Search results for: metal ion detection

Authors: Kenneth Fon Mbah, Arash Habibi Lashkari, Ali A. Ghorbani

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Phishing e-mails are a security issue that not only annoys online users, but has also resulted in significant financial losses for businesses. Phishing advertisements and pornographic e-mails are difficult to detect as attackers have been becoming increasingly intelligent and professional. Attackers track users and adjust their attacks based on users’ attractions and hot topics that can be extracted from community news and journals. This research focuses on deceptive Phishing attacks and their variants such as attacks through advertisements and pornographic e-mails. We propose a framework called Phishing Alerting System (PHAS) to accurately classify e-mails as Phishing, advertisements or as pornographic. PHAS has the ability to detect and alert users for all types of deceptive e-mails to help users in decision making. A well-known email dataset has been used for these experiments and based on previously extracted features, 93.11% detection accuracy is obtainable by using J48 and KNN machine learning techniques. Our proposed framework achieved approximately the same accuracy as the benchmark while using this dataset.

Keywords: phishing e-mail, phishing detection, anti phishing, alarm system, machine learning

Procedia PDF Downloads 344

Authors: Yang Jian-Hong, Zhang Ren-Cheng, Huang Li

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Arc fault is one of the main inducements of electric fires. Arc Fault Detection Device (AFDD) can detect arc fault effectively. Arc fault detections and unhooking standards are the keys to AFDD practical application. First, an arc fault continuous production system was developed, which could count the arc half wave number. Then, Combining with the UL1699 standard, ignition probability curve of cotton and unhooking time of various currents intensity were obtained by experiments. The combustion degree of arc fault could be expressed effectively by arc area. Experiments proved that electric fires would be misjudged or missed only using arc half wave number as AFDD unhooking basis. At last, Practical tests were carried out on the self-developed AFDD system. The result showed that actual AFDD unhooking time was the sum of arc half wave cycling number, Arc wave identification time and unhooking mechanical operation time And the first two shared shorter time. Unhooking time standard depended on the shortest mechanical operation time.

Keywords: arc fault detection device, arc area, arc half wave, unhooking time, arc fault

Procedia PDF Downloads 513

Authors: Afsal Mohammed Kadavilpparampu, Haider A. J. Al Lawati, Fakhr Eldin O. Suliman, Salma M. Z. Al Kindy

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In this work, we evaluated the appropriateness of various oxidants that can be used potentially with Ru(bipy)32+ CL system while performing CL detection in a microfluidic device using eight common active pharmaceutical ingredients- ciprofloxacin, hydrochlorothiazide, norfloxacin, buspirone, fexofenadine, cetirizine, codeine, and dextromethorphan. This is because, microfludics have very small channel volume and the residence time is also very short. Hence, a highly efficient oxidant is required for on-chip CL detection to obtain analytically acceptable CL emission. Three common oxidants were evaluated, lead dioxide, cerium ammonium sulphate and ammonium peroxydisulphate. Results obtained showed that ammonium peroxydisulphate is the most appropriate oxidant which can be used in microfluidic setup and all the tested analyte give strong CL emission while using this oxidant. We also found that Ru(bipy)33+ generated off-line by oxidizing [Ru(bipy)3]Cl2.6H2O in acetonitrile under acidic condition with lead dioxide was stable for more than 72 hrs. A highly sensitive microbore HPLC- CL method using ammonium peroxydisulphate as an oxidant in a microfluidic on-chip CL detection has been developed for the analyses of fixed-dose combinations of pseudoephedrine (PSE), fexofenadine (FEX) and cetirizine (CIT) in biological fluids and pharmaceutical formulations with minimum sample pre-treatment.

Keywords: oxidants, microbore High Performance Liquid Chromatography, chemiluminescence, microfluidics

Procedia PDF Downloads 453

Authors: Medina O. Kadiri, John E. Gabriel

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Heavy metals are metallic elements with a relatively high density, at least five times greater compared to water. The sources of heavy metal pollution in the environment include industrial, medical, agricultural, pharmaceutical, domestic effluents, and atmospheric sources, mining, foundries, smelting, and any heavy metal-based operation. Although some heavy metals in trace quantities are required for biological metabolism, their higher concentrations elicit toxicities. Others are distinctly toxic and are of no biological functions. Microalgae are the primary producers of aquatic ecosystems and, therefore, the foundation of the aquatic food chain. A study investigating the effects of copper and zinc on the two chlorophytes-Chlorella vulgaris and Dictyosphaerium pulchellum was done in the laboratory, under different concentrations of 0mg/l, 2mg/l, 4mg/l, 6mg/l, 8mg/l, 10mg/l, and 20mg/l. The growth of the test microalgae was determined every two days for 14 days. The results showed that the effects of the test heavy metals were concentration-dependent. From the two microalgae species tested, Chlorella vulgaris showed appreciable growth up to 8mg/l concentration of zinc. Dictyoshphaerium pulchellum had only minimal growth at different copper concentrations except for 2mg/l, which seemed to have relatively higher growth. The growth of the control was remarkably higher than in other concentrations. Generally, the growth of both test algae was consistently inhibited by heavy metals. Comparatively, copper generally inhibited the growth of both algae than zinc. Chlorella vulgaris can be used for bioremediation of high concentrations of zinc. The potential of many microalgae in heavy metal bioremediation can be explored.

