Search results for: Zinc extraction

Authors: S. Hutasavi, D. Chen

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The built-up area is a significant proxy to measure regional economic growth and reflects the Gross Provincial Product (GPP). However, an up-to-date and reliable database of built-up areas is not always available, especially in developing countries. The cloud-based geospatial analysis platform such as Google Earth Engine (GEE) provides an opportunity with accessibility and computational power for those countries to generate the built-up data. Therefore, this study aims to extract the built-up areas in Eastern Economic Corridor (EEC), Thailand using day and nighttime satellite imagery based on GEE facilities. The normalized indices were generated from Landsat 8 surface reflectance dataset, including Normalized Difference Built-up Index (NDBI), Built-up Index (BUI), and Modified Built-up Index (MBUI). These indices were applied to identify built-up areas in EEC. The result shows that MBUI performs better than BUI and NDBI, with the highest accuracy of 0.85 and Kappa of 0.82. Moreover, the overall accuracy of classification was improved from 79% to 90%, and error of total built-up area was decreased from 29% to 0.7%, after night-time light data from the Visible and Infrared Imaging Suite (VIIRS) Day Night Band (DNB). The results suggest that MBUI with night-time light imagery is appropriate for built-up area extraction and be utilize for further study of socioeconomic impacts of regional development policy over the EEC region.

Keywords: Built-up area extraction, Google earth engine, adaptive thresholding method, rapid mapping.

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Authors: G. Petruzzelli, F. Pedron, M. Grifoni, A. Pera, I. Rosellini, B. Pezzarossa

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The addition of lime as Ca(OH)2 to sewage sludge to destroy pathogens (Escherichia coli), was evaluated also in relation to heavy metal bioavailability. The obtained results show that the use of calcium hydroxide at the dose of 3% effectively destroyed pathogens ensuring the stability at high pH values over long period and the duration of the sewage sludge stabilization. In general, lime addition decreased the total extractability of heavy metals indicating a reduced bioavailability of these elements. This is particularly important for a safe utilization in agricultural soils to reduce the possible transfer of heavy metals to the food chain.

Keywords: Biological sludge, Ca(OH)2, copper, pathogens, sanitation, zinc.

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Authors: Prakash Chand, Anurag Gaur, Ashavani Kumar

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In the present study, we have synthesized Cr and Fe doped zinc oxide (ZnO) nanostructures (Zn1-δCraFebO; where δ = a + b = 20%, a = 5, 6, 8 & 10% and b = 15, 14, 12 & 10%) via sol-gel method at different doping concentrations. The synthesized samples were characterized for structural properties by X-ray diffractrometer and field emission scanning electron microscope and the optical properties were carried out through photoluminescence and UVvisible spectroscopy. The particle size calculated through field emission scanning electron microscope varies from 41 to 96 nm for the samples synthesized at different doping concentrations. The optical band gaps calculated through UV-visible spectroscopy are found to be decreasing from 3.27 to 3.02 eV as the doping concentration of Cr increases and Fe decreases.

Keywords: Nanostructures, Optical Properties, Sol-gel method.

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Authors: Velid Demir, Mesut Akgün

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The lanthanum and zinc oxide were synthesized and then loaded with 6 wt% over γ-Al2O3 using the wet impregnation method. The samples were calcined at 900 °C to ensure a coherent structure with high catalytic performance. Characterization of the catalysts was verified by X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR). The effect of catalysts on biodiesel content from jatropha oil was studied under supercritical conditions. The results showed that ZnO/γ-Al2O3 was the superior catalyst for jatropha oil with 98.05% biodiesel under reaction conditions of 7 min reaction time, 1:40 oil to methanol molar ratio, 6 wt% of catalyst loading, 90 bar of reaction pressure, and 300 °C of reaction temperature, compared to 95.50% with La2O3/γ-Al2O3 at the same parameters. For this study, ZnO/γ-Al2O3 was the most suitable catalyst due to performance and cost considerations.

Keywords: Biodiesel, heterogeneous catalyst, Jatropha oil, supercritical methanol, transesterification.

