Search results for: blue color detection

Authors: Suphat Rittirat, Sutha Klaocheed, Somporn Prasertsongskun, Kanchit Thammasiri

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Protocorms of Phalaenopsis cornu-cervi (Breda) Blume & Rchb. f. were successfully cryopreserved using a vitrification method. Two-month old protocorms at GI 4 stage were precultured in liquid MS medium supplemented with different concentrations of sucrose (0.3, 0.5, 0.7, 0.9 and 1.2 M) at 25±1°C for 2 days on an orbital shaker at 110 rpm. The protocorms were treated with loading solution (2 M glycerol plus 0.4 M sucrose) for 20 minutes at 25±1°C. Then, the protocorms were sufficiently dehydrated with vitrification solution (plant vitrification solution 2, PVS2) for various times (0, 30, 60, 90 and 120 minutes) at 25±1°C and stored in liquid nitrogen for 1 day. After rapid thawing in water bath at 40°C for 2 minutes, the explants were washed by MS liquid medium containing 0.5 ml of 1.2 M sucrose for 20 minutes. The results shown that the protocorms were precultured in liquid MS medium containing 0.5 M sucrose and dehydrated with vitrification solution for 60 minutes had the highest survival percentage of protocorm at 31±1.0 % as measured by Evan’s blue. No survival rate of protocorms was found without vitrification treatments.

Keywords: protocorms, cryopreservation, Phalaenopsis cornu-cervi, vitrification

Procedia PDF Downloads 363

Authors: Zainab Yasir Al-Rekaby, Abdul Jalil M. Khalaf

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Coloring the vertices of a graph such that every two adjacent vertices have different color is a very common problem in the graph theory. This is known as proper coloring of graphs. The possible number of different proper colorings on a graph with a given number of colors can be represented by a function called the chromatic polynomial. Two graphs G and H are said to be chromatically equivalent, if they share the same chromatic polynomial. A Graph G is chromatically unique, if G is isomorphic to H for any graph H such that G is chromatically equivalent to H. The study of chromatically equivalent and chromatically unique problems is called chromaticity. This paper shows that a wheel W14 is chromatically unique.

Keywords: chromatic polynomial, chromatically Equivalent, chromatically unique, wheel

Procedia PDF Downloads 414

Authors: N. Ouslimani, M. T. Abadlia, S. Yakoub, F. Tebbani

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Water has always been synonymous with life and growth. Blue gold is first essential to the survival of the human being whose body consists of more than 65% with the development of industrialization and consumption patterns; volumes of wastewater discharges have increased considerably whether industrial or domestic, waste water must be purified before discharge. Treatment, therefore, aims to reduce the pollution load which contain. The resources in Algeria are limited and unevenly distributed. Thus, to meet all the water needs of the country and to preserve the waters of good quality drinking water supply, one solution would be to use them according to their quality and to irrigate crops for the food or be directed to the irrigation of green areas or sports complex. The purification performance of this STEP has been established since the pH analyzed pollution criteria (7.36) and temperature (16°C), MES (10 mg / l), electrical conductivity (1122 / µs / cm), DBO5 (6mg / l), DCO (15mg / l) meet the discharge standards. Arguably the purified water discharged out of the boumerdes STEP comply with Algerian regulations and can be reused in agriculture. COD biodegradability of the coefficient / BOD5 is 2.5 (less than 3) indicates that of the effluent are biodegradable hence their urban origin.

Keywords: irrigation, recovery, treated, wastewater

Procedia PDF Downloads 253

Authors: Can Mungan, Gokhan Kilic

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Structural engineers and tunnel owners have good reason to attach importance to the assessment and inspection of tunnels. Regular inspection is necessary to maintain and monitor the health of the structure not only at the present time but throughout its life cycle. Detection of flaws within the structure, such as corrosion and the formation of cracks within the internal elements of the structure, can go a long way to ensuring that the structure maintains its integrity over the course of its life. Other issues that may be detected earlier through regular assessment include tunnel surface delamination and the corrosion of the rebar. One advantage of new technology such as the ground penetrating radar (GPR) is the early detection of imperfections. This study will aim to discuss and present the effectiveness of GPR as a tool for assessing the structural integrity of the heavily used tunnel. GPR is used with various antennae in frequency and application method (2 GHz and 500 MHz GPR antennae). The paper will attempt to produce a greater understanding of structural defects and identify the correct tool for such purposes. Conquest View with 3D scanning capabilities was involved throughout the analysis, reporting, and interpretation of the results. This study will illustrate GPR mapping and its effectiveness in providing information of value when it comes to rebar position (lower and upper reinforcement). It will also show how such techniques can detect structural features that would otherwise remain unseen, as well as moisture ingress.