Keywords: heavy metals, green algae, microalgae, pollution

Procedia PDF Downloads 198

Authors: Fuad Ameen, Ali A. Al-Homaidan

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Biochar can be used in numerous biotechnological applications due to its properties to adsorb beneficial nutrients and harmful pollutants. Objectives: We aimed to treat heavy metal polluted organic wastes using vermicomposting process and produce a fertilizer that can be used in agriculture. We improved the process by adding biochar as well as microbial inoculum and biomass into household waste or sewage sludge before vermicomposting. The earthworm Eisenia fetida used in vermicomposting was included to accumulate heavy metals, biochar to adsorb heavy metals, and the microalga Navicula sp. or the mangrove fungus Acrophialophora sp. to promote plant growth in the final product used as a seedbed for Solanaceae vegetables. We carried out vermicomposting treatments to see the effect of different amendments. Final compost quality was analyzed for maturity. The earthworms were studied for their vitality, heavy metal accumulation, and metallothionein protein content to verify their role in the process. The compost was used as a seedbed for vegetables that were inoculated with a phytopathogen Pythium sp. known to cause root rot and destroy seeds. Compost as seedbed promoted plant growth and reduced disease symptoms in leaves. In the treatment where E. fetida, 6% biochar, and Navicula sp. had been added, 90% of the seeds germinated, while less than 20% germinated in the control treatment. The experimental plants had acquired resistance against Pythium sp. The metagenomic profile of microbial communities will be reported.

Keywords: organic wastes, vermicomposting process, biochar, mangrove fungus

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Authors: Zyad Elkhadir, Khalid Chougdali, Mohammed Benattou

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Most of the existing intrusion detection systems works on quantitative network traffic data with many irrelevant and redundant features, which makes detection process more time’s consuming and inaccurate. A several feature extraction methods, such as linear discriminant analysis (LDA), have been proposed. However, LDA suffers from the small sample size (SSS) problem which occurs when the number of the training samples is small compared with the samples dimension. Hence, classical LDA cannot be applied directly for high dimensional data such as network traffic data. In this paper, we propose two solutions to solve SSS problem for LDA and apply them to a network IDS. The first method, reduce the original dimension data using principal component analysis (PCA) and then apply LDA. In the second solution, we propose to use the pseudo inverse to avoid singularity of within-class scatter matrix due to SSS problem. After that, the KNN algorithm is used for classification process. We have chosen two known datasets KDDcup99 and NSLKDD for testing the proposed approaches. Results showed that the classification accuracy of (PCA+LDA) method outperforms clearly the pseudo inverse LDA method when we have large training data.

Keywords: LDA, Pseudoinverse, PCA, IDS, NSL-KDD, KDDcup99

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Authors: Kaniz Roksana, Aluthgun Hewage Shaini, Cheng Zhu

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Lead is environmentally hazardous because it may persist for a long time in soil, water, and air, and it can travel large distances when carried by wind or water. Lead is toxic to many different species of organisms and has the potential to disrupt ecosystem stability. Moreover, lead can contaminate crops and livestock, which can then have an adverse effect on human health. This study was conducted to use the enzyme-induced calcium carbonate precipitation (EICP) technique from soybean crude extract urease along coconut fiber derived biochar’s (CFB) to bioremediate lead. To study the desorption rates of heavy metals from the soil, lead (Pb) was added to the soil at load ratios of 50 and 100 mg/kg. There were five separate treatment soil columns created: control sample, only CFB, only EICP, EICP with 2% (w/w) CFB, and EICP with 4% (w/w) CFB. Laboratory scale experiment demonstrates significant lead removal from soil. The amount of CaCO₃ precipitated in the soil was measured using a gravimetric acid digestion test, which related heavy metal desorption to the amount of precipitated calcium carbonate. These findings were validated using a scanning electron microscope (SEM), which revealed calcium carbonate and lead coprecipitation. As a result, the study reveals that the EICP technique, in conjunction with coconut fiber biochar, could be an efficient alternative in the remediation of heavy metal ion-contaminated soils.

Keywords: enzyme induced calcium carbonate precipitation (EICP), coconut fiber derived biochar’s (CFB), bioremediation, heavy metal

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Authors: Ashlesha Khanapure, Harsh Kashyap, Abhinav Anand, Sanjana Habib, Anupama Bidargaddi

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Technologies that are developing quickly are being developed daily in a variety of disciplines, particularly the medical field. For the purpose of detecting bone fractures in X-ray pictures of different body segments, our work compares the ResNet-50 and MobileNetV3 architectures. It evaluates accuracy and computing efficiency with X-rays of the elbow, hand, and shoulder from the MURA dataset. Through training and validation, the models are evaluated on normal and fractured images. While ResNet-50 showcases superior accuracy in fracture identification, MobileNetV3 showcases superior speed and resource optimization. Despite ResNet-50’s accuracy, MobileNetV3’s swifter inference makes it a viable choice for real-time clinical applications, emphasizing the importance of balancing computational efficiency and accuracy in medical imaging. We created a graphical user interface (GUI) for MobileNet V3 model bone fracture detection. This research underscores MobileNetV3’s potential to streamline bone fracture diagnoses, potentially revolutionizing orthopedic medical procedures and enhancing patient care.

