Search results for: plant detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6751

Search results for: plant detection

5341 Advanced Driver Assistance System: Veibra

Authors: C. Fernanda da S. Sampaio, M. Gabriela Sadith Perez Paredes, V. Antonio de O. Martins

Abstract:

Today the transport sector is undergoing a revolution, with the rise of Advanced Driver Assistance Systems (ADAS), industry and society itself will undergo a major transformation. However, the technological development of these applications is a challenge that requires new techniques and great machine learning and artificial intelligence. The study proposes to develop a vehicular perception system called Veibra, which consists of two front cameras for day/night viewing and an embedded device capable of working with Yolov2 image processing algorithms with low computational cost. The strategic version for the market is to assist the driver on the road with the detection of day/night objects, such as road signs, pedestrians, and animals that will be viewed through the screen of the phone or tablet through an application. The system has the ability to perform real-time driver detection and recognition to identify muscle movements and pupils to determine if the driver is tired or inattentive, analyzing the student's characteristic change and following the subtle movements of the whole face and issuing alerts through beta waves to ensure the concentration and attention of the driver. The system will also be able to perform tracking and monitoring through GSM (Global System for Mobile Communications) technology and the cameras installed in the vehicle.

Keywords: advanced driver assistance systems, tracking, traffic signal detection, vehicle perception system

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5340 Qualitative Detection of HCV and GBV-C Co-infection in Cirrhotic Patients Using a SYBR Green Multiplex Real Time RT-PCR Technique

Authors: Shahzamani Kiana, Esmaeil Lashgarian Hamed, Merat Shahin

Abstract:

HCV and GBV-C belong to the Flaviviridae family of viruses and GBV-C is the closest virus to HCV genetically. Accumulative research is in progress all over the world to clarify clinical aspects of GBV-C. Possibility of interaction between HCV and GBV-C and also its consequence with other liver diseases are the most important clinical aspects which encourage researchers to develop a technique for simultaneous detection of these viruses. In this study a SYBR Green multiplex real time RT-PCR technique as a new economical and sensitive method was optimized for simultaneous detection of HCV/GBV-C in HCV positive plasma samples. After designing and selection of two pairs of specific primers for HCV and GBV-C, SYBR Green Real time RT-PCR technique optimization was performed separately for each virus. Establishment of multiplex PCR was the next step. Finally our technique was performed on positive and negative plasma samples. 89 cirrhotic HCV positive plasma samples (29 of genotype 3 a and 27 of genotype 1a) were collected from patients before receiving treatment. 14% of genotype 3a and 17.1% of genotype 1a showed HCV/GBV-C co-infection. As a result, 13.48% of 89 samples had HCV/GBV-C co-infection that was compatible with other results from all over the world. Data showed no apparent influence of HGV co-infection on the either clinical or virological aspect of HCV infection. Furthermore, with application of multiplex Real time RT-PCR technique, more time and cost could be saved in clinical-research settings.

Keywords: HCV, GBV-C, cirrhotic patients, multiplex real time RT- PCR

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5339 Temperature Contour Detection of Salt Ice Using Color Thermal Image Segmentation Method

Authors: Azam Fazelpour, Saeed Reza Dehghani, Vlastimil Masek, Yuri S. Muzychka

Abstract:

The study uses a novel image analysis based on thermal imaging to detect temperature contours created on salt ice surface during transient phenomena. Thermal cameras detect objects by using their emissivities and IR radiance. The ice surface temperature is not uniform during transient processes. The temperature starts to increase from the boundary of ice towards the center of that. Thermal cameras are able to report temperature changes on the ice surface at every individual moment. Various contours, which show different temperature areas, appear on the ice surface picture captured by a thermal camera. Identifying the exact boundary of these contours is valuable to facilitate ice surface temperature analysis. Image processing techniques are used to extract each contour area precisely. In this study, several pictures are recorded while the temperature is increasing throughout the ice surface. Some pictures are selected to be processed by a specific time interval. An image segmentation method is applied to images to determine the contour areas. Color thermal images are used to exploit the main information. Red, green and blue elements of color images are investigated to find the best contour boundaries. The algorithms of image enhancement and noise removal are applied to images to obtain a high contrast and clear image. A novel edge detection algorithm based on differences in the color of the pixels is established to determine contour boundaries. In this method, the edges of the contours are obtained according to properties of red, blue and green image elements. The color image elements are assessed considering their information. Useful elements proceed to process and useless elements are removed from the process to reduce the consuming time. Neighbor pixels with close intensities are assigned in one contour and differences in intensities determine boundaries. The results are then verified by conducting experimental tests. An experimental setup is performed using ice samples and a thermal camera. To observe the created ice contour by the thermal camera, the samples, which are initially at -20° C, are contacted with a warmer surface. Pictures are captured for 20 seconds. The method is applied to five images ,which are captured at the time intervals of 5 seconds. The study shows the green image element carries no useful information; therefore, the boundary detection method is applied on red and blue image elements. In this case study, the results indicate that proposed algorithm shows the boundaries more effective than other edges detection methods such as Sobel and Canny. Comparison between the contour detection in this method and temperature analysis, which states real boundaries, shows a good agreement. This color image edge detection method is applicable to other similar cases according to their image properties.