Keywords: tunnel, GPR, health monitoring, moisture ingress, rebar position

Procedia PDF Downloads 119

Authors: Bashir Ahmad Aasim, Abdul Khaliq Karimi, Jun Tomiyama

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Material aging is one of the vital issues among all the civil, mechanical, and aerospace engineering societies. Sustenance and reliability of concrete, which is the widely used material in the world, is the focal point in civil engineering societies. For few decades, researchers have been able to present some form algorithms that could lead to evaluate a structure globally rather than locally without harming its serviceability and traffic interference. The algorithms could help presenting different methods for evaluating structures non-destructively. In this paper, a non-destructive vibration-based damage detection method is adopted to evaluate two concrete beams, one being in a healthy state while the second one contains a crack on its bottom vicinity. The study discusses that damage in a structure affects modal parameters (natural frequency, mode shape, and damping ratio), which are the function of physical properties (mass, stiffness, and damping). The assessment is carried out to acquire the natural frequency of the sound beam. Next, the vibration response is recorded from the cracked beam. Eventually, both results are compared to know the variation in the natural frequencies of both beams. The study concludes that damage can be detected using vibration characteristics of a structural member considering the decline occurred in the natural frequency of the cracked beam.

Keywords: concrete beam, natural frequency, non-destructive testing, vibration characteristics

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Authors: Tarek Dandashi

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WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

Procedia PDF Downloads 262

Authors: Farmesk Abubaker, Francesco Tortorici, Marco Capogni, Concetta Sutera, Vincenzo Bellini

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This project concerns with the detection efficiency of the portable triple-to-double coincidence ratio (TDCR) at the National Institute of Metrology of Ionizing Radiation (INMRI-ENEA) which allows direct activity measurement and radionuclide standardization for pure-beta emitter or pure electron capture radionuclides. The dependency of the simulated detection efficiency of the TDCR, by using Monte Carlo simulation Geant4 code, on the Birks factor (kB) and defocusing parameter has been examined especially for low energy beta-emitter radionuclides such as 3H and 14C, for which this dependency is relevant. The results achieved in this analysis can be used for selecting the best kB factor and the defocusing parameter for computing theoretical TDCR parameter value. The theoretical results were compared with the available ones, measured by the ENEA TDCR portable detector, for some pure-beta emitter radionuclides. This analysis allowed to improve the knowledge of the characteristics of the ENEA TDCR detector that can be used as a traveling instrument for in-situ measurements with particular benefits in many applications in the field of nuclear medicine and in the nuclear energy industry.

Keywords: Birks constant, defocusing parameter, GEANT4 code, TDCR parameter

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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Authors: M. M. Ali, Ahmed Al- Ani, Derek Eamus, Daniel K. Y. Tan

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In this glasshouse study, we developed the new image-based non-destructive technique for detecting leaf P status of different crops such as cotton, tomato and lettuce. Plants were allowed to grow on nutrient media containing different P concentrations, i.e. 0%, 50% and 100% of recommended P concentration (P0 = no P, L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P as NaH2PO4). After 10 weeks of growth, plants were harvested and data on leaf P contents were collected using the standard destructive laboratory method and at the same time leaf images were collected by a handheld crop image sensor. We calculated leaf area, leaf perimeter and RGB (red, green and blue) values of these images. This data was further used in the linear discriminant analysis (LDA) to estimate leaf P contents, which successfully classified these plants on the basis of leaf P contents. The data indicated that P deficiency in crop plants can be predicted using the image and morphological data. Our proposed non-destructive imaging method is precise in estimating P requirements of different crop species.

Keywords: image-based techniques, leaf area, leaf P contents, linear discriminant analysis

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Authors: Saleh H. Abud, Z. Hassan, F. K. Yam

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Characteristics of MSM photodetector based on a porous In0.08Ga0.92N thin film were reported. Nanoporous structures of n-type In0.08Ga0.92N/AlN/Si thin films were synthesized by photoelectrochemical (PEC) etching at a ratio of 1:4 of HF:C2H5OH solution for 15 min. The structural and optical properties of pre- and post-etched thin films were investigated. Field emission scanning electron microscope and atomic force microscope images showed that the pre-etched thin film has a sufficiently smooth surface over a large region and the roughness increased for porous film. Blue shift has been observed in photoluminescence emission peak at 300 K for porous sample. The photoluminescence intensity of the porous film indicated that the optical properties have been enhanced. A high work function metals (Pt and Ni) were deposited as a metal contact on the porous films. The rise and recovery times of the devices were investigated at 390 nm chopped light. Finally, the sensitivity and quantum efficiency were also studied.