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life due to the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or COVID-19 induced pneumonia. The early prediction and classification of such lung diseases help reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans are pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publicly available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scans, COVID-19, deep learning, image processing, pneumonia, lung disease.

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Authors: Moheb R. Girgis, Tarek M. Mahmoud, Tarek Abd-El-Hafeez

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This paper proposes a system to extract images from web pages and then detect the skin color regions of these images. As part of the proposed system, using BandObject control, we built a Tool bar named 'Filter Tool Bar (FTB)' by modifying the Pavel Zolnikov implementation. The Yahoo! Team provides us with the Yahoo! SDK API, which also supports image search and is really useful. In the proposed system, we introduced three new methods for extracting images from the web pages (after loading the web page by using the proposed FTB, before loading the web page physically from the localhost, and before loading the web page from any server). These methods overcome the drawback of the regular expressions method for extracting images suggested by Ilan Assayag. The second part of the proposed system is concerned with the detection of the skin color regions of the extracted images. So, we studied two famous skin color detection techniques. The first technique is based on the RGB color space and the second technique is based on YUV and YIQ color spaces. We modified the second technique to overcome the failure of detecting complex image's background by using the saturation parameter to obtain an accurate skin detection results. The performance evaluation of the efficiency of the proposed system in extracting images before and after loading the web page from localhost or any server in terms of the number of extracted images is presented. Finally, the results of comparing the two skin detection techniques in terms of the number of pixels detected are presented.

Keywords: Browser Helper Object, Color spaces, Image and URL extraction, Skin detection, Web Browser events.

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Authors: Nurul Amziah Md Yunus, Izhal Abdul Halin, Nasri Sulaiman, Noor Faezah Ismail, Nik Hasniza Nik Aman

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Nanotechnology has become the world attention in various applications including the solar cells devices due to the uniqueness and benefits of achieving low cost and better performances of devices. Recently, thin film solar cells such as Cadmium Telluride (CdTe), Copper-Indium-Gallium-diSelenide (CIGS), Copper-Zinc-Tin-Sulphide (CZTS), and Dye-Sensitized Solar Cells (DSSC) enhanced by nanotechnology have attracted much attention. Thus, a compilation of nanotechnology devices giving the progress in the solar cells has been presented. It is much related to nanoparticles or nanocrystallines, carbon nanotubes, and nanowires or nanorods structures.

Keywords: Nanotechnology, nanocrystalline, nanowires, carbon nanotubes, nanorods, thin film solar cells.

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Authors: Violina R. Angelova, Dimitar F. Grekov, Veselin K. Kisyov, Krasimir I. Ivanov

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A field study was conducted to evaluate the efficacy of lavender for phytoremediation of contaminated soils. The experiment was performed on an agricultural fields contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. The concentrations of Pb, Zn and Cd in lavender (roots, stems, leaves and inflorescences) and in the essential oils of lavender were determined. Lavender is a plant which is tolerant to heavy metals and can be grown on contaminated soils, and which can be referred to the hyperaccumulators of lead and the accumulators of cadmium and zinc, and can be successfully used in the phytoremediation of heavy metal contaminated soils. Favorable is also the fact that heavy metals do not influence the development of the lavender, as well as on the quality and quantity of the essential oil. The possibility of further industrial processing will make lavender economically interesting crops for farmers of phytoextraction technology.

Keywords: Heavy metals, lavender, phytoremediation, polluted soils.

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Authors: S. Demiray, M. E. Pintado, P. M. L. Castro