Keywords: color image processing, edge detection, ice contour boundary, salt ice, thermal image

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5338 Effects of Malachite Green Contaminated Water on Production of Pak Choy and Chinese Convolvulus

Authors: N. Piwpuan, J. Tosalee, N. Phonkerd

Abstract:

Malachite green (MG), a synthetic dye, is used in industries and aquaculture and also disposed in the effluent. Use of wastewater in irrigation increases due to water shortage. However, wastewater containing dyes, MG, are toxic to biological systems. Therefore, effects of MG on growth of vegetables were evaluated in order to utilize dye-contaminated wastewater for irrigation. In this study, Pak choy (Brassica chinensis) and Chinese convolvulus (Ipomoea aquatica) were grown in growing material (mixture of soil, coconut fiber, and compost) for four weeks and afterward kept watering with 200 ml of tap water containing MG at the concentrations of 0 (control), 1, 2, 10, and 20 mg/L. At harvest, number of leaf and shoot and root dry weight of the treated plants were measured and compared with control. For both species, their biomass values were similar among treatments and did not differ from the control plants (dry weight were 0.6-1.0 and 1.1-1.7 g/plant for B. chinensis and I. aquatica, respectively). B. chinensis treated with 2, 10, and 20 mg/L of MG produced lower number of new leaf and had smaller and shorter leaf compared to control and treatment of 1 mg/L. These results indicate the different responses between plant species, which B. chinensis is more sensitive to contaminant compared to I. aquatica. There was no sign of MG and leucomalachite green (LMG) detected in root and shoot tissues of plants treated with MG at 20 mg/L, tested by thin layer chromatography. After plant harvest, toxicity of the growing material from all treatments was tested on mung beans. Percent germination (83-97%), seedling fresh weight (0.3-0.5 g/plant), and shoot length (11-12.5 cm) were similar to the control. These indicated that contaminant in growing material did not pose detrimental effect on mung beans. Based on these results, the water contaminated with low concentration of MG, such as discharge from aquaculture, may serve as ferti-irrigation water to compensate water shortage.

Keywords: ferti-irrigation, soil toxicity, triphenylmethane dye, wastewater reuse

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5337 Effect of Composition Fuel on Safety of Combustion Process

Authors: Lourdes I. Meriño, Viatcheslav Kafarov, Maria Gómez

Abstract:

Fuel gas used in the burner receives as contributors other gases from different processes and this result in variability in the composition, which may cause an incomplete combustion. The burners are designed to operate in a certain curve, the calorific power dependent on the pressure and gas burners. When deviation of propane and C5+ is huge, there is a large release of energy, which causes it to work out the curves of the burners, because less pressure is required to force curve into operation. That increases the risk of explosion in an oven, besides of a higher environmental impact. There should be flame detection systems, and instrumentation equipment, such as local pressure gauges located at the entrance of the gas burners, to permit verification by the operator. Additionally, distributed control systems must be configured with different combustion instruments associated with respective alarms, as well as its operational windows, and windows control guidelines of integrity, leaving the design information of this equipment. Therefore, it is desirable to analyze when a plant is taken out of service and make good operational analysis to determine the impact of changes in fuel gas streams contributors, by varying the calorific power. Hence, poor combustion is one of the cause instability in the flame of the burner and having a great impact on process safety, the integrity of individuals and teams and environment.

Keywords: combustion process, fuel composition, safety, fuel gas

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5336 Unsupervised Neural Architecture for Saliency Detection

Authors: Natalia Efremova, Sergey Tarasenko

Abstract:

We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

Procedia PDF Downloads 344
5335 Modelling Affordable Waste Management Solutions for India

Authors: Pradip Baishya, D. K. Mahanta

Abstract:

Rapid and unplanned urbanisation in most cities of India has progressively increased the problem of managing municipal waste in the past few years. With insufficient infrastructure and funds, Municipalities in most cities are struggling to cope with the pace of waste generated. Open dumping is widely in practice as a cheaper option. Scientific disposal of waste in such a large scale with the elements of segregation, recycling, landfill, and incineration involves sophisticated and expensive plants. In an effort to finding affordable and simple solutions to address this burning issue of waste disposal, a semi-mechanized plant has been designed underlying the concept of a zero waste community. The fabrication work of the waste management unit is carried out by local skills from locally available materials. A resident colony in the city of Guwahati has been chosen, which is seen as a typical representative of most cities in India in terms of size and key issues surrounding waste management. Scientific management and disposal of waste on site is carried out on the principle of reduce, reuse and recycle from segregation to compositing. It is a local community participatory model, which involves all stakeholders in the process namely rag pickers, residents, municipality and local industry. Studies were conducted to testify the plant as revenue earning self-sustaining model in the long term. Current working efficiency of plant for segregation was found to be 1kg per minute. Identifying bottlenecks in the success of the model, data on efficiency of the plant, economics of its fabrication were part of the study. Similar satellite waste management plants could potentially be a solution to supplement the waste management system of municipalities of similar sized cities in India or South East Asia with similar issues surrounding waste disposal.