Keywords: porous InGaN, photoluminescence, SMS photodetector, atomic force microscopy

Procedia PDF Downloads 489

Authors: Shizra Waris, Bilal Shoaib, Munib Ahmad

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Background; The using of clinical decision support systems (CDSSs) may recover unceasing disease organization, which requires regular visits to multiple health professionals, treatment monitoring, disease control, and patient behavior modification. The objective of this survey is to determine if these CDSSs improve the processes of unceasing care including diagnosis, treatment, and monitoring of diseases. Though artificial intelligence is not a new idea it has been widely documented as a new technology in computer science. Numerous areas such as education business, medical and developed have made use of artificial intelligence Methods: The survey covers articles extracted from relevant databases. It uses search terms related to information technology and viral hepatitis which are published between 2000 and 2016. Results: Overall, 80% of studies asserted the profit provided by information technology (IT); 75% of learning asserted the benefits concerned with medical domain;25% of studies do not clearly define the added benefits due IT. The CDSS current state requires many improvements to hold up the management of liver diseases such as HCV, liver fibrosis, and cirrhosis. Conclusion: We concluded that the planned model gives earlier and more correct calculation of hepatitis B and it works as promising tool for calculating of custom hepatitis B from the clinical laboratory data.

Keywords: detection, hapataties, observation, disesese

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Authors: J. J. Rickard, A. Belli, P. Goldberg Oppenheimer

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Medical diagnostics, environmental monitoring, homeland security and forensics increasingly demand specific and field-deployable analytical technologies for quick point-of-care diagnostics. Although technological advancements have made optical methods well-suited for miniaturization, a highly-sensitive detection technique for minute sample volumes is required. Raman spectroscopy is a well-known analytical tool, but has very weak signals and hence is unsuitable for trace level analysis. Enhancement via localized optical fields (surface plasmons resonances) on nanoscale metallic materials generates huge signals in surface-enhanced Raman scattering (SERS), enabling single molecule detection. This enhancement can be tuned by manipulation of the surface roughness and architecture at the sub-micron level. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for SERS-based sensing devices. While most SERS substrates are manufactured by conventional lithographic methods, the development of a cost-effective approach to create nanostructured surfaces is a much sought-after goal in the SERS community. Here, a method is established to create controlled, self-organized, hierarchical nanostructures using electrohydrodynamic (HEHD) instabilities. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements. HEHD pattern formation enables the fabrication of multiscale 3D structured arrays as SERS-active platforms. Importantly, each of the HEHD-patterned individual structural units yield a considerable SERS enhancement. This enables each single unit to function as an isolated sensor. Each of the formed structures can be effectively tuned and tailored to provide high SERS enhancement, while arising from different HEHD morphologies. The HEHD fabrication of sub-micrometer architectures is straightforward and robust, providing an elegant route for high-throughput biological and chemical sensing. The superior detection properties and the ability to fabricate SERS substrates on the miniaturized scale, will facilitate the development of advanced and novel opto-fluidic devices, such as portable detection systems, and will offer numerous applications in biomedical diagnostics, forensics, ecological warfare and homeland security.

Keywords: hierarchical electrohydrodynamic patterning, medical diagnostics, point-of care devices, SERS

Procedia PDF Downloads 345

Authors: Tahir Iqbal, Mumtaz Ali, Syed Wajahat Kareem, Muhammad Harris

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Digital information is expanding in exponential order in our life. Information that is residing online and offline are stored in huge repositories relating to every aspect of our lives. Getting the required information is a task of retrieval systems. Content based image retrieval (CBIR) is a retrieval system that retrieves the required information from repositories on the basis of the contents of the image. Time is a critical factor in retrieval system and using indexed views with CBIR system improves the time efficiency of retrieved results.