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There is a growing interest in the food industry and in preventive health care for the development and evaluation of natural antioxidants from medicinal plant materials. In the present work, extracts of three medicinal plants (Tilia argentea, Crataegi folium leaves and Polygonum bistorta roots) used in Turkish phytotheraphy were screened for their phenolic profiles and antioxidant properties. Crude extracts were obtained from different parts of plants, by solidliquid extraction with pure water, 70% acetone and 70% methanol aqueous solvents. The antioxidant activity of the extracts was determined by ABTS.+ radical cation scavenging activity. The Folin Ciocalteu procedure was used to assess the total phenolic concentrations of the extracts as gallic acid equivalents. A modified liquid chromatography-electro spray ionization-mass spectrometry (LC-ESI-MS) was used to obtain chromatographic profiles of the phenolic compounds in the medicinal plants. The predominant phenolic compounds detected in different extracts of the plants were catechin, protocatechuic and chlorogenic acids. The highest phenolic contents were obtained by using 70% acetone as aqueous solvent, whereas the lowest phenolic contents were obtained by water extraction due to Folin Ciocalteu results. The results indicate that acetone extracts of Tilia argentea had the highest antioxidant capacity as free ABTS radical scavengers. The lowest phenolic contents and antioxidant capacities were obtained from Polygonum bistorta root extracts.

Keywords: Medicinal plants, antioxidant activity, totalphenolics, LC-ESI-MS.

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Authors: Prima Luna, Afroditi Chatzifragkou, Dimitris Charalampopoulos

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Sorghum byproducts, namely bran, stalk, and panicle are examples of lignocellulosic biomass. These raw materials contain large amounts of polysaccharides, in particular hemicelluloses, celluloses, and lignins, which if efficiently extracted, can be utilised for the development of a range of added value products with potential applications in agriculture and food packaging sectors. The aim of this study was to characterise fractions extracted from sorghum bran and stalk with regards to their physicochemical properties that could determine their applicability as food-packaging materials. A sequential alkaline extraction was applied for the isolation of cellulosic, hemicellulosic and lignin fractions from sorghum stalk and bran. Lignin content, phenolic content and antioxidant capacity were also investigated in the case of the lignin fraction. Thermal analysis using differential scanning calorimetry (DSC) and X-Ray Diffraction (XRD) revealed that the glass transition temperature (T_g) of cellulose fraction of the stalk was ~78.33 ^oC at amorphous state (~65%) and water content of ~5%. In terms of hemicellulose, the T_g value of stalk was slightly lower compared to bran at amorphous state (~54%) and had less water content (~2%). It is evident that hemicelluloses generally showed a lower thermal stability compared to cellulose, probably due to their lack of crystallinity. Additionally, bran had higher arabinose-to-xylose ratio (0.82) than the stalk, a fact that indicated its low crystallinity. Furthermore, lignin fraction had T_g value of ~93 ^oC at amorphous state (~11%). Stalk-derived lignin fraction contained more phenolic compounds (mainly consisting of p-coumaric and ferulic acid) and had higher lignin content and antioxidant capacity compared to bran-derived lignin fraction.

Keywords: Alkaline extraction, bran, cellulose, hemicellulose, lignin, sorghum, stalk.

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Authors: A. Ali, V. Strezov, P. Davies, I. Wright, T. Kan

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The environmental impacts arising from mining activities affect the air, water, and soil quality. Impacts may result in unexpected and adverse environmental outcomes. This study reports on the impact of coal production on sediment in Sydney region of Australia. The sediment samples upstream and downstream from the discharge points from three mines were taken, and 80 parameters were tested. The results were assessed against sediment quality based on presence of metals. The study revealed the increment of metal content in the sediment downstream of the reference locations. In many cases, the sediment was above the Australia and New Zealand Environment Conservation Council and international sediment quality guidelines value (SQGV). The major outliers to the guidelines were nickel (Ni) and zinc (Zn).

Keywords: Coal mine, environmental impact, produced water, sediment quality guidelines value.

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Authors: S.I.Nikolaeva, Yu.V. Petrov, L.Ye.Skipnikova

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It has been shown that the solution of water shortage problem in Central Asia closely connected with inclusion of atmosphere water vapour into the system of response and water resources management. Some methods of water extraction from atmosphere have been discussed.

Keywords: potable water, water resources, water problems, water scarcity.

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Authors: Hema Nair

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This paper presents a new system developed in Java® for pattern recognition and pattern summarisation in multi-band (RGB) satellite images. The system design is described in some detail. Results of testing the system to analyse and summarise patterns in SPOT MS images and LANDSAT images are also discussed.