Keywords: affordable, rag pickers, recycle, reduce, reuse, segregation, zero waste

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5334 Designing of Oat Drink with Phytonutrients Assigned for Pro-Health Oriented Consumers

Authors: Gramza-Michalowska Anna, Skrety Joanna, Anna Zywica, Kobus-Cisowska Joanna, Kmiecik Dominik, Korczak Jozef

Abstract:

Background: Modern consumer highly appreciates the positive influence of consumed products on well-being and overall health. High acceptance of new food is a result of intensified research showing many proofs confirming that food offers significant prophylactic and therapeutic potential, next to its basic nutritional function. Objective: Proposition of the technology of unsweetened oat drinks enriched with plant extracts for pro-health oriented individuals. We investigated the effects of selected plant extracts addition on antioxidative capacity and consumer’s acceptance of drinks as representative of all day diet product. Methods: The analysis of the basic composition and antioxidant properties of the drinking product was conducted. Basic composition included protein, lipids and fiber content. Antioxidant capacity of drink was evaluated with use radical scavenging methods (DPPH, ABTS), ORAC value and FRAP. Proposed drink as new product was also characterized with sensory analysis, which included color, aroma, taste, consistency and overall acceptance. Results: Results showed that addition of plant extracts into a oat drink allowed to enhance its antioxidant potential and influenced significantly its sensory values. The preferred composition and properties of designed beverage permit claim that it can have a positive impact on the health of the consumers. Conclusion: Designed oat drink would be an answer for pro-healthy life style of the consumers. Results showed that product with plant extracts addition would be accepted by the consumers and because of its antioxidative potential could be an important factor in prevention of free radicals influence on human organism.

Keywords: phytonutrients, pro-health, well-being, antioxidant potential, sensory value

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5333 Penetration Analysis for Composites Applicable to Military Vehicle Armors, Aircraft Engines and Nuclear Power Plant Structures

Authors: Dong Wook Lee

Abstract:

This paper describes a method for analyzing penetration for composite material using an explicit nonlinear Finite Element Analysis (FEA). This method may be used in the early stage of design for the protection of military vehicles, aircraft engines and nuclear power plant structures made of composite materials. This paper deals with simple ballistic penetration tests for composite materials and the FEA modeling method and results. The FEA was performed to interpret the ballistic field test phenomenon regarding the damage propagation in the structure subjected to local foreign object impact.

Keywords: computer aided engineering, finite element analysis, impact analysis, penetration analysis, composite material

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5332 Lung Cancer Detection and Multi Level Classification Using Discrete Wavelet Transform Approach

Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

Abstract:

Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

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5331 Vitamin C Enhances Growth and Productivity of Sunflower Plants Grown under Newly-Reclaimed Saline Soil Conditions

Authors: Saad M. Howladar, Mostafa M. Rady, Wael M. Semida

Abstract:

A field experiment was conducted during the two successive seasons of 2012 and 2013 in the Experimental Farm (newly-reclaimed saline soil; EC = 7.8 dS m-1), Faculty of Agriculture, Fayoum University, Fayoum, Egypt to investigate the effect of vitamin C foliar application at the rates of 1, 2, 3 and 4 mM on the possibility of improving growth, seed and oil yields, and some chemical constituents of Helianthus annuus L. plants under the adverse conditions of the selected soil. Significant positive influences of all vitamin C treatments were observed on growth, seed and oil yields and some chemical constituents in both seasons. Compared to unsprayed plants (control), spraying plants with various rates of vitamin C significantly increased vegetative growth traits (i.e. plant height, No. of leaves plant-1, leaf area leaf-1, total leaves area plant-1, and dry weights of leaves and shoot plant-1) and seed and oil yields and their components (i.e. head diameter, seed weight head-1, 100-seed weight, seed yield feddan-1 and oil yield feddan-1). In addition, the concentrations of chlorophyll a, chlorophyll b, total chlorophylls, total carotenoids and total phenols in fresh leaves, and total carbohydrates, total soluble sugars, free proline and some nutrients (i.e. N, P, K, Fe, Mn, and Zn) in dry leaves were also increased significantly with all vitamin C applications. Vitamin C treatment at the rate of 3 mM was generated the best results. These results are important as the potential of vitamin C to alleviate the harmful effects of salt stress offer an opportunity to increase the resistance of sunflower plants to grow under saline conditions of the newly-reclaimed soils.