Keywords: content based image retrieval (CBIR), indexed view, color, image retrieval, cross correlation

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Authors: Salim Ahmed

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In many countries, water pollution from industrial effluents is a real problem. It may have a negative impact on the environment. To minimize the adverse effects of these contaminants, various methods are used to improve effluent purification, including physico-chemical processes such as adsorption.The present study focuses on applying a naturally biodegradable adsorbent based on argan (southern Morocco) in a physico-chemical adsorption process to reduce the harmful effects of pollutants on the environment. Tests were carried out with the cationic dye methylene blue (MB) and revealed that removal is significantly higher within the first 15 minutes. The parameters studied in this study are adsorbent mass and concentration. The Freundlich model provides an excellent example of the adsorption phenomenon of BMs over argan powder. The results of this study show that argan kernels are a highly beneficial alternative for local communities, as they help to achieve a triple objective: pollution reduction, waste recovery and water recycling.

Keywords: environmental protection, activated carbon, water treatment, adsorption

Procedia PDF Downloads 62

Authors: A. I. Khalafalla, K. A. Al-Busada, I. M. El-Sabagh

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Pox and pox-like diseases of camels are a group of exanthematous skin conditions that have become increasingly important economically. They may be caused by three distinct viruses: camelpox virus (CMPV), camel contagious ecthyma virus (CCEV) and camel papillomavirus (CAPV). These diseases are difficult to differentiate based on clinical presentation in disease outbreaks. Molecular methods such as PCR targeting species-specific genes have been developed and used to identify CMPV and CCEV, but not simultaneously in a single tube. Recently, multiplex PCR has gained reputation as a convenient diagnostic method with cost- and time–saving benefits. In the present communication, we describe the development, optimization and validation a multiplex PCR assays able to detect simultaneously the genome of the three viruses in one single test allowing for rapid and efficient molecular diagnosis. The assay was developed based on the evaluation and combination of published and new primer sets, and was applied to the detection of 110 tissue samples. The method showed high sensitivity, and the specificity was confirmed by PCR-product sequencing. In conclusion, this rapid, sensitive and specific assay is considered a useful method for identifying three important viruses in specimens from camels and as part of a molecular diagnostic regime.

Keywords: multiplex PCR, diagnosis, pox and pox-like diseases, camels

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Authors: Abdulsalam M. Alhawsawi

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Estimation of a radiation detector's efficiency plays a significant role in calculating the activity of radioactive samples. Detector efficiency is measured using sources that emit a variety of energies from low to high-energy photons along the energy spectrum. Some photon energies are hard to find in lab settings either because check sources are hard to obtain or the sources have short half-lives. This work aims to develop a method to determine the efficiency of a High Purity Germanium Detector (HPGe) based on the 662 keV gamma ray photon emitted from Cs-137. Cesium-137 is readily available in most labs with radiation detection and health physics applications and has a long half-life of ~30 years. Several photon efficiencies were calculated using the MCNP5 simulation code. The simulated efficiency of the 662 keV photon was used as a base to calculate other photon efficiencies in a point source and a Marinelli Beaker form. In the Marinelli Beaker filled with water case, the efficiency of the 59 keV low energy photons from Am-241 was estimated with a 9% error compared to the MCNP5 simulated efficiency. The 1.17 and 1.33 MeV high energy photons emitted by Co-60 had errors of 4% and 5%, respectively. The estimated errors are considered acceptable in calculating the activity of unknown samples as they fall within the 95% confidence level.

Keywords: MCNP5, MonteCarlo simulations, efficiency calculation, absolute efficiency, activity estimation, Cs-137

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Authors: Moulay Smaïne Ghembaza, Mokhtar Dadouch, Nour-Said Ikhlef

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Soil treatment is to make use soil that does not have the characteristics required in a given context. We limit ourselves in this work to the field of road earthworks where we have chosen to develop a local material in the region of Sidi Bel Abbes (Algeria). This material has poor characteristics not meeting the standards used in road geo technics. To remedy this, firstly, we were trying to improve the Proctor Standard characteristics of this material by mechanical treatment increasing the compaction energy. Then, by a chemical treatment, adding some cement dosages, our results show that this material classified A1h a increase maximum dry density and a reduction in the water content of compaction. A comparative study is made on the optimal properties of the material between the two modes of treatment. On the other hand, after treatment, one finds a decrease in the plasticity index and the methylene blue value. This material exhibits a change of class. Therefore, soil class CL turned into a soil class composed CL-ML (Silt of low plasticity). This observation allows this material to be used as backfill or sub grade.

