Search results for: weak efficient
360 Enhancing Efficiency of Building through Translucent Concrete
Authors: Humaira Athar, Brajeshwar Singh
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Generally, the brightness of the indoor environment of buildings is entirely maintained by the artificial lighting which has consumed a large amount of resources. It is reported that lighting consumes about 19% of the total generated electricity which accounts for about 30-40% of total energy consumption. One possible way is to reduce the lighting energy by exploiting sunlight either through the use of suitable devices or energy efficient materials like translucent concrete. Translucent concrete is one such architectural concrete which allows the passage of natural light as well as artificial light through it. Several attempts have been made on different aspects of translucent concrete such as light guiding materials (glass fibers, plastic fibers, cylinder etc.), concrete mix design and manufacturing methods for use as building elements. Concerns are, however, raised on various related issues such as poor compatibility between the optical fibers and cement paste, unaesthetic appearance due to disturbance occurred in the arrangement of fibers during vibration and high shrinkage in flowable concrete due to its high water/cement ratio. Need is felt to develop translucent concrete to meet the requirement of structural safety as OPC concrete with the maximized saving in energy towards the power of illumination and thermal load in buildings. Translucent concrete was produced using pre-treated plastic optical fibers (POF, 2mm dia.) and high slump white concrete. The concrete mix was proportioned in the ratio of 1:1.9:2.1 with a w/c ratio of 0.40. The POF was varied from 0.8-9 vol.%. The mechanical properties and light transmission of this concrete were determined. Thermal conductivity of samples was measured by a transient plate source technique. Daylight illumination was measured by a lux grid method as per BIS:SP-41. It was found that the compressive strength of translucent concrete increased with decreasing optical fiber content. An increase of ~28% in the compressive strength of concrete was noticed when fiber was pre-treated. FE-SEM images showed little-debonded zone between the fibers and cement paste which was well supported with pull-out bond strength test results (~187% improvement over untreated). The light transmission of concrete was in the range of 3-7% depending on fiber spacing (5-20 mm). The average daylight illuminance (~75 lux) was nearly equivalent to the criteria specified for illumination for circulation (80 lux). The thermal conductivity of translucent concrete was reduced by 28-40% with respect to plain concrete. The thermal load calculated by heat conduction equation was ~16% more than the plain concrete. Based on Design-Builder software, the total annual illumination energy load of a room using one side translucent concrete was 162.36 kW compared with the energy load of 249.75 kW for a room without concrete. The calculated energy saving on an account of the power of illumination was ~25%. A marginal improvement towards thermal comfort was also noticed. It is concluded that the translucent concrete has the advantages of the existing concrete (load bearing) with translucency and insulation characteristics. It saves a significant amount of energy by providing natural daylight instead of artificial power consumption of illumination.Keywords: energy saving, light transmission, microstructure, plastic optical fibers, translucent concrete
Procedia PDF Downloads 121359 Changing from Crude (Rudimentary) to Modern Method of Cassava Processing in the Ngwo Village of Njikwa Sub Division of North West Region of Cameroon
Authors: Loveline Ambo Angwah
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The processing of cassava from tubers or roots into food using crude and rudimentary method (hand peeling, grating, frying and to sun drying) is a very cumbersome and difficult process. The crude methods are time consuming and labour intensive. While on the other hand, modern processing method, that is using machines to perform the various processes as washing, peeling, grinding, oven drying, fermentation and frying is easier, less time consuming, and less labour intensive. Rudimentarily, cassava roots are processed into numerous products and utilized in various ways according to local customs and preferences. For the people of Ngwo village, cassava is transformed locally into flour or powder form called ‘cumcum’. It is also sucked into water to give a kind of food call ‘water fufu’ and fried to give ‘garri’. The leaves are consumed as vegetables. Added to these, its relative high yields; ability to stay underground after maturity for long periods give cassava considerable advantage as a commodity that is being used by poor rural folks in the community, to fight poverty. It plays a