Keywords: sunflower, Helianthus annuus L., ascorbic acid, salinity, growth, seed yield, oil content, chemical composition

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5330 Pharmacognostical and Phytochemical Investigation of the Endemic Medicinal Plant Tekchebilium arvensis Linn

Authors: K. Bengango, H. Mesahsah, F. Haseb-Reho, J. M. Tafrate

Abstract:

This present work was conducted to explore the micro-morphology and phytochemical characterization of the endemic medicinal plant Tekchebilium arvensis Linn (Asteraceae). Macroscopy, microscopy, physicochemical analysis and WHO recommended parameters for standardizations were performed. Microscopic evaluation revealed the presence of abaxial epidermis with paracytic stomata. Petiole showed epidermis, vascular strands, ground tissue and secretary cavities. Physico-chemical tests like ash values, loss on drying, extractive values were determined. Preliminary phytochemical screening showed the presence of sterols, tannins, flavonoids, glycosides, volatile oil, terpenoids, saponin and alkaloids.

Keywords: Tekchebilium arvensis Linn, Asteraceae, microscopical evaluation, phytochemical, powder microscopy, standardization

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5329 Green Synthesis of Silver Nanoparticles Mediated by Plant by-Product Extracts

Authors: Cristian Moisa, Andreea Lupitu, Adriana Csakvari, Dana G. Radu, Leonard Marian Olariu, Georgeta Pop, Dorina Chambre, Lucian Copolovici, Dana Copolovici

Abstract:

Green synthesis of nanoparticles (NPs) represents a promising, accessible, eco-friendly, and safe process with significant applications in biotechnology, pharmaceutical sciences, and farming. The aim of our study was to obtain silver nanoparticles, using plant wastes extracts resulted in the essential oils extraction process: Thymus vulgaris L., Origanum vulgare L., Lavandula angustifolia L., and in hemp processing for seed and fibre, Cannabis sativa. Firstly, we obtained aqueous extracts of thyme, oregano, lavender, and hemp (two monoicous and one dioicous varieties), all harvested in western part of Romania. Then, we determined the chemical composition of the extracts by liquid-chromatography coupled with diode array and mass spectrometer detectors. The compounds identified in the extracts were in agreement with earlier published data, and the determination of the antioxidant activity of the obtained extracts by DPPH (2,2-diphenyl-1-picrylhydrazyl) and ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)) assays confirmed their antioxidant activity due to their total polyphenolic content evaluated by Folin-Ciocalteu assay. Then, the silver nanoparticles (AgNPs) were successfully biosynthesised, as was demonstrated by UV-VIS, FT-IR spectroscopies, and SEM, by reacting AgNO₃ solution and plant extracts. AgNPs were spherical in shape, with less than 30 nm in diameter, and had a good bactericidal activity against Gram-positive (Staphylococcus aureus) and Gram-negative bacteria (Escherichia coli, Klebsiella pneumoniae, Pseudomonas fluorescens).

Keywords: plant wastes extracts, chemical composition, high performance liquid chromatography mass spectrometer, HPLC-MS, scanning electron microscopy, SEM, silver nanoparticles

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5328 Faster, Lighter, More Accurate: A Deep Learning Ensemble for Content Moderation

Authors: Arian Hosseini, Mahmudul Hasan

Abstract:

To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

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5327 Clustered Regularly Interspaced Short Palindromic Repeat/cas9-Based Lateral Flow and Fluorescence Diagnostics for Rapid Pathogen Detection

Authors: Mark Osborn

Abstract:

Clustered, regularly interspaced short palindromic repeat (CRISPR/Cas) proteins can be designed to bind specified DNA and RNA sequences and hold great promise for the accurate detection of nucleic acids for diagnostics. Commercially available reagents were integrated into a CRISPR/Cas9-based lateral flow assay that can detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences with single-base specificity. This approach requires minimal equipment and represents a simplified platform for field-based deployment. A rapid, multiplex fluorescence CRISPR/Cas9 nuclease cleavage assay capable of detecting and differentiating SARS-CoV-2, influenza A and B, and respiratory syncytial virus in a single reaction was also developed. These findings provide proof of principle for CRISPR/Cas9 point-of-care diagnosis that can detect specific SARS-CoV-2 strain(s). Further, Cas9 cleavage allows for a scalable fluorescent platform for identifying respiratory viral pathogens with overlapping symptomology. Collectively, this approach is a facile platform for diagnostics with broad application to user-defined sequence interrogation and detection.

Keywords: CRISPR/Cas9, lateral flow assay, SARS-Co-V2, single-nucleotide resolution

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5326 Autonomous Kuka Youbot Navigation Based on Machine Learning and Path Planning

Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

Abstract:

The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

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5325 Acute Antihyperglycemic Activity of a Selected Medicinal Plant Extract Mixture in Streptozotocin Induced Diabetic Rats

Authors: D. S. N. K. Liyanagamage, V. Karunaratne, A. P. Attanayake, S. Jayasinghe

Abstract:

