional ◽  
Santa Cruz ◽  
Cultural Conditions ◽  
Two Phases ◽  
America Latina

ResumoTendo por campo de investigação o Festival da América do Sul Pantanal (FASP) em 2018, na cidade de Corumbá (Brasil), objetiva-se identificar a materialidade e conceitos que permeiam as manifestações artísticas bidimensionais nesta região de fronteira, a partir da percepção de artistas da Bolívia. A pesquisa se organizou em duas fases: na primeira foi realizado um levantamento em plataformas online de produções acadêmicas em artes visuais, com foco no trabalho bidimensional, utilizando os descritores “arte popular” e “estética latina” resultando em três artigos. Na segunda fase foram selecionados dois trabalhos de uma artista da Bolívia, participante da mostra “Conexão Santa Cruz”, realizada durante o FASP 2018, que foram analisados em seus níveis representacional e simbólico. Pela interpretação das imagens foi possível construir uma leitura sobre a perspectiva da artista a respeito de suas condições culturais dentro da ordenação social em que se encontra situada.Palavras-chave: Artes Visuais. Arte Popular. Arte Regional. América Latina. Representation and symbolism: visual arts on the Brazil/Bolivia frontierAbstractHaving as research field the Festival da América do Sul Pantanal (FASP) in 2018, in the city of Corumbá (Brazil), the objective is to identify the materiality and concepts that permeate the two-dimensional artistic manifestations in this border region, from the perception of artists from Bolivia. The research was organized in two phases: in the first, a survey was carried out on online platforms of academic productions in visual arts, focusing on two-dimensional work, using the descriptors “arte popular” and “estética latina” resulting in three articles. In the second phase, two works were selected by an artist from Bolivia, participating in the exhibition “Conexão Santa Cruz”, held during FASP 2018, which were analyzed at their representational and symbolic levels. Through the interpretation of the images, it was possible to construct a reading on the artist’s perspective regarding her cultural conditions within the social order in which she is located.Keywords: Visual Arts. Folk Art. Regional Art. Latin America.Representación y simbolismo: artes visuales en la frontera de Brasil/BoliviaResumenTeniendo como campo de investigación el Festival de Sudamérica Pantanal (FASP) en 2018, en la ciudad de Corumbá (Brasil), el objetivo es identificar la materialidad y conceptos que permean las manifestaciones artísticas bidimensionales en esta región fronteriza, desde la percepción de artistas de Bolivia. La investigación se organizó en dos fases: en la primera, se realizó una encuesta en plataformas online de producciones académicas en artes visuales, con foco en el trabajo bidimensional, utilizando los descriptores “arte popular” y “estética latina” dando como resultado tres artículos. En la segunda fase, dos obras fueron seleccionadas por un artista de Bolivia, participante de la exposición “Conexão Santa Cruz”, realizada durante FASP 2018, que fueron analizadas en sus niveles representativos y simbólicos. A través de la interpretación de las imágenes, fue posible construir una lectura sobre la perspectiva de la artista sobre sus condiciones culturales dentro del orden social en el que se ubica.Palabras clave: Artes Visuales. Arte Popular. Arte Regional. América Latina.

scholarly journals Development and validation of a short version of the Sarcopenia Quality of Life questionnaire: the SF-SarQoL

2021 ◽  
Author(s):  
A. Geerinck ◽  
C. Beaudart ◽  
J.-Y. Reginster ◽  
M. Locquet ◽  
C. Monseur ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Short Form ◽  
Reduction Process ◽  
Community Dwelling ◽  
Short Version ◽  
Second Phase ◽  
Life Questionnaire ◽  
Quality Of Life Questionnaire ◽  
Two Phases

Abstract Purpose To facilitate the measurement of quality of life in sarcopenia, we set out to reduce the number of items in the previously validated Sarcopenia Quality of Life (SarQoL®) questionnaire, and to evaluate the clinimetric properties of this new short form. Methods The item reduction process was carried out in two phases. First, information was gathered through item-impact scores from older people (n = 1950), a Delphi method with sarcopenia experts, and previously published clinimetric data. In the second phase, this information was presented to an expert panel that decided which of the items to include in the short form. The newly created SFSarQoL was then administered to older, community-dwelling participants who previously participated in the SarcoPhAge study. We examined discriminative power, internal consistency, construct validity, test–retest reliability, structural validity and examined item parameters with a graded response model (IRT). Results The questionnaire was reduced from 55 to 14 items, a 75% reduction. A total of 214 older, community-dwelling people were recruited for the validation study. The clinimetric evaluation showed that the SF-SarQoL® can discriminate on sarcopenia status [EWGSOP2 criteria; 34.52 (18.59–43.45) vs. 42.86 (26.56–63.69); p = 0.043], is internally consistent (α = 0.915, ω = 0.917) and reliable [ICC = 0.912 (0.847–0.942)]. A unidimensional model was fitted (CFI = 0.978; TLI = 0.975; RMSEA = 0.108, 90% CI 0.094–0.123; SRMR = 0.055) with no misfitting items and good response category separation. Conclusions A new, 14-item, short form version of the Sarcopenia Quality of Life questionnaire has been developed and shows good clinimetric properties.