major role in efforts to alleviate the food crisis because of its efficient production of food energy, year-round availability, tolerance to extreme stress conditions, and suitability to present farming and food systems in Africa. Improvement of cassava processing and utilization techniques would greatly increase labor efficiency, incomes, and living standards of cassava farmers and the rural poor, as well as enhance the-shelf life of products, facilitate their transportation, increase marketing opportunities, and help improve human and livestock nutrition. This paper presents a general overview of crude ways in cassava processing and utilization methods now used by subsistence and small-scale farmers in Ngwo village of the North West region in Cameroon, and examine the opportunities of improving processing technologies. Cassava needs processing because the roots cannot be stored for long because they rot within 3-4 days of harvest. They are bulky with about 70% moisture content, and therefore transportation of the tubers to markets is difficult and expensive. The roots and leaves contain varying amounts of cyanide which is toxic to humans and animals, while the raw cassava roots and uncooked leaves are not palatable. Therefore, cassava must be processed into various forms in order to increase the shelf life of the products, facilitate transportation and marketing, reduce cyanide content and improve palatability.Keywords: cassava roots, crude ways, food system, poverty
Procedia PDF Downloads 162358 Microgrid Design Under Optimal Control With Batch Reinforcement Learning
Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion
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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.Keywords: batch-constrained reinforcement learning, control, design, optimal
Procedia PDF Downloads 116357 Experimental and Numerical Investigations on the Vulnerability of Flying Structures to High-Energy Laser Irradiations
Authors: Vadim Allheily, Rudiger Schmitt, Lionel Merlat, Gildas L'Hostis
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Inflight devices are nowadays major actors in both military and civilian landscapes. Among others, missiles, mortars, rockets or even drones this last decade are increasingly sophisticated, and it is today of prior manner to develop always more efficient defensive systems from all these potential threats. In this frame, recent High Energy Laser weapon prototypes (HEL) have demonstrated some extremely good operational abilities to shot down within seconds flying targets several kilometers off. Whereas test outcomes are promising from both experimental and cost-related perspectives, the deterioration process still needs to be explored to be able to closely predict the effects of a high-energy laser irradiation on typical structures, heading finally to an effective design of laser sources and protective countermeasures. Laser matter interaction researches have a long history of more than 40 years at the French-German Research Institute (ISL). Those studies were tied with laser sources development in the mid-60s, mainly for specific metrology of fast phenomena. Nowadays, laser matter interaction can be viewed as the terminal ballistics of conventional weapons, with the unique capability of laser beams to carry energy at light velocity over large ranges. In the last years, a strong focus was made at ISL on the interaction process of laser radiation with metal targets such as artillery shells. Due to the absorbed laser radiation and the resulting heating process, an encased explosive charge can be initiated resulting in deflagration or even detonation of the projectile in flight. Drones and Unmanned Air Vehicles (UAVs) are of outmost interests in modern warfare. Those aerial systems are usually made up of polymer-based composite materials, whose complexity involves new scientific challenges. Aside this main laser-matter interaction activity, a lot of experimental and numerical knowledge has been gathered at ISL within domains like spectrometry, thermodynamics or mechanics. Techniques and devices were developed to study separately each aspect concerned by this topic; optical characterization, thermal investigations, chemical reactions analysis or mechanical examinations are beyond carried out to neatly estimate essential key values. Results from these diverse tasks are then incorporated into analytic or FE numerical models that were elaborated, for example, to predict thermal repercussion on explosive charges or mechanical failures of structures. These simulations highlight the influence of each phenomenon during the laser irradiation and forecast experimental observations with good accuracy.Keywords: composite materials, countermeasure, experimental work, high-energy laser, laser-matter interaction, modeling
Procedia PDF Downloads 255356 Enhancing Industrial Wastewater Treatment: Efficacy and Optimization of Ultrasound-Assisted Laccase Immobilized on Magnetic Fe₃O₄ Nanoparticles