Diabetes mellitus is an ever increasing global health problem which causes disability and untimely death. Current treatments using synthetic drugs have caused numerous adverse effects as well as complications, leading research efforts in search of safe and effective alternative treatments for diabetes mellitus. Even though there are traditional Ayurvedic remedies which are effective, due to a lack of scientific exploration, they have not been proven to be beneficial for common use. Hence the aim of this study is to evaluate the traditional remedy made of mixture of plant components, namely leaves of Murraya koenigii L. Spreng (Rutaceae), cloves of Allium sativum L. (Amaryllidaceae), fruits of Garcinia queasita Pierre (Clusiaceae) and seeds of Piper nigrum L. (Piperaceae) used for the treatment of diabetes. We report herein the preliminary results for the in vivo study of the anti-hyperglycaemic activity of the extracts of the above plant mixture in Wistar rats. A mixture made out of equal weights (100 g) of the above mentioned medicinal plant parts were extracted into cold water, hot water (3 h reflux) and water: acetone mixture (1:1) separately. Male wistar rats were divided into six groups that received different treatments. Diabetes mellitus was induced by intraperitoneal administration of streptozotocin at a dose of 70 mg/ kg in male Wistar rats in group two, three, four, five and six. Group one (N=6) served as the healthy untreated and group two (N=6) served as diabetic untreated control and both groups received distilled water. Cold water, hot water, and water: acetone plant extracts were orally administered in diabetic rats in groups three, four and five, respectively at different doses of 0.5 g/kg (n=6), 1.0 g/kg(n=6) and 1.5 g/kg(n=6) for each group. Glibenclamide (0.5 mg/kg) was administered to diabetic rats in group six (N=6) served as the positive control. The acute anti-hyperglycemic effect was evaluated over a four hour period using the total area under the curve (TAUC) method. The results of the test group of rats were compared with the diabetic untreated control. The TAUC of healthy and diabetic rats were 23.16 ±2.5 mmol/L.h and 58.31±3.0 mmol/L.h, respectively. A significant dose dependent improvement in acute anti-hyperglycaemic activity was observed in water: acetone extract (25%), hot water extract ( 20 %), and cold water extract (15 %) compared to the diabetic untreated control rats in terms of glucose tolerance (P < 0.05). Therefore, the results suggest that the plant mixture has a potent antihyperglycemic effect and thus validating their used in Ayurvedic medicine for the management of diabetes mellitus. Future studies will be focused on the determination of the long term in vivo anti-diabetic mechanisms and isolation of bioactive compounds responsible for the anti-diabetic activity.

Keywords: acute antihyperglycemic activity, herbal mixture, oral glucose tolerance test, Sri Lankan medicinal plant extracts

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5324 Short-Term Effects of Seed Dressing With Azorhizobium Caulinodans on Establishment, Development and Yield of Early Maturing Maize ( Zea Mays L.) In Zimbabwe

Authors: Gabriel Vusanimuzi Nkomo

Abstract:

The majority of soils in communal areas of Zimbabwe are sandy and inherently infertile and sustainable cultivation is not feasible without addition of plant nutrients. Most farmers find it difficult to raise the capital required for investments in mineral fertilizer and find it cheaper to use low nutrition animal manure. An experiment was conducted to determine the effects of nitrokara biofertiliser on early growth, development and maize yield while also comparing nitrokara biofertiliser on availability of nitrogen and phosphorous in soil. The experiment was conducted at Africa University Farm. The experiment had six treatments (nitrokara +300kg/ha Compound D, nitrokara+ 300kg/ha Compound D(7N;14P;7K) + 75kg/ha Ammonium Nitrate(AN), nitrokara +300kg/ha Compound D +150kg AN, nitrokara +300kg/ha Compound D +225kg/ha AN, nitrokara +300kg/ha Compound D + 300 kg/ha AN and 0 nitrokara+300kg/ha Compound D +0 AN). Early maturing SC 403 maize (Zea mays) was inoculated with nitrokara and a compound mineral fertilizer at 300 kg/ha at planting while ammonium nitrate was applied at 45 days after planting. There were no significant differences (P > 0.05) on emergence % from 5days up to 10 days after planting using maize seed inoculated with nitrokara. Emergence percentage varied with the number of days. At 5 days the emergence % was 62% to a high of 97 % at 10 days after emergence among treatments. There were no significant differences (P > 0.05) on plant biomass on treatments 1 to 6 at 4 weeks after planting as well as at 8 weeks after planting. There were no significant differences among the treatments on the availability of nitrogen after 6 weeks (P > 0.05). However at 8 and 10 weeks after planting there were significant differences among treatments on nitrogen availability (P < 0.05). There were no significant differences among the treatments at week 6 after planting on soil pH (p > 0.05). However there were significant differences among treatments pH at weeks 9 and 12 (p < 0.05). There were significant differences among treatments on phosphorous availability at 6, 8 and 10 weeks after planting (p < 0.05). There were no significant differences among treatments on stem diameter at 3 and 6 weeks after planting (p > 0.05).However at 9 and 12 weeks after planting there were significant differences among treatments on stem diameter (p < 0.05).There were no significant differences among treatments on plant height from week 3 up to week 6 on plant height (P > 0.05).However there were significant differences among treatments at week 9 and 12 (p < 0.05). There were significant differences among treatments on days to early, 50% and 100% anthesis (P < 0.05). There were significant differences during early, 50% and 100% days to silking among the treatments (P < 0.05).Also there were significant differences during early, 50% and 100% days to silking among the treatments (P < 0.05).The study revealed that inoculation of nitrokara biofertiliser at planting with subsequent addition of ammonium nitrate has a positive effect on maize crop development and yield.