Keywords: treatment of soil, cement, subgrade, Atteberg limits, classification, optimum proctor properties

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Authors: Abdulrahman Algaeed

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The Ophthalmic Ultrasound is the easiest method of early diagnosing Retinoblastoma after clinical examination. It can be done with ease without sedation. King Khaled Eye Specialist Hospital is a tertiary care center where Retinoblastoma patients are often seen and treated there. The first modality to rule out the disease is Ophthalmic Ultrasound. Classic Retinoblastoma is easily diagnosed by using the conventional 10MHz Ophthalmic Ultrasound probe in the regular clinic setup. Retinal lesion with multiple, very highly reflective surfaces within lesion typical of Calcium deposits. The use of Standardized A-scan is very useful where internal reflectivity is classified as very highly reflective. Color Doppler is extremely useful as well to show the blood flow within lesion/s. In conclusion: Ophthalmic Ultrasound should be the first tool to be used to diagnose Retinoblastoma after clinical examination. The accuracy of the Exam is very high.

Keywords: doppler, retinoblastoma, reflectivity, ultrasound

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: Brittany Richardson, Ying Wang

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For physical therapy, exercise prescription, athlete training, and regular fitness training, it is crucial to perform health assessments or fitness assessments periodically. An accurate assessment is propitious for tracking recovery progress, preventing potential injury and making long-range training plans. Assessments include necessary measurements, height, weight, blood pressure, heart rate, body fat, etc. and advanced evaluation, muscle group strength, stability-mobility, and movement evaluation, etc. In the current standard assessment procedures, the accuracy of assessments, especially advanced evaluations, largely depends on the experience of physicians, coaches, and personal trainers. And it is challenging to track clients’ progress in the current assessment. Unlike the tradition assessment, in this paper, we present a deep learning based face recognition algorithm for accurate, comprehensive and trackable assessment. Based on the result from our assessment, physicians, coaches, and personal trainers are able to adjust the training targets and methods. The system categorizes the difficulty levels of the current activity for the client or user, furthermore make more comprehensive assessments based on tracking muscle group over time using a designed landmark detection method. The system also includes the function of grading and correcting the form of the clients during exercise. Experienced coaches and personal trainer can tell the clients' limit based on their facial expression and muscle group movements, even during the first several sessions. Similar to this, using a convolution neural network, the system is trained with people’s facial expression to differentiate challenge levels for clients. It uses landmark detection for subtle changes in muscle groups movements. It measures the proximal mobility of the hips and thoracic spine, the proximal stability of the scapulothoracic region and distal mobility of the glenohumeral joint, as well as distal mobility, and its effect on the kinetic chain. This system integrates data from other fitness assistant devices, including but not limited to Apple Watch, Fitbit, etc. for a improved training and testing performance. The system itself doesn’t require history data for an individual client, but the history data of a client can be used to create a more effective exercise plan. In order to validate the performance of the proposed work, an experimental design is presented. The results show that the proposed work contributes towards improving the quality of exercise plan, execution, progress tracking, and performance.

Keywords: exercise prescription, facial recognition, landmark detection, fitness assessments

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Authors: Ghodbane Azeddine, Saad Maarouf, Boland Jean-Francois, Thibeault Claude

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This paper proposes a new design of an active fault-tolerant flight control system against abrupt actuator faults. This overall system combines a multiple time scale sliding mode controller for fault compensation and a geometric approach for fault detection and diagnosis. The proposed control system is able to accommodate several kinds of partial and total actuator failures, by using available healthy redundancy actuators. The overall system first estimates the correct fault information using the geometric approach. Then, and based on that, a new reconfigurable control law is designed based on the multiple time scale sliding mode technique for on-line compensating the effect of such faults. This approach takes advantages of the fact that there are significant difference between the time scales of aircraft states that have a slow dynamics and those that have a fast dynamics. The closed-loop stability of the overall system is proved using Lyapunov technique. A case study of the non-linear model of the F16 fighter, subject to the rudder total loss of control confirms the effectiveness of the proposed approach.