Authors: K. Verma, v. S. Moholkar
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In developed countries, water pollution caused by industrial discharge has emerged as a significant environmental concern over the past decades. However, despite ongoing efforts, a fully effective and sustainable remediation strategy has yet to be identified. This paper describes how enzymatic and sonochemical treatments have demonstrated great promise in degrading bio-refractory pollutants. Mainly, a compelling area of interest lies in the combined technique of sono-enzymatic treatment, which has exhibited a synergistic enhancement effect surpassing that of the individual techniques. This study employed the covalent attachment method to immobilize Laccase from Trametes versicolor onto amino-functionalized magnetic Fe₃O₄ nanoparticles. To comprehensively characterize the synthesized free nanoparticles and the laccase-immobilized nanoparticles, various techniques such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscope (SEM), vibrating sample magnetometer (VSM), and surface area through Brunauer-Emmett-Teller (BET) were employed. The size of immobilized Fe₃O₄@Laccase was found to be 60 nm, and the maximum loading of laccase was found to be 24 mg/g of nanoparticle. An investigation was conducted to study the effect of various process parameters, such as immobilized Fe₃O₄ Laccase dose, temperature, and pH, on the % Chemical oxygen demand (COD) removal as a response. The statistical design pinpointed the optimum conditions (immobilized Fe₃O₄ Laccase dose = 1.46 g/L, pH = 4.5, and temperature = 66 oC), resulting in a remarkable 65.58% COD removal within 60 minutes. An even more significant improvement (90.31% COD removal) was achieved with ultrasound-assisted enzymatic reaction utilizing a 10% duty cycle. The investigation of various kinetic models for free and immobilized laccase, such as the Haldane, Yano, and Koga, and Michaelis-Menten, showed that ultrasound application impacted the kinetic parameters Vmax and Km. Specifically, Vmax values for free and immobilized laccase were found to be 0.021 mg/L min and 0.045 mg/L min, respectively, while Km values were 147.2 mg/L for free laccase and 136.46 mg/L for immobilized laccase. The lower Km and higher Vmax for immobilized laccase indicate its enhanced affinity towards the substrate, likely due to ultrasound-induced alterations in the enzyme's confirmation and increased exposure of active sites, leading to more efficient degradation. Furthermore, the toxicity and Liquid chromatography-mass spectrometry (LC-MS) analysis revealed that after the treatment process, the wastewater exhibited 70% less toxicity than before treatment, with over 25 compounds degrading by more than 75%. At last, the prepared immobilized laccase had excellent recyclability retaining 70% activity up to 6 consecutive cycles. A straightforward manufacturing strategy and outstanding performance make the recyclable magnetic immobilized Laccase (Fe₃O₄ Laccase) an up-and-coming option for various environmental applications, particularly in water pollution control and treatment.Keywords: kinetic, laccase enzyme, sonoenzymatic, ultrasound irradiation
Procedia PDF Downloads 59355 ENDO-β-1,4-Xylanase from Thermophilic Geobacillus stearothermophilus: Immobilization Using Matrix Entrapment Technique to Increase the Stability and Recycling Efficiency
Authors: Afsheen Aman, Zainab Bibi, Shah Ali Ul Qader
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Introduction: Xylan is a heteropolysaccharide composed of xylose monomers linked together through 1,4 linkages within a complex xylan network. Owing to wide applications of xylan hydrolytic products (xylose, xylobiose and xylooligosaccharide) the researchers are focusing towards the development of various strategies for efficient xylan degradation. One of the most important strategies focused is the use of heat tolerant biocatalysts which acts as strong and specific cleaving agents. Therefore, the exploration of microbial pool from extremely diversified ecosystem is considerably vital. Microbial populations from extreme habitats are keenly explored for the isolation of thermophilic entities. These thermozymes usually demonstrate fast hydrolytic rate, can produce high yields of product and are less prone to microbial contamination. Another possibility of degrading xylan continuously is the use of immobilization technique. The current work is an effort to merge both the positive aspects of thermozyme and immobilization technique. Methodology: Geobacillus stearothermophilus was isolated from soil sample collected near the blast furnace site. This thermophile is capable of producing thermostable endo-β-1,4-xylanase which cleaves xylan effectively. In the current study, this thermozyme was immobilized within a synthetic and a non-synthetic matrice for continuous production