Keywords: Pattern recognition, image analysis, feature extraction, blackboard component, linguistic summary.

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Authors: Olayinka Omotosho

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The study investigated efficiency cassava peel carbon and Zinc Chloride activated cassava peel carbon at 1:3, 2:3 and 1:1 activation levels in the removal of nitrates from oxidized cassava processing wastewater. Results showed that the CPC and CPAC were effective in adsorption of nitrates. A summary of results from the study revealed that CPAC at 1:3 exhibited the highest initial decontamination (69.5% after 2 hrs) while CPAC at 1:1 activation ratio showed a slower initial decontamination rate. The CPC & CPAC exhibited Langmuir Rα values of 0.15, 0.11, 0.09, and 0.07 for the 0:1, 1:3, 2:3 and 1:1 confirming its suitability as adsorption material.

Keywords: Adsorption, Cassava, Activated Carbon, Nitrate, Isotherm, Langmuir.

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Authors: M. Feliciano, F. Maia, A. Gonçalves

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Olive oil production sector plays an important role in Portuguese economy. It had a major growth over the last decade, increasing its weight in the overall national exports. International market penetration for Mediterranean traditional products is increasingly more demanding, especially in the Northern European markets, where consumers are looking for more sustainable products. Trying to support this growing demand this study addresses olive oil production under the environmental and eco-efficiency perspectives. The analysis considers two consecutive product life cycle stages: olive trees farming; and olive oil extraction in mills. Addressing olive farming, data collection covered two different organizations: a middle-size farm (~12ha) (F1) and a large-size farm (~100ha) (F2). Results from both farms show that olive collection activities are responsible for the largest amounts of Green House Gases (GHG) emissions. In this activities, estimate for the Carbon Footprint per olive was higher in F2 (188g CO₂e/kg_olive) than in F1 (148g CO₂e/kg_olive). Considering olive oil extraction, two different mills were considered: one using a two-phase system (2P) and other with a three-phase system (3P). Results from the study of two mills show that there is a much higher use of water in 3P. Energy intensity (EI) is similar in both mills. When evaluating the GHG generated, two conditions are evaluated: a biomass neutral condition resulting on a carbon footprint higher in 3P (184g CO₂e/L_{olive oil}) than in 2P (92g CO₂e/L_{olive oil}); and a non-neutral biomass condition in which 2P increase its carbon footprint to 273g CO₂e/L_{olive oil}. When addressing the carbon footprint of possible combinations among studied subsystems, results suggest that olive harvesting is the major source for GHG.

Keywords: Carbon footprint, environmental indicators, farming subsystem, industrial subsystem, olive oil.

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Authors: D. Kliaugaitė, J. K, Staniškis

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In this study tree types of multilayer gas barrier plastic packaging films were compared using life cycle assessment as a tool for resource efficient and environmentally low-impact materials selection. The first type of multilayer packaging film (PET-AlOx/LDPE) consists of polyethylene terephthalate with barrier layer AlOx (PET-AlOx) and low density polyethylene (LDPE). The second type of polymer film (PET/PE-EVOH-PE) is made of polyethylene terephthalate (PET) and co-extrusion film PE-EVOH-PE as barrier layer. And the third one type of multilayer packaging film (PET-PVOH/LDPE) is formed from polyethylene terephthalate with barrier layer PVOH (PET-PVOH) and low density polyethylene (LDPE).

All of analyzed packaging has significant impact to resource depletion, because of raw materials extraction and energy use and production of different kind of plastics. Nevertheless the impact generated during life cycle of functional unit of II type of packaging (PET/PE-EVOH-PE) was about 25% lower than impact generated by I type (PET-AlOx/LDPE) and III type (PET-PVOH/LDPE) of packaging.

Result revealed that the contribution of different gas barrier type to the overall environmental problem of packaging is not significant. The impact are mostly generated by using energy and materials during raw material extraction and production of different plastic materials as plastic polymers material as PE, LDPE and PET, but not gas barrier materials as AlOx, PVOH and EVOH.