Keywords: actuator faults, fault detection and diagnosis, fault tolerant flight control, sliding mode control, multiple time scale approximation, geometric approach for fault reconstruction, lyapunov stability

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Authors: Khalid Alhudaib

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Potato is considered as one of the most important and potential vegetable crops in Saudi Arabia. Alfalfa mosaic virus (AMV), genus Alfamovirus, family Bromoviridae is among the broad spread of viruses in potato. During spring and fall growing seasons of potato in 2015 and 2016, several field visits were conducted in the four major growing areas of potato cultivation (Riyadh-Qaseem-Hail-Hard). The presence of AMV was detected in samples using ELISA, dot blot hybridization and/or RT-PCR. The highest occurrence of AMV was observed as 18.6% in Qaseem followed by Riyadh with 15.2% while; the lowest infection rates were recorded in Hard and Hail, 8.3 and 10.4%, respectively. The sequences of seven isolates of AMV obtained in this study were determined and the sequences were aligned with the other sequences available in the GenBank database. Analyses confirmed the low variability among AMV isolated in this study, which means that all AMV isolates may originate from the same source. Due to high incidence of AMV, other economic susceptible crops may become affected by high incidence of this virus in potato crops. This requires accurate examination of potato seed tubers to prevent the spread of the virus in Saudi Arabia. The obtained results indicated that the hybridization and ELISA are suitable techniques in the routine detection of AMV in a large number of samples while RT-PCR is more sensitive and essential for molecular characterization of AMV.

Keywords: Alfamovirus, AMV, Alfalfa mosaic virus, PCR, potato

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Authors: Saeed Asiri

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The Novel Automated System (NAS) has the control system of the level of chlorine and acid (i.e. pH level) through a feedback in three forms of synchronous alerts. The feedback is in the form of an alert voice, a visible color, and a message on a digital screen. In addition, NAS contains a slide-in container in which chemicals are used to treat the problems of chlorine and acid levels independently. Moreover, NAS has a net in front of it to clean the pool on the surface of the water from leaves and wastes and so on which is controlled through a remote control. The material used is a lightweight aluminum with mechanical and electric parts integrated with each other. In fact, NAS is qualified to serve as an assistant security guard for swimming pools because it has the characteristics that make it unique and smart.

Keywords: novel automated system, pool safety, maintenance, pH level, digital screen

Procedia PDF Downloads 71

Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Madhushi Bandara, Dharshana Kasthurirathna, Danaja Maldeniya, Mahendra Piraveenan

Abstract:

Community detection is an extremely useful technique in understanding the structure and function of a social network. Louvain algorithm, which is based on Newman-Girman modularity optimization technique, is extensively used as a computationally efficient method extract the communities in social networks. It has been suggested that the nodes that are in close geographical proximity have a higher tendency of forming communities. Variants of the Newman-Girman modularity measure such as dist-modularity try to normalize the effect of geographical proximity to extract geographically dispersed communities, at the expense of losing the information about the geographically proximate communities. In this work, we propose a method to extract geographically dispersed communities while preserving the information about the geographically proximate communities, by analyzing the ‘community network’, where the centroids of communities would be considered as network nodes. We suggest that the inter-community link strengths, which are normalized over the community sizes, may be used to identify and extract the ‘overlay communities’. The overlay communities would have relatively higher link strengths, despite being relatively apart in their spatial distribution. We apply this method to the Gowalla online social network, which contains the geographical signatures of its users, and identify the overlay communities within it.

Keywords: social networks, community detection, modularity optimization, geographically dispersed communities

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Authors: Peter Modregger, Özgül Öztürk

Abstract:

Glass fabric reinforced thermoplastic (GFRT) are composite materials, which combine low weight and resilient mechanical properties rendering them especially suitable for automobile construction. However, defects in the glass fabric as well as in the polymer matrix can occur during manufacturing, which may compromise component lifetime or even safety. One type of these defects is local fiber shifts, which can be difficult to detect. Recently, we have experimentally demonstrated the reliable detection of local fiber shifts by X-ray scattering based on the edge-illumination (EI) principle. EI constitutes a novel X-ray imaging technique that utilizes two slit masks, one in front of the sample and one in front of the detector, in order to simultaneously provide absorption, phase, and scattering contrast. The principle of contrast formation is as follows. The incident X-ray beam is split into smaller beamlets by the sample mask, resulting in small beamlets. These are distorted by the interaction with the sample, and the distortions are scaled up by the detector masks, rendering them visible to a pixelated detector. In the experiment, the sample mask is laterally scanned, resulting in Gaussian-like intensity distributions in each pixel. The area under the curves represents absorption, the peak offset refraction, and the width of the curve represents the scattering occurring in the sample. Here, scattering is caused by the numerous glass fiber/polymer matrix interfaces. In our recent publication, we have shown that the standard deviation of the absorption and scattering values over a selected field of view can be used to distinguish between intact samples and samples with local fiber shift defects. The quantification of defect detection performance was done by using p-values (p=0.002 for absorption and p=0.009 for scattering) and contrast-to-noise ratios (CNR=3.0 for absorption and CNR=2.1 for scattering) between the two groups of samples. This was further improved for the scattering contrast to p=0.0004 and CNR=4.2 by utilizing a harmonic decomposition analysis of the images. Thus, we concluded that local fiber shifts can be reliably detected by the X-ray scattering contrasts provided by EI. However, a potential application in, for example, production monitoring requires fast data acquisition times. For the results above, the scanning of the sample masks was performed over 50 individual steps, which resulted in long total scan times. In this paper, we will demonstrate that reliable detection of local fiber shift defects is also possible by using single images, which implies a speed up of total scan time by a factor of 50. Additional performance improvements will also be discussed, which opens the possibility for real-time acquisition. This contributes a vital step for the translation of EI to industrial applications for a wide variety of materials consisting of numerous interfaces on the micrometer scale.