of metabolites using entrapment technique. The kinetic parameters of the free and immobilized enzyme were studied. For this purpose calcium alginate and polyacrylamide beads were prepared. Results: For the synthesis of immobilized beads, sodium alginate (40.0 gL-1) and calcium chloride (0.4 M) was used amalgamated. The temperature (50°C) and pH (7.0) optima of immobilized enzyme remained same for xylan hydrolysis however, the enzyme-substrate catalytic reaction time raised from 5.0 to 30.0 minutes as compared to free counterpart. Diffusion limit of high molecular weight xylan (corncob) caused a decline in Vmax of immobilized enzyme from 4773 to 203.7 U min-1 whereas, Km value increased from 0.5074 to 0.5722 mg ml-1 with reference to free enzyme. Immobilized endo-β-1,4-xylanase showed its stability at high temperatures as compared to free enzyme. It retained 18% and 9% residual activity at 70°C and 80°C, respectively whereas; free enzyme completely lost its activity at both temperatures. The Immobilized thermozyme displayed sufficient recycling efficiency and can be reused up to five reaction cycles, indicating that this enzyme can be a plausible candidate in paper processing industry. Conclusion: This thermozyme showed better immobilization yield and operational stability with the purpose of hydrolyzing the high molecular weight xylan. However, the enzyme immobilization properties can be improved further by immobilizing it on different supports for industrial purpose.Keywords: immobilization, reusability, thermozymes, xylanase
Procedia PDF Downloads 371354 Optimization of Cobalt Oxide Conversion to Co-Based Metal-Organic Frameworks
Authors: Aleksander Ejsmont, Stefan Wuttke, Joanna Goscianska
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Gaining control over particle shape, size and crystallinity is an ongoing challenge for many materials. Especially metalorganic frameworks (MOFs) are recently widely studied. Besides their remarkable porosity and interesting topologies, morphology has proven to be a significant feature. It can affect the further material application. Thus seeking new approaches that enable MOF morphology modulation is important. MOFs are reticular structures, where building blocks are made up of organic linkers and metallic nodes. The most common strategy of ensuring metal source is using salts, which usually exhibit high solubility and hinder morphology control. However, there has been a growing interest in using metal oxides as structure-directing agents towards MOFs due to their very low solubility and shape preservation. Metal oxides can be treated as a metal reservoir during MOF synthesis. Up to now, reports in which receiving MOFs from metal oxides mostly present ZnO conversion to ZIF-8. However, there are other oxides, for instance, Co₃O₄, which often is overlooked due to their structural stability and insolubility in aqueous solutions. Cobalt-based materials are famed for catalytic activity. Therefore the development of their efficient synthesis is worth attention. In the presented work, an optimized Co₃O₄transition to Co-MOFviaa solvothermal approach was proposed. The starting point of the research was the synthesis of Co₃O₄ flower petals and needles under hydrothermal conditions using different cobalt salts (e.g., cobalt(II) chloride and cobalt(II) nitrate), in the presence of urea, and hexadecyltrimethylammonium bromide (CTAB) surfactant as a capping agent. After receiving cobalt hydroxide, the calcination process was performed at various temperatures (300–500 °C). Then cobalt oxides as a source of cobalt cations were subjected to reaction with trimesic acid in solvothermal environment and temperature of 120 °C leading to Co-MOF fabrication. The solution maintained in the system was a mixture of water, dimethylformamide, and ethanol, with the addition of strong acids (HF and HNO₃). To establish how solvents affect metal oxide conversion, several different solvent ratios were also applied. The materials received were characterized with analytical techniques, including X-ray powder diffraction, energy dispersive spectroscopy,low-temperature nitrogen adsorption/desorption, scanning, and transmission electron microscopy. It was confirmed that the synthetic routes have led to the formation of Co₃O₄ and Co-based MOF varied in shape and size of particles. The diffractograms showed receiving crystalline phase for Co₃O₄, and also for Co-MOF. The Co₃O₄ obtained from nitrates and with using low-temperature calcination resulted in smaller particles. The study indicated that cobalt oxide particles of different size influence the efficiency of conversion and morphology of Co-MOF. The highest conversion was achieved using metal oxides with small crystallites.Keywords: Co-MOF, solvothermal synthesis, morphology control, core-shell
Procedia PDF Downloads 156353 Learners’ Preferences in Selecting Language Learning Institute (A Study in Iran)