The LCA results could be useful in different decision-making processes, for selecting resource efficient and environmentally low-impact materials.

Keywords: Polymer packaging, life cycle assessment, resource efficiency.

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Authors: Mustafa M. Donma, Orkide Donma

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Cardiovascular (CV) pathology is one of the expected consequences of excessive fat gain. The role of zinc (Zn) in thyroid hormone metabolism (THM) is a matter of debate. Both thyroid stimulating hormone (TSH) and Zn levels are subject to variation in obese individuals. Zn participates in THM. It is closely related to TSH. Since thyroid hormones are required for Zn absorption, hypothyroidism can lead to Zn deficiency and vice versa. Zn exhibits protective effects on CV health and it is inversely correlated with CV markers in childhood obesity. The association between subclinical hypothyroidism (SCHT) and metabolic disorders is under investigation due to its clinical importance. SCHT is defined as the elevated serum TSH levels in the presence of normal free thyroxin (T4) concentrations. The aim of this study is to evaluate the associations between TSH levels and Zn concentrations in SCHT cases detected in morbid obese (MO) children with and without metabolic syndrome (MetS) [(MOMetS+ and MOMetS-)], respectively. 42 children were present in each study group. Informed consent forms were obtained. Tekrdag Namik Kemal University Faculty of Medicine Non-Interventional Clinical Investigations Ethical Committee approved the study protocol. World Health Organization criteria were used for obesity classification. Children with age and sex-dependent body mass index percentile values above 99 were defined as MO. Children exhibiting at least two of MetS criteria were included in MOMetS+ group. Elevated fasting blood glucose, elevated triglycerides (TRG)/decreased high density lipoprotein-cholesterol (HDL-C) concentrations, elevated blood pressure values in addition to central obesity were listed as MetS criteria. Anthropometric measures were recorded. Routine biochemical analyses were performed. In MOMetS- group 13, in MOMetS+ group 15 children were with SCHT. Statistical analyses were performed. p < 0.05 was accepted as statistically significant. In MOMetS- and MOMetS+ groups, TSH levels were 4.1 ± 2.9 mU/L and 4.6 ± 3.1 mU/L, respectively. Corresponding values for SCHT cases were 7.3 ± 3.1 mU/L and 8.0 ± 2.7 mU/L. Free T4 levels were within normal limits. Zn concentrations were negatively correlated with TSH levels in both groups. Significant negative correlation calculated in MOMetS+ group (r = -0.909; p < 0.001) was much stronger than that found in MOMetS- group (r = -0.706; p < 0.05). This strong correlation (r = -0.909; p < 0.001) calculated for cases with SCHT in MOMetS+ group was much lower in the same group (r = -0.793; p < 0.001) when all cases were considered. In conclusion, the presence of strong correlations between TSH and Zn in SCHT in both MOMetS- and MOMetS+ groups have pointed out that MO children were under the threat of CV pathologies. The detection of the much stronger correlation in MOMetS+ group in comparison with the correlation found in MOMetS- group was the indicator of greater CV risk due to the presence of MetS. In MOMetS+ group, correlation in SCHT cases found higher than correlation calculated for all cases confirmed much higher CV risk due to the contribution of SCHT.

Keywords: Cardiovascular risk, child morbid obesity, subclinical hypothyroidism, zinc.

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Authors: Shwe Wut Hmon Aye, Kay Thi Lwin, Waing Waing Kay Khine Oo

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As the material used for fuselage structure must possess low density, high strength to weight ratio, the selection of appropriate materials for fuselage structure is one of the most important tasks. Aluminum metal itself is soft and low in strength. It can be made stronger by giving proper combination of suitable alloy addition, mechanical treatment and thermal treatment. The usual thermal treatment given to aluminum alloys is called age-hardening or precipitation hardening. In this paper, the studies are carried out on 7075 aluminum alloy which is how to improve strength level for fuselage structure. The marked effect of the strength on the ternary alloy is clearly demonstrated at several ageing times and temperatures. It is concluded that aluminum-zinc-magnesium alloy can get the highest strength level in natural ageing.