Keywords: defects in composites, X-ray scattering, local fiber shifts, X-ray edge Illumination

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Authors: Feddal Imene, Boumediene Youssra, Mimanne Goussem

Abstract:

The history of the environment and its chemistry is above all the history of its pollution. For a large part, it is the changes made in the air, water and soil by human beings. From there, we can define that pollution is an unfavorable modification of the natural environment that appears as a by-product of human action, through direct and indirect effects. The protection and preservation of the environment is one of the pillars of sustainable development, which is currently a major issue for the future of man and the planet. Currently, humanity is facing an alarming increase in the pollution of the natural environment by various organic or inorganic materials. The objective of our work is to study the adsorption of a textile dye which is known in the industrial environment, methyl green, on raw calcic clay. Our material was characterized by X-ray diffraction (XRD) Fourier transform infrared (FTIR), we also determined its cation exchange capacity (CEC), pHzc and specific surface by Methylene Blue method. The kinetic and thermodynamic study of the adsorption of methyl green was studied, these experiments resulted that the adsorption of the dye follows pseudo second order kinetics, and according to the thermodynamic study and the study of the probability we can say that we have a physisorption.

Keywords: calcic clay, dye, materials, environment

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Authors: Djamila Aboutaleb, Brahim Safi

Abstract:

In this paper, sodium borosilicates glasses were prepared by melting in air. These heat-resistant transparent glasses have subjected subsequently isothermal treatments at different times, which have transformed them at opaque glass (milky white color). Such changes indicate that these glasses showed clearly phase separation (immiscibility). The immiscibility region in a sodium borosilicate ternary system was investigated in this work, i.e. to determine the regions from which some compositions can show phase separation. For this we went through the conditions of thermodynamic equilibrium, which were translated later by mathematical equations to find an approximate solution. The latter has been translated in a simulation which was established thereafter to find the immiscibility regions in this type of special glasses.

Keywords: sodium borosilicate, heat-resistant, isothermal treatments, immiscibility, thermodynamics

Procedia PDF Downloads 337

Authors: R. M. Korzerzer, J. O. Hambolu, S. O. Salami, S. B. Oladele

Abstract:

Twelve apparently healthy grasscutters between the ages of three and seven months were used for this study. The animals were purchased from local breeders in Oturkpo, Benue state, Nigeria and transported to the research laboratory in the Department of Veterinary Anatomy, Ahmadu Bello University, Zaria by means of constructed cages. The animals were divided into three groups according to their ages and acclimatised. Sacrifice was done using chloroform gaseous inhalation anaesthesia. An incision was made at the neck region and the thymus located and identified by its prominent bilateral nature. Extirpated thymuses from each animal were immediately weighed and fixed in Bouin’s fluid for 48 hours. The tissues were then prepared using standard methods. Haematoxilin and eosin was used for routine histology and Rhodamine B aniline methylene blue was for studying the architecture of the elastic and reticular fibres of the thymus. Grossly, the thymus appeared as a bilateral organ on either side of the thoracic midline. The organ size decreased consistently as the animals advanced in age. Mean ± SEM values for thymic weights were 1.23 ± 0.048 g, 0.53 ± 0.019 g and 0.30 ± 0.042 g at three, five and seven months of age respectively.

Keywords: gross, histological, thymus, grasscutter

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