Keywords: CNN, MobileNet V3, ResNet-50, healthcare, MURA, X-ray, fracture detection

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Authors: Mohammed Al Sulaimani, Hamad Al Manhi

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With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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Authors: Ismayanti Magfirah, Sartohadi Junun, Samodra Guruh

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Landslides are one of the most frequent and devastating natural disasters in Indonesia. Many studies have been conducted regarding this phenomenon. However, there is a lack of attention in the landslide inventory mapping. The natural condition (dense forest area) and the limited human and economic resources are some of the major problems in building landslide inventory in Indonesia. Considering the importance of landslide inventory data in susceptibility, hazard, and risk analysis, it is essential to generate landslide inventory based on available resources. In order to achieve this, the first thing we have to do is identify the landslides' location. The presence of Sentinel-1A and Sentinel-2A data gives new insights into land monitoring investigation. The free access, high spatial resolution, and short revisit time, make the data become one of the most trending open sources data used in landslide mapping. Sentinel-1A and Sentinel-2A data have been used broadly for landslide detection and landuse/landcover mapping. This study aims to generate landslide map by integrating Sentinel-1A and Sentinel-2A data use change detection method. The result will be validated by field investigation to make preliminary landslide inventory in the study area.

Keywords: change detection method, landslide inventory mapping, Sentinel-1A, Sentinel-2A

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Authors: S. N. Turkmen, A. S. Kipcak, N. Tugrul, E. M. Derun, S. Piskin

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Activated carbon is an amorphous carbon chain which has extremely extended surface area. High surface area of activated carbon is due to the porous structure. Activated carbon, using a variety of materials such as coal and cellulosic materials; can be obtained by both physical and chemical methods. The prepared activated carbon can be used for decolorize, deodorize and also can be used for removal of organic and non-organic pollution. In this study, pomegranate peel was subjected to 800W microwave power for 1 to 4 minutes. Also fresh pomegranate peel was used for the reference material. Then ZnCl2 was used for the chemical activation purpose. After the activation process, activated pomegranate peels were used for the adsorption of Zn metal (40 ppm) in the waste water. As a result of the adsorption experiments, removal of heavy metals ranged from 89% to 85%.

Keywords: activated carbon, adsorption, chemical activation, microwave, pomegranate peel

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Authors: Taiwo Ebenezer Abioye, Alexis Medrano-Tellez, Peter Kayode Farayibi, Peter Kayode Oke,

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Laser metal deposition by wire feedstock has been established as a process which can provide a high material deposition rate with good quality. Sound mechanical properties of the deposited parts are the pre-requisites for the real applications of this process. This paper investigates the laser metal deposition of 308LSi stainless steel wire within a process window. Single tracks and multiple layer thin-walls of 308LSi stainless steel wire were deposited on 304 stainless steel substrate. The grain structures of the built walls were examined using optical microscopy. The mechanical properties of the built walls including the micro-hardness and tensile properties along the transverse and longitudinal directions were investigated using Vickers hardness tester and tensile test machine. Long columnar grains were found growing in the wall building direction (transverse) and nucleation were observed at the boundary between two deposited layers due to remelting of the previously deposited layers. The results showed that the hardness values of the deposited walls (ranging between 194 HV and 167 HV) decreased from the track-substrate interface to the top of the wall. The ultimate tensile strength (UTS) of the wall (518 ± 7 MPa) showed dependence on wall building directions.

Keywords: laser metal deposition, ultimate tensile strength, hardness, wall, microstructure

Procedia PDF Downloads 417

Authors: Ki Hyun Park, Hye Min Park, Jeong Ho Kim, Chan Jong Park, Koan Sik Joo

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In the modern days, the use of radioactive substances is on the rise in the areas like chemical weaponry, industrial usage, and power plants. Although there are various technologies available to detect and monitor radioactive substances in the air, the technologies to detect underwater radioactive substances are scarce. In this study, computer simulation of the underwater detection system measuring beta-ray, a radioactive substance, has been done through MCNP. CaF₂, YAP(Ce) and YAG(Ce) have been used in the computer simulation to detect beta-ray as scintillator. Also, the source used in the computer simulation is Sr-90 and Y-90, both of them emitting only pure beta-ray. The distance between the source and the detector was shifted from 1mm to 10mm by 1 mm in the computer simulation. The result indicated that Sr-90 was impossible to measure below 1 mm since its emission energy is low while Y-90 was able to be measured up to 10mm underwater. In addition, the detector designed with CaF₂ had the highest efficiency among 3 scintillators used in the computer simulation. Since it was possible to verify the detectable range and the detection efficiency according to modeling through MCNP simulation, it is expected that such result will reduce the time and cost in building the actual beta-ray detector and evaluating its performances, thereby contributing the research and development.