Keywords: Aluminum alloy, ageing, heat treatment, strength.

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

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Active carbon can be obtained from agricultural sources. Due to the high surface area, the production of activated carbon from cheap resources is very important. Since the surface area of 1 g activated carbon is approximately between 300 and 2000 m², it can be used to remove both organic and inorganic impurities. In this study, the adsorption of Zn metal was studied with the product of activated carbon, which is obtained from pomegranate peel by microwave and chemical activation methods. The microwave process of pomegranate peel was carried out under constant microwave power of 800 W and 1 to 4 minutes. After the microwave process, samples were treated with H₂SO₄ for 3 h. Then prepared product was used in synthetic waste water including 40 ppm Zn metal. As a result, removal of waste Zn in waste water ranged from 91% to 93%.

Keywords: Activated carbon, chemical activation, H2SO4, microwave, pomegranate peel.

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Authors: H. Fazlinejad, A. Halvaee

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In this study, characteristics of ATIG welds using ZnO flux on aluminum was investigated and compared with TIG welds. Autogenously AC-ATIG bead on plate welding was applied on Al1050 plate with a coating of ZnO as the flux. Different levels of welding current and flux layer thickness was considered to study the effect of heat input and flux quantity on ATIG welds and was compared with those of TIG welds. Geometrical investigation of the weld cross sections revealed that penetration depth of the ATIG welds with ZnO flux, was increased up to 2 times in some samples compared to the TIG welds. Optical metallographic and Scanning Electron Microscopy (SEM) observations revealed similar microstructures in TIG and ATIG welds. Composition of the ATIG welds slag was also analyzed using X-ray diffraction. In both TIG and ATIG samples, the lowest values of microhardness were observed in the HAZ.

Keywords: ATIG, active flux, weld penetration, Al 1050, ZnO.

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Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: Human machine interface, industrial internet of things, internet of things, optical character recognition, video analytic.

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Authors: K. Mohammed, M. Agarwal, J. Mewman, Y. Ren

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An optimum technic has been developed for extracting volatile organic compounds which contribute to the aroma of lime fruit (Citrus aurantifolia). The volatile organic compounds of healthy and infested lime fruit with California red scale Aonidiella aurantii were characterized using headspace solid phase microextraction (HS-SPME) combined with gas chromatography (GC) coupled flame ionization detection (FID) and gas chromatography with mass spectrometry (GC-MS) as a very simple, efficient and nondestructive extraction method. A three-phase 50/30 μm PDV/DVB/CAR fibre was used for the extraction process. The optimal sealing and fibre exposure time for volatiles reaching equilibrium from whole lime fruit in the headspace of the chamber was 16 and 4 hours respectively. 5 min was selected as desorption time of the three-phase fibre. Herbivorous activity induces indirect plant defenses, as the emission of herbivorous-induced plant volatiles (HIPVs), which could be used by natural enemies for host location. GC-MS analysis showed qualitative differences among volatiles emitted by infested and healthy lime fruit. The GC-MS analysis allowed the initial identification of 18 compounds, with similarities higher than 85%, in accordance with the NIST mass spectral library. One of these were increased by A. aurantii infestation, D-limonene, and three were decreased, Undecane, α-Farnesene and 7-epi-α-selinene. From an applied point of view, the application of the above-mentioned VOCs may help boost the efficiency of biocontrol programs and natural enemies’ production techniques.

Keywords: Lime fruit, Citrus aurantifolia, California red scale, Aonidiella aurantii, VOCs, HS-SPME/GC-FID-MS.