scholarly journals SWIPT in mMIMO system with non-linear energy-harvesting terminals: protocol design and performance optimization

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Kui Xu ◽  
Ming Zhang ◽  
Jie Liu ◽  
Nan Sha ◽  
Wei Xie ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Performance Optimization ◽  
Power Transmission ◽  
Base Station ◽  
Second Phase ◽  
Wireless Power ◽  
Half Duplex ◽  
Non Linear ◽  
Two Phases ◽  
And Performance

Abstract In this paper, we design the simultaneous wireless information and power transfer (SWIPT) protocol for massive multi-input multi-output (mMIMO) system with non-linear energy-harvesting (EH) terminals. In this system, the base station (BS) serves a set of uplink fixed half-duplex (HD) terminals with non-linear energy harvester. Considering the non-linearity of practical energy-harvesting circuits, we adopt the realistic non-linear EH model rather than the idealistic linear EH model. The proposed SWIPT protocol can be divided into two phases. The first phase is designed for terminals EH and downlink training. A beam domain energy beamforming method is employed for the wireless power transmission. In the second phase, the BS forms the two-layer receive beamformers for the reception of signals transmitted by terminals. In order to improve the spectral efficiency (SE) of the system, the BS transmit power- and time-switching ratios are optimized. Simulation results show the superiority of the proposed beam-domain SWIPT protocol on SE performance compared with the conventional mMIMO SWIPT protocols.

scholarly journals Development and Evaluation of Direct Paddy Seeder in Puddled Field

2021 ◽  
Vol 13 (5) ◽  
pp. 2745
Author(s):  
Manoj Kumar ◽  
Ritu Dogra ◽  
Mahesh Narang ◽  
Manjit Singh ◽  
Sushant Mehan
Keyword(s):  
Laboratory Testing ◽  
Field Evaluation ◽  
Row Spacing ◽  
Second Phase ◽  
Cell Type ◽  
Inclined Plate ◽  
Seed Damage ◽  
Two Phases ◽  
Almost All ◽  
Different Soils

Manual transplanting, a pre-dominant practice in almost all the paddy growing areas in India, is laborious, burdensome, and has many expenses on raising, settling, and transplanting nursery. The transplanting process’s limitations motivated the replacement of conventional paddy transplanting methods. The study was divided into two phases. The first phase included laboratory testing of three levels of metering mechanisms, namely cell type (M1) with 10 cells grooved around a circular plate having a 13 cm diameter, inclined plate (M2) containing 24 U shaped cells provided on an 18 cm diameter plate, and fluted roller (M3) with 10 flutes on a 5 cm diameter shaft. The testing matrix included a missing index, multiple index, and seed damage with forward speeds (2.5, 3.0, and 3.5 km/h), and pre-germination levels of 24 h soaked (P1), 24 h pre-germinated (P2), and 36 h pre-germinated paddy seeds (P3)). The second phase included selecting the best combination obtained from the laboratory study and developing a new efficient planter for the puddled field. The inclined plate metering mechanism operating at 2.5 km/h for 24 h pre-germinated seeds was reported most efficient from the first phase. Therefore, a self-propelled 8-row planter equipped with an inclined plate metering mechanism having a row-to-row spacing of 22.5 cm was developed, fabricated, and evaluated in the puddled field. The designed planter was assessed on two different soils: sandy loom (ST1) and clay loom (ST2) and at two different hopper fill levels as ½ filled hopper (F1) and ¾ filled hopper (F2). The number of plants per square meter and hill-to-hill spacing was measured. The on-field evaluation revealed that the number of plants per square meter was non-significantly affected by the type of soil but was significantly affected by hopper fill.

scholarly journals XCOVNet: Chest X-ray Image Classification for COVID-19 Early Detection Using Convolutional Neural Networks

2021 ◽  
Author(s):  
Vishu Madaan ◽  
Aditya Roy ◽  
Charu Gupta ◽  
Prateek Agrawal ◽  
Anand Sharma ◽  
...  
Keyword(s):  
Image Classification ◽  
Second Phase ◽  
Two Phase ◽  
X Ray ◽  
The Neural Network ◽  
Rapid Spread ◽  
Chest X Ray ◽  
Polymerase Chain ◽  
Two Phases ◽  
Active Patients

AbstractCOVID-19 (also known as SARS-COV-2) pandemic has spread in the entire world. It is a contagious disease that easily spreads from one person in direct contact to another, classified by experts in five categories: asymptomatic, mild, moderate, severe, and critical. Already more than 66 million people got infected worldwide with more than 22 million active patients as of 5 December 2020 and the rate is accelerating. More than 1.5 million patients (approximately 2.5% of total reported cases) across the world lost their life. In many places, the COVID-19 detection takes place through reverse transcription polymerase chain reaction (RT-PCR) tests which may take longer than 48 h. This is one major reason of its severity and rapid spread. We propose in this paper a two-phase X-ray image classification called XCOVNet for early COVID-19 detection using convolutional neural Networks model. XCOVNet detects COVID-19 infections in chest X-ray patient images in two phases. The first phase pre-processes a dataset of 392 chest X-ray images of which half are COVID-19 positive and half are negative. The second phase trains and tunes the neural network model to achieve a 98.44% accuracy in patient classification.

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