Keywords: Beta-ray, CaF₂, detector, MCNP simulation, scintillator

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Authors: Sfiso Radebe

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The design models dealing with flawless composite structures are in abundance, where the mechanical properties of composite structures are assumed to be known a priori. However, if the worst case scenario is assumed, where material defects combined with processing anomalies in composite structures are expected, a different solution is attained. Furthermore, if the system being designed combines in series hybrid elements, individually affected by material constant variations, it implies that a different approach needs to be taken. In the body of literature, there is a compendium of research that investigates different modes of failure affecting hybrid metal-composite structures. It covers areas pertaining to the failure of the hybrid joints, structural deformation, transverse displacement, the suppression of vibration and noise. In the present study a system employing a combination of two or more hybrid power transmitting elements will be explored for the least favourable dynamic loads as well as weight minimization, subject to uncertain material properties. Elastic constants are assumed to be uncertain-but-bounded quantities varying slightly around their nominal values where the solution is determined using convex models of uncertainty. Convex analysis of the problem leads to the computation of the least favourable solution and ultimately to a robust design. This approach contrasts with a deterministic analysis where the average values of elastic constants are employed in the calculations, neglecting the variations in the material properties.

Keywords: convex modelling, hybrid, metal-composite, robust design

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Authors: Hongmei Chi

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The Blockchain has become a necessity for many different societal industries and ordinary lives including cryptocurrency technology, supply chain, health care, public safety, education, etc. Therefore, training our future blockchain developers to know blockchain programming vulnerability and I.T. students' cyber security is in high demand. In this work, we propose a framework including learning modules and hands-on labs to guide future I.T. professionals towards developing secure blockchain programming habits and mitigating source code vulnerabilities at the early stages of the software development lifecycle following the concept of Secure Software Development Life Cycle (SSDLC). In this research, our goal is to make blockchain programmers and I.T. students aware of the vulnerabilities of blockchains. In summary, we develop a framework that will (1) improve students' skills and awareness of blockchain source code vulnerabilities, detection tools, and mitigation techniques (2) integrate concepts of blockchain vulnerabilities for IT students, (3) improve future IT workers’ ability to master the concepts of blockchain attacks.

Keywords: software vulnerability detection, hands-on lab, static analysis tools, vulnerabilities, blockchain, active learning

Procedia PDF Downloads 104

Authors: Nicholas Mavrogiannis, Francesca Crivellari, Zachary Gagnon

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Development of low-cost, rapid, sensitive and portable biosensing systems are important for the detection and prevention of disease in developing countries, biowarfare/antiterrorism applications, environmental monitoring, point-of-care diagnostic testing and for basic biological research. Currently, the most established commercially available and widespread assays for portable point of care detection and disease testing are paper-based dipstick and lateral flow test strips. These paper-based devices are often small, cheap and simple to operate. The last three decades in particular have seen an emergence in these assays in diagnostic settings for detection of pregnancy, HIV/AIDS, blood glucose, Influenza, urinary protein, cardiovascular disease, respiratory infections and blood chemistries. Such assays are widely available largely because they are inexpensive, lightweight, and portable, are simple to operate, and a few platforms are capable of multiplexed detection for a small number of sample targets. However, there is a critical need for sensitive, quantitative and multiplexed detection capabilities for point-of-care diagnostics and for the detection and prevention of disease in the developing world that cannot be satisfied by current state-of-the-art paper-based assays. For example, applications including the detection of cardiac and cancer biomarkers and biothreat applications require sensitive multiplexed detection of analytes in the nM and pM range, and cannot currently be satisfied with current inexpensive portable platforms due to their lack of sensitivity, quantitative capabilities and often unreliable performance. In this talk, inexpensive label-free biomolecular detection at liquid interfaces using a newly discovered electrokinetic phenomenon known as fluidic dielectrophoresis (fDEP) is demonstrated. The electrokinetic approach involves exploiting the electrical mismatches between two aqueous liquid streams forced to flow side-by-side in a microfluidic T-channel. In this system, one fluid stream is engineered to have a higher conductivity relative to its neighbor which has a higher permittivity. When a “low” frequency (< 1 MHz) alternating current (AC) electrical field is applied normal to this fluidic electrical interface the fluid stream with high conductivity displaces into the low conductive stream. Conversely, when a “high” frequency (20MHz) AC electric field is applied, the high permittivity stream deflects across the microfluidic channel. There is, however, a critical frequency sensitive to the electrical differences between each fluid phase – the fDEP crossover frequency – between these two events where no fluid deflection is observed, and the interface remains fixed when exposed to an external field. To perform biomolecular detection, two streams flow side-by-side in a microfluidic T-channel: one fluid stream with an analyte of choice and an adjacent stream with a specific receptor to the chosen target. The two fluid streams merge and the fDEP crossover frequency is measured at different axial positions down the resulting liquid