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Authors: T.K. Tan, P.S. Khiew, W.S. Chiu, S.Radiman, R.Abd-Shukor, N.M. Huang, H.N. Lim

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In our recent study, we have used ZnO nanoparticles assisted with UV light irradiation to investigate the photocatalytic degradation of Phenol Red (PR). The ZnO photocatalyst was characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), specific surface area analysis (BET) and UVvisible spectroscopy. X-ray diffractometry result for the ZnO nanoparticles exhibit normal crystalline phase features. All observed peaks can be indexed to the pure hexagonal wurtzite crystal structures, with the space group of P63mc. There are no other impurities in the diffraction peak. In addition, TEM measurement shows that most of the nanoparticles are rod-like and spherical in shape and fairly monodispersed. A significant degradation of the PR was observed when the catalyst was added into the solution even without the UV light exposure. In addition, the photodegradation increases with the photocatalyst loading. The surface area of the ZnO nanomaterials from the BET measurement was 11.9 m2/g. Besides the photocatalyst loading, the effect of some parameters on the photodegradation efficiency such as initial PR concentration and pH were also studied.

Keywords: Nanostructures, phenol red, zinc oxide, heterogeneous photocatalyst.

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Authors: Maryam Afsharpour, Saleh Imani, Shahrzad Abdolmohammadi

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We investigate the ZnO role in the inherent protection of old manuscripts to protect them against environmental damaging effect of ultraviolet radiation, pollutant gasses, mold and bacteria. In this study a cellulosic nanocomposite of ZnO were used as protective coating on the surface of paper fibers. This layered nanocomposite can act as a consolidate materials too. Furthermore, to determine how well paper works screen objects from the damaging effects, two accelerated aging mechanisms due to light and heat are discussed. Results show good stability of papers with nanocomposite coating. Also, a good light stability was shown in the colored paper that treated with this nanocomposite. Furthermore, to demonstrate the degree of antifungal and antibacterial properties of coated papers, papers was treated with four common molds and bacteria and the good preventive effects of coated paper against molds and bacteria are described.

Keywords: Enviromental effects, Manuscript, Nanocomposite, Zinc oxide.

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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, chemical activation, microwave, pomegranate peel.

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Authors: Chundong Li, V. V. Neshchimenko, M. M. Mikhailov

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The effect of the modification of ZnO powders by ZrO₂, Al₂O₃, TiO₂, SiO₂, CeO₂ and Y₂O₃ nanoparticles with a concentration of 1-30 wt % is investigated by diffuse reflectance spectra within the wavelength range 200 to 2500 nm before and after 100 keV proton and electron irradiation. It has been established that the introduction of nanoparticles ZrO₂, Al₂O₃ enhances the optical stability of the pigments under proton irradiation, but reduces it under electron irradiation. Modifying with TiO₂, SiO₂, CeO₂, Y₂O₃ nanopowders leads to decrease radiation stability in both types of irradiation. Samples modified by 5 wt. % of ZrO₂ nanoparticles have the highest stability of optical properties after proton exposure. The degradation of optical properties under electron irradiation is not high for this concentration of nanoparticles. A decrease in the absorption of pigments modified with nanoparticles proton exposure is determined by a decrease in the intensity of bands located in the UV and visible regions. After electron exposure the absorption bands have in the whole spectrum range.

Keywords: Irradiation, nanopowders, radiation stability, zinc oxide.

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Authors: Amit Kumar Bhandary, Prithviraj Gupta, Siddhartha Mukherjee, Mahua Ghosh Chaudhuri, Rajib Dey

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Chromite ores are primarily used for extraction of chromium, which is an expensive metal. For low grade chromite ores (containing less than 40% Cr₂O₃), the chromium extraction is not usually economically viable. India possesses huge quantities of low grade chromite reserves. This deposit can be utilized after proper physical beneficiation. Magnetic separation techniques may be useful after reduction for the beneficiation of low grade chromite ore. The sample collected from the sukinda mines is characterized by XRD which shows predominant phases like maghemite, chromite, silica, magnesia and alumina. The raw ore is crushed and ground to below 75 micrometer size. The microstructure of the ore shows that the chromite grains surrounded by a silicate matrix and porosity observed the exposed side of the chromite ore. However, this ore may be utilized in refractory applications. Chromite ores contain Cr₂O₃, FeO, Al₂O₃ and other oxides like Fe-Cr, Mg-Cr have a high tendency to form spinel compounds, which usually show high refractoriness. Initially, the low grade chromite ore (containing 34.8% Cr₂O₃) was reduced at 1200 ⁰C for 80 minutes with 30% coke fines by weight, before being subjected to magnetic separation. The reduction by coke leads to conversion of higher state of iron oxides converted to lower state of iron oxides. The pre-reduced samples are then characterized by XRD. The magnetically inert mass was then reacted with 20% MgO by weight at 1450 ⁰C for 2 hours. The resultant product was then tested for various refractoriness parameters like apparent porosity, slag resistance etc. The results were satisfactory, indicating that the resultant spinel compounds are suitable for refractory applications for elevated temperature processes.