Keywords: nitrokara, biofertiliser, symbiotic, plant biomass, inoculated

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5323 Finite Dynamic Programming to Decision Making in the Use of Industrial Residual Water Treatment Plants

Authors: Oscar Vega Camacho, Andrea Vargas, Ellery Ariza

Abstract:

This paper presents the application of finite dynamic programming, specifically the "Markov Chain" model, as part of the decision making process of a company in the cosmetics sector located in the vicinity of Bogota DC. The objective of this process was to decide whether the company should completely reconstruct its waste water treatment plant or instead optimize the plant through the addition of equipment. The goal of both of these options was to make the required improvements in order to comply with parameters established by national legislation regarding the treatment of waste before it is released into the environment. This technique will allow the company to select the best option and implement a solution for the processing of waste to minimize environmental damage and the acquisition and implementation costs.

Keywords: decision making, markov chain, optimization, waste water

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5322 Study on an Integrated Real-Time Sensor in Droplet-Based Microfluidics

Authors: Tien-Li Chang, Huang-Chi Huang, Zhao-Chi Chen, Wun-Yi Chen

Abstract:

The droplet-based microfluidic are used as micro-reactors for chemical and biological assays. Hence, the precise addition of reagents into the droplets is essential for this function in the scope of lab-on-a-chip applications. To obtain the characteristics (size, velocity, pressure, and frequency of production) of droplets, this study describes an integrated on-chip method of real-time signal detection. By controlling and manipulating the fluids, the flow behavior can be obtained in the droplet-based microfluidics. The detection method is used a type of infrared sensor. Through the varieties of droplets in the microfluidic devices, the real-time conditions of velocity and pressure are gained from the sensors. Here the microfluidic devices are fabricated by polydimethylsiloxane (PDMS). To measure the droplets, the signal acquisition of sensor and LabVIEW program control must be established in the microchannel devices. The devices can generate the different size droplets where the flow rate of oil phase is fixed 30 μl/hr and the flow rates of water phase range are from 20 μl/hr to 80 μl/hr. The experimental results demonstrate that the sensors are able to measure the time difference of droplets under the different velocity at the voltage from 0 V to 2 V. Consequently, the droplets are measured the fastest speed of 1.6 mm/s and related flow behaviors that can be helpful to develop and integrate the practical microfluidic applications.

Keywords: microfluidic, droplets, sensors, single detection

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5321 Using ALOHA Code to Evaluate CO2 Concentration for Maanshan Nuclear Power Plant

Authors: W. S. Hsu, S. W. Chen, Y. T. Ku, Y. Chiang, J. R. Wang , J. H. Yang, C. Shih

Abstract:

ALOHA code was used to calculate the concentration under the CO2 storage burst condition for Maanshan nuclear power plant (NPP) in this study. Five main data are input into ALOHA code including location, building, chemical, atmospheric, and source data. The data from Final Safety Analysis Report (FSAR) and some reports were used in this study. The ALOHA results are compared with the failure criteria of R.G. 1.78 to confirm the habitability of control room. The result of comparison presents that the ALOHA result is below the R.G. 1.78 criteria. This implies that the habitability of control room can be maintained in this case. The sensitivity study for atmospheric parameters was performed in this study. The results show that the wind speed has the larger effect in the concentration calculation.

Keywords: PWR, ALOHA, habitability, Maanshan

Procedia PDF Downloads 191
5320 Application of Support Vector Machines in Fault Detection and Diagnosis of Power Transmission Lines

Authors: I. A. Farhat, M. Bin Hasan

Abstract:

A developed approach for the protection of power transmission lines using Support Vector Machines (SVM) technique is presented. In this paper, the SVM technique is utilized for the classification and isolation of faults in power transmission lines. Accurate fault classification and location results are obtained for all possible types of short circuit faults. As in distance protection, the approach utilizes the voltage and current post-fault samples as inputs. The main advantage of the method introduced here is that the method could easily be extended to any power transmission line.

Keywords: fault detection, classification, diagnosis, power transmission line protection, support vector machines (SVM)

Procedia PDF Downloads 552
5319 The Benefits of Security Culture for Improving Physical Protection Systems at Detection and Radiation Measurement Laboratory

Authors: Ari S. Prabowo, Nia Febriyanti, Haryono B. Santosa

Abstract:

Security function that is called as Physical Protection Systems (PPS) has functions to detect, delay and response. Physical Protection Systems (PPS) in Detection and Radiation Measurement Laboratory needs to be improved continually by using internal resources. The nuclear security culture provides some potentials to support this research. The study starts by identifying the security function’s weaknesses and its strengths of security culture as a purpose. Secondly, the strengths of security culture are implemented in the laboratory management. Finally, a simulation was done to measure its effectiveness. Some changes were happened in laboratory personnel behaviors and procedures. All became more prudent. The results showed a good influence of nuclear security culture in laboratory security functions.