Keywords: biodetection, fluidic dielectrophoresis, interfacial polarization, liquid interface

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Authors: Arvind Mittal, Rajesh Gupta

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Influence of heat input on the micro structure and mechanical properties of shield metal arc welded of duplex stainless steel UNSNO.S-31803 has been investigated. Three heat input combinations designated as low heat (0.675 KJ/mm), medium heat (0.860 KJ/mm) and high heat (1.094 KJ/mm) and weld joints made using these combinations were subjected to micro structural evaluations and tensile and impact testing so as to analyze the effect of thermal arc energy on the micro structure and mechanical properties of these joints. The result of this investigation shows that the joints made using low heat input exhibited higher tensile strength than those welded with medium and high heat input. Heat affected zone of welded joint made with medium heat input has austenitic ferritic grain structure with some patchy austenite provide high toughness. Significant grain coarsening was observed in the heat affected zone (HAZ) of medium and high heat input welded joints, whereas low heat input welded joint shows the fine grain structure in the heat affected zone with small amount of dendritic formation and equiaxed grain structure where inner zone indicates slowly cooled grains in the direction of heat dissipation. This is the main reason for the observable changes of tensile properties of weld joints welded with different arc energy inputs.

Keywords: microstructure, mechanical properties, shield metal arc welded, duplex stainless steel

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Authors: H. O. Udeh, T. E. Kgatla, A. I. O. Jideani

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The effect of Zn2+, Mg2+, and Ba2+ on Saccharomyces pastorianus during very high gravity fermentation was evaluated in this study at independent and three variable combinations. Wort gravity of 21oP was prepared from barley malt, hops and water, to which the metal ions were supplemented in their combinations and subsequently pitched. After 96 h of fermentation, high wort fermentability (%F)= 29.53 was obtained in wort medium containing 900:4 ppm Mg2+ + Ba2+. Increased ethanol titre 7.3491 %(v/v) and 7.1313 %(v/v) were obtained in media containing 900:4 ppm Mg2+ + Ba2+ and 12:900 ppm Zn2+ + Mg2+. Decrease %F= 22.54 and ethanol titre 6.1757% (v/v) was recorded in wort medium containing 12:4 ppm Zn2+ + Ba2+. In media containing the individual metal ions, increased %F= 27.94 and %F= 26.03 were obtained in media containing 700 ppm Mg2+ and 2 ppm Ba2+, with increased ethanol yield of 7.8844% (v/v) and 7.6245% (v/v) respectively. Least %F of 11.75 and 10.80, and ethanol titre of 4.99 (%v/v) and 4.80 (%v/v) were obtained for 10 ppm Zn2+ and 4 ppm Ba2+ respectively.

Keywords: ethanol yield, fermentability, mineral ions, yeast stress, very high gravity fermentation

Procedia PDF Downloads 374

Authors: Sabina Żołędowska, Tadeusz Ossowski, Robert Bogdanowicz, Jacek Ryl, Paweł Rostkowski, Michał Kruczkowski, Michał Sobaszek, Zofia Cebula, Grzegorz Skowierzak, Paweł Jakóbczyk, Lilit Hovhannisyan, Paweł Ślepski, Iwona Kaczmarczyk, Mattia Pierpaoli, Bartłomiej Dec, Dawid Nidzworski

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The circular economy of water presents a pressing environmental challenge in our society. Water contains various harmful substances, such as drugs, antibiotics, hormones, and dioxides, which can pose silent threats. Water pollution has severe consequences for aquatic ecosystems. It disrupts the balance of ecosystems by harming aquatic plants, animals, and microorganisms. Water pollution poses significant risks to human health. Exposure to toxic chemicals through contaminated water can have long-term health effects, such as cancer, developmental disorders, and hormonal imbalances. However, effective remediation systems can be implemented to remove these contaminants using electrocatalytic processes, which offer an environmentally friendly alternative to other treatment methods, and one of them is the innovative iCLARE system. The project's primary focus revolves around a few main topics: Reactor design and construction, selection of a specific type of reticulated vitreous carbon foams (RVC), analytical studies of harmful contaminants parameters and AI implementation. This high-performance electrochemical reactor will be build based on a novel type of electrode material. The proposed approach utilizes the application of reticulated vitreous carbon foams (RVC) with deposited modified metal oxides (MMO) and diamond thin films. The following setup is characterized by high surface area development and satisfactory mechanical and electrochemical properties, designed for high electrocatalytic process efficiency. The consortium validated electrode modification methods that are the base of the iCLARE product and established the procedures for the detection of chemicals detection: - deposition of metal oxides WO3 and V2O5-deposition of boron-doped diamond/nanowalls structures by CVD process. The chosen electrodes (porous Ferroterm electrodes) were stress tested for various parameters that might occur inside the iCLARE machine–corosis, the long-term structure of the electrode surface during electrochemical processes, and energetic efficacy using cyclic polarization and electrochemical impedance spectroscopy (before and after electrolysis) and dynamic electrochemical impedance spectroscopy (DEIS). This tool allows real-time monitoring of the changes at the electrode/electrolyte interphase. On the other hand, the toxicity of iCLARE chemicals and products of electrolysis are evaluated before and after the treatment using MARA examination (IBMM) and HPLC-MS-MS (NILU), giving us information about the harmfulness of using electrode material and the efficiency of iClare system in the disposal of pollutants. Implementation of data into the system that uses artificial intelligence and the possibility of practical application is in progress (SensDx).