Keywords: Apparent porosity, beneficiation, low grade chromite, refractory, spinel compounds, slag resistance.

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Authors: H. Benjamin Fredrick David, R. Balasubramanian, A. Anbarasa Pandian

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Image retrieval is the most interesting technique which is being used today in our digital world. CBIR, commonly expanded as Content Based Image Retrieval is an image processing technique which identifies the relevant images and retrieves them based on the patterns that are extracted from the digital images. In this paper, two research works have been presented using CBIR. The first work provides an automated and interactive approach to the analysis of CBIR techniques. CBIR works on the principle of supervised machine learning which involves feature selection followed by training and testing phase applied on a classifier in order to perform prediction. By using feature extraction, the image transforms such as Contourlet, Ridgelet and Shearlet could be utilized to retrieve the texture features from the images. The features extracted are used to train and build a classifier using the classification algorithms such as Naïve Bayes, K-Nearest Neighbour and Multi-class Support Vector Machine. Further the testing phase involves prediction which predicts the new input image using the trained classifier and label them from one of the four classes namely 1- Normal brain, 2- Benign tumour, 3- Malignant tumour and 4- Severe tumour. The second research work includes developing a tool which is used for tumour stage identification using the best feature extraction and classifier identified from the first work. Finally, the tool will be used to predict tumour stage and provide suggestions based on the stage of tumour identified by the system. This paper presents these two approaches which is a contribution to the medical field for giving better retrieval performance and for tumour stages identification.

Keywords: Brain tumour detection, content based image retrieval, classification of tumours, image retrieval.

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Authors: M. R. Homaeinezhad, E. Tavakkoli, M. Habibi, S. A. Atyabi, A. Ghaffari

Abstract:

This paper describes a new supervised fusion (hybrid) electrocardiogram (ECG) classification solution consisting of a new QRS complex geometrical feature extraction as well as a new version of the learning vector quantization (LVQ) classification algorithm aimed for overcoming the stability-plasticity dilemma. Toward this objective, after detection and delineation of the major events of ECG signal via an appropriate algorithm, each QRS region and also its corresponding discrete wavelet transform (DWT) are supposed as virtual images and each of them is divided into eight polar sectors. Then, the curve length of each excerpted segment is calculated and is used as the element of the feature space. To increase the robustness of the proposed classification algorithm versus noise, artifacts and arrhythmic outliers, a fusion structure consisting of five different classifiers namely as Support Vector Machine (SVM), Modified Learning Vector Quantization (MLVQ) and three Multi Layer Perceptron-Back Propagation (MLP–BP) neural networks with different topologies were designed and implemented. The new proposed algorithm was applied to all 48 MIT–BIH Arrhythmia Database records (within–record analysis) and the discrimination power of the classifier in isolation of different beat types of each record was assessed and as the result, the average accuracy value Acc=98.51% was obtained. Also, the proposed method was applied to 6 number of arrhythmias (Normal, LBBB, RBBB, PVC, APB, PB) belonging to 20 different records of the aforementioned database (between– record analysis) and the average value of Acc=95.6% was achieved. To evaluate performance quality of the new proposed hybrid learning machine, the obtained results were compared with similar peer– reviewed studies in this area.

Keywords: Feature Extraction, Curve Length Method, SupportVector Machine, Learning Vector Quantization, Multi Layer Perceptron, Fusion (Hybrid) Classification, Arrhythmia Classification, Supervised Learning Machine.

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.

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