Keywords: laboratory, physical protection system, security culture, security function

Procedia PDF Downloads 179
5318 Determining the City Development Based on the Modeling of the Pollutant Emission from Power Plant by Using AERMOD Software

Authors: Abbasi Fakhrossadat, Moharreri Mohammadamir, Shadmanmahani Mohammadjavad

Abstract:

The development of cities can be influenced by various factors, including air pollution. In this study, the focus is on the city of Mashhad, which has four large power plants operating. The emission of pollutants from these power plants can have a significant impact on the quality of life and health of the city's residents. Therefore, modeling and analyzing the emission pattern of pollutants can provide useful information for urban decision-makers and help in estimating the urban development model. The aim of this research is to determine the direction of city development based on the modeling of pollutant emissions (NOX, CO, and PM10) from power plants in Mashhad. By using the AERMOD software, the release of these pollutants will be modeled and analyzed.

Keywords: emission of air pollution, thermal power plant, urban development, AERMOD

Procedia PDF Downloads 72
5317 Artificial Intelligence Approach to Water Treatment Processes: Case Study of Daspoort Treatment Plant, South Africa

Authors: Olumuyiwa Ojo, Masengo Ilunga

Abstract:

Artificial neural network (ANN) has broken the bounds of the convention programming, which is actually a function of garbage in garbage out by its ability to mimic the human brain. Its ability to adopt, adapt, adjust, evaluate, learn and recognize the relationship, behavior, and pattern of a series of data set administered to it, is tailored after the human reasoning and learning mechanism. Thus, the study aimed at modeling wastewater treatment process in order to accurately diagnose water control problems for effective treatment. For this study, a stage ANN model development and evaluation methodology were employed. The source data analysis stage involved a statistical analysis of the data used in modeling in the model development stage, candidate ANN architecture development and then evaluated using a historical data set. The model was developed using historical data obtained from Daspoort Wastewater Treatment plant South Africa. The resultant designed dimensions and model for wastewater treatment plant provided good results. Parameters considered were temperature, pH value, colour, turbidity, amount of solids and acidity. Others are total hardness, Ca hardness, Mg hardness, and chloride. This enables the ANN to handle and represent more complex problems that conventional programming is incapable of performing.

Keywords: ANN, artificial neural network, wastewater treatment, model, development

Procedia PDF Downloads 145
5316 Cyber-Med: Practical Detection Methodology of Cyber-Attacks Aimed at Medical Devices Eco-Systems

Authors: Nir Nissim, Erez Shalom, Tomer Lancewiki, Yuval Elovici, Yuval Shahar

Abstract:

Background: A Medical Device (MD) is an instrument, machine, implant, or similar device that includes a component intended for the purpose of the diagnosis, cure, treatment, or prevention of disease in humans or animals. Medical devices play increasingly important roles in health services eco-systems, including: (1) Patient Diagnostics and Monitoring; Medical Treatment and Surgery; and Patient Life Support Devices and Stabilizers. MDs are part of the medical device eco-system and are connected to the network, sending vital information to the internal medical information systems of medical centers that manage this data. Wireless components (e.g. Wi-Fi) are often embedded within medical devices, enabling doctors and technicians to control and configure them remotely. All these functionalities, roles, and uses of MDs make them attractive targets of cyber-attacks launched for many malicious goals; this trend is likely to significantly increase over the next several years, with increased awareness regarding MD vulnerabilities, the enhancement of potential attackers’ skills, and expanded use of medical devices. Significance: We propose to develop and implement Cyber-Med, a unique collaborative project of Ben-Gurion University of the Negev and the Clalit Health Services Health Maintenance Organization. Cyber-Med focuses on the development of a comprehensive detection framework that relies on a critical attack repository that we aim to create. Cyber-Med will allow researchers and companies to better understand the vulnerabilities and attacks associated with medical devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The Cyber-Med detection framework will consist of two independent, but complementary detection approaches: one for known attacks, and the other for unknown attacks. These modules incorporate novel ideas and algorithms inspired by our team's domains of expertise, including cyber security, biomedical informatics, and advanced machine learning, and temporal data mining techniques. The establishment and maintenance of Cyber-Med’s up-to-date attack repository will strengthen the capabilities of Cyber-Med’s detection framework. Major Findings: Based on our initial survey, we have already found more than 15 types of vulnerabilities and possible attacks aimed at MDs and their eco-system. Many of these attacks target individual patients who use devices such pacemakers and insulin pumps. In addition, such attacks are also aimed at MDs that are widely used by medical centers such as MRIs, CTs, and dialysis engines; the information systems that store patient information; protocols such as DICOM; standards such as HL7; and medical information systems such as PACS. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched against MDs. Very little research has been conducted in order to protect these devices from cyber-attacks, since most of the development and engineering efforts are aimed at the devices’ core medical functionality, the contribution to patients’ healthcare, and the business aspects associated with the medical device.