Keywords: waste water treatement, RVC, electrocatalysis, paracetamol

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Authors: Narasimhulu Korrapati

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The objective of this present study is to optimize the process parameters for batch biosorption of Cr(VI) and Cu(II) ions by Bacillus subtilis using Response Surface Methodology (RSM). Batch biosorption studies were conducted under optimum pH, temperature, biomass concentration and contact time for the removal of Cr(VI) and Cu(II) ions using Bacillus subtilis. From the studies it is noticed that the maximum biosorption of Cr(VI) and Cu(II) was by Bacillus subtilis at optimum conditions of contact time of 30 minutes, pH of 4.0, biomass concentration of 2.0 mg/mL, the temperature of 32°C in batch biosorption studies. Predicted percent biosorption of the selected heavy metal ions by the design expert software is in agreement with experimental results of percent biosorption. The percent biosorption of Cr(VI) and Cu(II) in batch studies is 80% and 78.4%, respectively.

Keywords: heavy metal ions, response surface methodology, biosorption, wastewater

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Authors: Mohamed Fathy Heweage, Xiao Wen, Ayman Mokhtar, Ahmed Eldamarawy

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In this paper, we are interested in modeling, simulation, and measurement of the laser spot position with a quadrant detector. We enhance detection and tracking of semi-laser weapon decoding system based on microcontroller. The system receives the reflected pulse through quadrant detector and processes the laser pulses through a processing circuit, a microcontroller decoding laser pulse reflected by the target. The seeker accuracy will be enhanced by the decoding system, the laser detection time based on the receiving pulses number is reduced, a gate is used to limit the laser pulse width. The model is implemented based on Pulse Repetition Frequency (PRF) technique with two microcontroller units (MCU). MCU1 generates laser pulses with different codes. MCU2 decodes the laser code and locks the system at the specific code. The codes EW selected based on the two selector switches. The system is implemented and tested in Proteus ISIS software. The implementation of the full position determination circuit with the detector is produced. General system for the spot position determination was performed with the laser PRF for incident radiation and the mechanical system for adjusting system at different angles. The system test results show that the system can detect the laser code with only three received pulses based on the narrow gate signal, and good agreement between simulation and measured system performance is obtained.

Keywords: four quadrant detector, pulse code detection, laser guided weapons, pulse repetition frequency (PRF), Atmega 32 microcontrollers

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Authors: M. Shemis, O. Maher, G. Casterou, F. Gauffre

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Hepatitis C virus (HCV) is a major cause of chronic liver disease with a global 170 million chronic carriers at risk of developing liver cirrhosis and/or liver cancer. Egypt reports the highest prevalence of HCV worldwide. Currently, two classes of assays are used in the diagnosis and management of HCV infection. Despite the high sensitivity and specificity of the available diagnostic assays, they are time-consuming, labor-intensive, expensive, and require specialized equipment and highly qualified personal. It is therefore important for clinical and economic terms to develop a low-tech assay for the direct detection of HCV RNA with acceptable sensitivity and specificity, short turnaround time, and cost-effectiveness. Such an assay would be critical to control HCV in developing countries with limited resources and high infection rates, such as Egypt. The unique optical and physical properties of gold nanoparticles (AuNPs) have allowed the use of these nanoparticles in developing simple and rapid colorimetric assays for clinical diagnosis offering higher sensitivity and specificity than current detection techniques. The current research aims to develop a detection assay for HCV RNA using gold nanoparticles (AuNPs). Methods: 200 anti-HCV positive samples and 50 anti-HCV negative plasma samples were collected from Egyptian patients. HCV viral load was quantified using m2000rt (Abbott Molecular Inc., Des Plaines, IL). HCV genotypes were determined using multiplex nested RT- PCR. The assay is based on the aggregation of AuNPs in presence of the target RNA. Aggregation of AuNPs causes a color shift from red to blue. AuNPs were synthesized using citrate reduction method. Different sets of probes within the 5’ UTR conserved region of the HCV genome were designed, grafted on AuNPs and optimized for the efficient detection of HCV RNA. Results: The nano-gold assay could colorimetrically detect HCV RNA down to 125 IU/ml with sensitivity and specificity of 91.1% and 93.8% respectively. The turnaround time of the assay is < 30 min. Conclusions: The assay allows sensitive and rapid detection of HCV RNA and represents an inexpensive and simple point-of-care assay for resource-limited settings.