Authors: Hoora Dehghani, Meisam Shahbazi, Reza Zare
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During the previous decade, a significant evolution has occurred in the number of private educational centers and, accordingly, the increase in the number of providers and students of these centers around the world. The number of language teaching institutes in Iran that are considered private educational sectors is also growing exponentially as the request for learning foreign languages has extremely increased in recent years. This fact caused competition among the institutions in improving better services tailored to the students’ demands to win the competition. Along with the growth in the industry of education, higher education institutes should apply the marketing-related concepts and view students as customers because students’ outlooks are similar to consumers with education. Studying the influential factors in the selection of an institute has multiple benefits. Firstly, it acknowledges the institutions of the students’ choice factors. Secondly, the institutions use the obtained information to improve their marketing methods. It also helps institutions know students’ outlooks that can be applied to expand the student know-how. Moreover, it provides practical evidence for educational centers to plan useful amenities and programs, and use efficient policies to cater to the market, and also helps them execute the methods that increase students’ feeling of contentment and assurance. Thus, this study explored the influencing factors in the selection of a language learning institute by language learners and examined and compared the importance among the varying age groups and genders. In the first phase of the study, the researchers selected 15 language learners as representative cases within the specified age ranges and genders purposefully and interviewed them to explore the comprising elements in their language institute selection process and analyzed the results qualitatively. In the second phase, the researchers identified elements as specified items of a questionnaire, and 1000 English learners across varying educational contexts rated them. The TOPSIS method was used to analyze the data quantitatively by representing the level of importance of the items for the participants generally and specifically in each subcategory; genders and age groups. The results indicated that the educational quality, teaching method, duration of training course, establishing need-oriented courses, and easy access were the most important elements. On the other hand, offering training in different languages, the specialized education of only one language, the uniform and appropriate appearance of office staff, having native professors to the language of instruction, applying Computer or online tests instead of the usual paper tests respectively as the least important choice factors in selecting a language institute. Besides, some comparisons among different groups’ ratings of choice factors were made, which revealed the differences among different groups' priorities in choosing a language institute.Keywords: choice factors, EFL institute selection, english learning, need analysis, TOPSIS
Procedia PDF Downloads 159352 Sustainable Solid Waste Management Solutions for Asian Countries Using the Potential in Municipal Solid Waste of Indian Cities
Authors: S. H. Babu Gurucharan, Priyanka Kaushal
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Majority of the world's population is expected to live in the Asia and Pacific region by 2050 and thus their cities will generate the maximum waste. India, being the second populous country in the world, is an ideal case study to identify a solution for Asian countries. Waste minimisation and utilisation have always been part of the Indian culture. During rapid urbanisation, our society lost the art of waste minimisation and utilisation habits. Presently, Waste is not considered as a resource, thus wasting an opportunity to tap resources. The technologies in vogue are not suited for effective treatment of large quantities of generated solid waste, without impacting the environment and the population. If not treated efficiently, Waste can become a silent killer. The article is trying to highlight the Indian municipal solid waste scenario as a key indicator of Asian waste management and recommend sustainable waste management and suggest effective solutions to treat the Solid Waste. The methods followed during the research were to analyse the solid waste data on characteristics of solid waste generated in Indian cities, then evaluate the current technologies to identify the most suitable technology in Indian conditions with minimal environmental impact, interact with the technology technical teams, then generate a technical process specific to Indian conditions and further examining the environmental impact and advantages/ disadvantages of the suggested process. The most