Keywords: medical device, cyber security, attack, detection, machine learning

Procedia PDF Downloads 353
5315 Dynamics of Plant Communities with Chamaerops humilis in the Region of Tlemcen

Authors: O. Hasnaoui, A. Bekkouche, A. Mostefai, M. Bouazza

Abstract:

The region of Tlemcen (west Algeria) is known by their very important floral diversity bound to the conjugation of the multiple factors. Chamaerops humilis covers a big surface in this region, which appears in the majority of the cases in the form of more or less degraded matorral. Our work is dedicated to the comparative analysis of the groupings in chamaeropaie of the mounts of Tlemcen and mounts of traras, based on a phytoécologique approach. Four representative stations of chamaeropaies were retained to make this work. 120 floristic surveys were realized by using a minimal area of 100 m2. The obtained results show that the Mounts of Tlemcen present a wealth more important than those met at the level of the Mounts of Traras. More we go away from the coast towards the Mounts of Tlemcen, we notice a regressive evolution and a transformation of the plant carpet towards a thérophytisation, as well as an accentuation of the aridity.

Keywords: Tlemcen, west Algeria, Chamaerops humilis L., phytoécological, floristic survey, thérophytisation

Procedia PDF Downloads 280
5314 Developing a Process and Cost Model for Xanthan Biosynthesis from Bioethanol Production Waste Effluents

Authors: Bojana Ž. Bajić, Damjan G. Vučurović, Siniša N. Dodić, Jovana A. Grahovac, Jelena M. Dodić

Abstract:

Biosynthesis of xanthan, a microbial polysaccharide produced by Xanthomonas campestris, is characterized by the possibility of using non-specific carbohydrate substrates, which means different waste effluents can be used as a basis for the production media. Potential raw material sources for xanthan production come from industries with large amounts of waste effluents that are rich in compounds necessary for microorganism growth and multiplication. Taking into account the amount of waste effluents generated by the bioethanol industry and the fact that it contains a high inorganic and organic load it is clear that they represent a potential environmental pollutants if not properly treated. For this reason, it is necessary to develop new technologies which use wastes and wastewaters of one industry as raw materials for another industry. The result is not only a new product, but also reduction of pollution and environmental protection. Biotechnological production of xanthan, which consists of using biocatalysts to convert the bioethanol waste effluents into a high-value product, presents a possibility for sustainable development. This research uses scientific software developed for the modeling of biotechnological processes in order to design a xanthan production plant from bioethanol production waste effluents as raw material. The model was developed using SuperPro Designer® by using input data such as the composition of raw materials and products, defining unit operations, utility consumptions, etc., while obtaining capital and operating costs and the revenues from products to create a baseline production plant model. Results from this baseline model can help in the development of novel biopolymer production technologies. Additionally, a detailed economic analysis showed that this process for converting waste effluents into a high value product is economically viable. Therefore, the proposed model represents a useful tool for scaling up the process from the laboratory or pilot plant to a working industrial scale plant.

Keywords: biotechnology, process model, xanthan, waste effluents

Procedia PDF Downloads 341
5313 Metal-Oxide-Semiconductor-Only Process Corner Monitoring Circuit

Authors: Davit Mirzoyan, Ararat Khachatryan

Abstract:

A process corner monitoring circuit (PCMC) is presented in this work. The circuit generates a signal, the logical value of which depends on the process corner only. The signal can be used in both digital and analog circuits for testing and compensation of process variations (PV). The presented circuit uses only metal-oxide-semiconductor (MOS) transistors, which allow increasing its detection accuracy, decrease power consumption and area. Due to its simplicity the presented circuit can be easily modified to monitor parametrical variations of only n-type and p-type MOS (NMOS and PMOS, respectively) transistors, resistors, as well as their combinations. Post-layout simulation results prove correct functionality of the proposed circuit, i.e. ability to monitor the process corner (equivalently die-to-die variations) even in the presence of within-die variations.

Keywords: detection, monitoring, process corner, process variation

Procedia PDF Downloads 516
5312 Fault Diagnosis in Induction Motor

Authors: Kirti Gosavi, Anita Bhole

Abstract:

The paper demonstrates simulation and steady-state performance of three phase squirrel cage induction motor and detection of rotor broken bar fault using MATLAB. This simulation model is successfully used in the fault detection of rotor broken bar for the induction machines. A dynamic model using PWM inverter and mathematical modelling of the motor is developed. The dynamic simulation of the small power induction motor is one of the key steps in the validation of the design process of the motor drive system and it is needed for eliminating advertent design errors and the resulting error in the prototype construction and testing. The simulation model will be helpful in detecting the faults in three phase induction motor using Motor current signature analysis.

Keywords: squirrel cage induction motor, pulse width modulation (PWM), fault diagnosis, induction motor

Procedia PDF Downloads 624