Keywords: HCV, gold nanoparticles, point of care, viral load

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Authors: N. Tugrul, E. Moroydor Derun, E. Cinar, A. S. Kipcak, N. Baran Acarali, S. Piskin

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Fly ash is an important waste, produced in thermal power plants which causes very important environmental pollutions. For this reason the usage and evaluation the fly ash in various areas are very important. Nearly, 15 million tons/year of fly ash is produced in Turkey. In this study, usage of fly ash with diatomite and molasses for heavy metal (Cd) adsorption from wastewater is investigated. The samples of Seyitomer region fly ash were analyzed by X-ray fluorescence (XRF) and Scanning Electron Microscope (SEM) then diatomite (0 and 1% in terms of fly ash, w/w) and molasses (0-0.75 mL) were pelletized under 30 MPa of pressure for the usage of cadmium (Cd) adsorption in wastewater. After the adsorption process, samples of Seyitomer were analyzed using Optical Emission Spectroscopy (ICP-OES). As a result, it is seen that the usage of Seyitomer fly ash is proper for cadmium (Cd) adsorption and an optimum adsorption yield with 52% is found at a compound with Seyitomer fly ash (10 g), diatomite (0.5 g) and molasses (0.75 mL) at 2.5 h of reaction time, pH:4, 20ºC of reaction temperature and 300 rpm of stirring rate.

Keywords: heavy metal, fly ash, molasses, diatomite, adsorption, wastewater

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Authors: Nirav J. Patel, Kalpesh K. Dudani

Abstract:

Partial discharge (PD) is the dissipation of energy caused by localized breakdown of insulation. Power transformers are one of the most important components in the electrical energy network. Insulation degradation of transformer is frequently linked to PD. This is why PD detection is used in power system to monitor the health of high voltage transformer. If such problem are not detected and repaired, the strength and frequency of PD may increase and eventually lead to the catastrophic failure of the transformer. This can further cause external equipment damage, fires and loss of revenue due to an unscheduled outage. Hence, reliable online PD detection is a critical need for power companies to improve personnel safety and decrease the probability of loss of service. The PD phenomenon is manifested in a variety of physically observable signals including Ultra High Frequency (UHF) radiation and Acoustic Disturbances, Electrical pulses. Acoustic method is based on sensing the radiated acoustic emission from discharge sites in the insulation. Propagated wave from the PD fault site are captured sensor are consequently pre-amplified, filtered, recorded and analyze.

Keywords: acoustic, partial discharge, perfectly matched layer, sensor

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Authors: Vipulkumar Jagodana

Abstract:

Recently the use of renewable sources has increased, these sources include fuel cell, photo voltaic, and wind turbine. Islanding occurs when one portion of grid is isolated from remaining grid. Use of the renewable sources can provide continuous power to isolated portion in islanding condition. One of the common renewable sources is wind generation using wind turbine. The efficiency of wind generation can be increased in combination with conventional sources. When islanding occurs, few parameters change which may be frequency, voltage, active power, and harmonics. According to large change in one of these parameters islanding is detected. In this paper, two passive methods Rate of Change of Frequency (ROCOF) and Rate of change of Power (ROCOP) have been implemented for islanding detection of small wind-turbine. Islanding detection of both methods have been simulated in PSCAD. Simulation results show at different islanding inception angle response of ROCOF and ROCOP.

Keywords: islanding, adopted methods, PSCAD simulation, comparison

Procedia PDF Downloads 228

Authors: Luciana P. Mazur, Tatiana A. Pozdniakova, Rui A. R. Boaventura, Vitor J. P. Vilar

Abstract:

The principal mechanism of metal ions sequestration by brown algae involves the formation of complexes between the metal ion and functional groups present on the cell wall of the biological material. To understand the role of functional groups on copper(II) uptake by Ascophyllum nodosum, some functional groups were chemically modified. The esterification of carboxylic groups was carried out by suspending the biomass in a methanol/HCl solution under stirring for 48 h and the blocking of the sulfonic groups was performed by repeating the same procedure for 4 cycles of 48 h. The methylation of amines was conducted by suspending the biomass in a formaldehyde/formic acid solution under shaking for 6 h and the chemical modification of sulfhydryl groups on the biomass surface was achieved using dithiodipyridine for 1 h. Equilibrium sorption studies for Cu2+ using the raw and esterified algae were performed at pH 2.0 and 4.0. The experiments were performed using an initial copper concentration of 300 mg/L and algae dose of 1.0 g/L. After reaching the equilibrium, the metal in solution was quantified by atomic absorption spectrometry. The biological material was analyzed by Fourier Transform Infrared Spectroscopy and Potentiometric Titration techniques for functional groups identification and quantification, respectively. The results using unmodified algae showed that the maximum copper uptake capacity at pH 4.0 and 2.0 was 1.17 and 0.52 mmol/g, respectively. At acidic pH values most carboxyl groups are protonated and copper sorption suffered a significant reduction of 56%. Blocking the carboxylic, sulfonic, amines and sulfhydryl functional groups, copper uptake decreased by 24/26%, 69/81%, 1/23% and 40/27% at pH 2.0/4.0, respectively, when compared to the unmodified biomass. It was possible to conclude that the carboxylic and sulfonic groups are the main functional groups responsible for copper binding (>80%). This result is supported by the fact that the adsorption capacity is directly related to the presence of carboxylic groups of the alginate polymer, and the second most abundant acidic functional group in brown algae is the sulfonic acid of fucoidan that contributes, to a lower extent, to heavy metal binding, particularly at low pH.

Keywords: biosorption, brown marine macroalgae, copper, ion-exchange

Procedia PDF Downloads 329

Authors: Aman Berhe, Camille Guinaudeau, Claude Barras

Abstract:

In order to facilitate information seeking in large collections of multimedia documents with long and progressive content (such as broadcast news or TV series), one can extract the semantic links that exist between semantically coherent parts of documents, i.e., scenes. The links can then create a coherent collection of scenes from which it is easier to perform content analysis, topic extraction, or information retrieval. In this paper, we focus on TV series structuring and propose two approaches for scene linking at different levels of granularity (episode and season): a fuzzy online clustering technique and a graph-based community detection algorithm. When evaluated on the two first seasons of the TV series Game of Thrones, we found that the fuzzy online clustering approach performed better compared to graph-based community detection at the episode level, while graph-based approaches show better performance at the season level.

Keywords: multimedia collection structuring, progressive content, scene linking, fuzzy clustering, community detection

Procedia PDF Downloads 106

Authors: Adebisi M. Tiamiyu, Adewale F. Adeyemi, Olu-Ayobamikale V. Irewunmi

Abstract:

Fish consumption has increased in recent years in both developing and advanced countries, owing to increased awareness of its nutritional and therapeutic benefits and its availability and affordability relative to other animal protein sources. Fish and fish products, however, are extremely prone to contamination by a wide range of hazardous organic and inorganic substances. This study assessed the levels of three heavy metals, copper (Cu), iron (Fe), and zinc (Zn), in frozen fish imported into Nigeria and sold in Ondo City for their safety for human consumption as recommended by WHO and FEPA. Three species of frozen fish (Scombrus scombrus, Merluccius merluccius, and Clupea harengus) were purchased, and the wet tissues (gills, muscles, and liver) were digested using a 3:1 mixture of nitric acid (HNO3) and hydrochloric acid (HCL). An atomic absorption spectrophotometer (AAS) was used to detect the amount of metal in the tissues. The levels of heavy metals in different fish species' organs varied. The fish had Zn > Fe > Cu heavy metal concentrations in that order. While the concentration of Cu and Fe in the tissues of all three fish species studied were within the WHO and FEPA prescribed limits for food fish, the concentration of Zn in the muscles of M. merluccius (0.262±0.052), C. harengus harengus (0.327±0.099), and S. scombrus (0.362±0.119) was above the prescribed limit (0.075 ppm) set by FEPA. An excessive amount of zinc in the body can cause nausea, headaches, decreased immunity, and appetite loss.

Keywords: heavy metal, atomic absorption spectrophotometer, fish, agencies

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Authors: Ahmed Noor Al-Qayyim

Abstract:

During the past decades, the bridge structures are considered very important portions of transportation networks, due to the fast urban sprawling. With the failure of bridges that under operating conditions lead to focus on updating the default bridge inspection methodology. The structures health monitoring (SHM) using the vibration response appeared as a promising method to evaluate the condition of structures. The rapid development in the sensors technology and the condition assessment techniques based on the vibration-based damage detection made the SHM an efficient and economical ways to assess the bridges. SHM is set to assess state and expects probable failures of designated bridges. In this paper, a presentation for Frequency Response function method that uses the captured vibration test information of structures to evaluate the structure condition. Furthermore, the main steps of the assessment of bridge using the vibration information are presented. The Frequency Response function method is applied to the experimental data of a full-scale bridge.

Keywords: bridge assessment, health monitoring, damage detection, frequency response function (FRF), signal processing, structure identification

Procedia PDF Downloads 353

Authors: Paiboon Jeamponk, Tasanee Ponglaa, Patchapon Srisanguan

Abstract:

The aim of this research paper was based on an examination of sources of water supply and water quality for local consumption, conducted at eco-tourism villages of Suan Luang Sub- District Municipality of Amphawa District, Samut Songkram Province. The study incorporated both questionnaire and field work of water testing as the research tool and method. The sample size of 288 households was based on the population of the district, whereas the selected sample water sources were from 60 households: 30 samples were ground water and another 30 were surface water. Degree of heavy metal contamination in the water including copper, iron, manganese, zinc, cadmium and lead was investigated utilizing the Atomic Absorption- Direct Aspiration method. The findings unveiled that 96.0 percent of household water consumption was based on water supply, while the rest on canal, river and rain water. The household behaviour of consumption revealed that 47.2 percent of people routinely consumed water without boiling or filtering prior to consumption. The investigation of water supply quality found that the degree of heavy metal contamination including metal, lead, iron, copper, manganese and cadmium met the standards of the Department of Health.

Keywords: sources of water supply, water quality, water supply, Thailand

Procedia PDF Downloads 298