important finding from the study was the recognition that most of the current municipal waste treatment technologies being employed, operate sub-optimally in Indian conditions. Therefore, the study using the available data, generated heat and mass balance of processes to arrive at the final technical process, which was broadly divided into Waste processing, Waste Treatment, Power Generation, through various permutations and combinations at each stage to ensure that the process is techno-commercially viable in Indian conditions. Then environmental impact was arrived through secondary sources and a comparison of environmental impact of different technologies was tabulated. The major advantages of the suggested process are the effective use of waste for resource generation both in terms of maximised power output or conversion to eco-friendly products like biofuels or chemicals using advanced technologies, minimum environmental impact and the least landfill requirement. The major drawbacks are the capital, operations and maintenance costs. The existing technologies in use in Indian municipalities have their own limitations and the shortlisted technology is far superior to other technologies in vogue. Treatment of Municipal Solid Waste with an efficient green power generation is possible through a combination of suitable environment-friendly technologies. A combination of bio-reactors and plasma-based gasification technology is most suitable for Indian Waste and in turn for Asian waste conditions.Keywords: calorific value, gas fermentation, landfill, municipal solid waste, plasma gasification, syngas
Procedia PDF Downloads 180351 MOF [(4,4-Bipyridine)₂(O₂CCH₃)₂Zn]N as Heterogeneous Acid Catalysts for the Transesterification of Canola Oil
Authors: H. Arceo, S. Rincon, C. Ben-Youssef, J. Rivera, A. Zepeda
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Biodiesel has emerged as a material with great potential as a renewable energy replacement to current petroleum-based diesel. Recently, biodiesel production is focused on the development of more efficient, sustainable process with lower costs of production. In this sense, a “green” approach to biodiesel production has stimulated the use of sustainable heterogeneous acid catalysts, that are better alternatives to conventional processes because of their simplicity and the simultaneous promotion of esterification and transesterification reactions from low-grade, highly-acidic and water containing oils without the formation of soap. The focus of this methodology is the development of new heterogeneous catalysts that under ordinary reaction conditions could reach yields similar to homogeneous catalysis. In recent years, metal organic frameworks (MOF) have attracted much interest for their potential as heterogeneous acid catalysts. They are crystalline porous solids formed by association of transition metal ions or metal–oxo clusters and polydentate organic ligands. This hybridization confers MOFs unique features such as high thermal stability, larger pore size, high specific area, high selectivity and recycling potential. Thus, MOF application could be a way to improve the biodiesel production processes. In this work, we evaluated the catalytic activity of MOF [(4,4-bipyridine)2(O₂CCH₃)2Zn]n (MOF Zn-I) for the synthesis of biodiesel from canola oil. The reaction conditions were optimized using the response surface methodology with a compound design central with 24. The variables studied were: Reaction temperature, amount of catalyst, molar ratio oil: MetOH and reaction time. The preparation MOF Zn-I was performed by mixing 5 mmol 4´4 dipyridine dissolved in 25 mL methanol with 10 mmol Zn(O₂CCH₃)₂ ∙ 2H₂O in 25 mL water. The crystals were obtained by slow evaporation of the solvents at 60°C for 18 h. The prepared catalyst was characterized using X-ray diffraction (XRD) and Fourier transform infrared spectrometer (FT-IR). The prepared catalyst was characterized using X-ray diffraction (XRD) and Fourier transform infrared spectrometer (FT-IR). Experiments were performed using commercially available canola oil in ace pressure tube under continuous stirring. The reaction was filtered and vacuum distilled to remove the catalyst and excess alcohol, after which it was centrifuged to separate the obtained biodiesel and glycerol. 1H NMR was used to calculate the process yield. GC-MS was used to quantify the fatty acid methyl ester (FAME). The results of this study show that the acid catalyst MOF Zn-I could be used as catalyst for biodiesel production through heterogeneous transesterification of canola oil with FAME yield 82 %. The optimum operating condition for the catalytic reaction were of 142°C, 0.5% catalyst/oil weight ratio, 1:30 oil:MeOH molar ratio and 5 h reaction time.Keywords: fatty acid methyl ester, heterogeneous acid catalyst, metal organic framework, transesterification
Procedia PDF Downloads 275350 Improved Signal-To-Noise Ratio by the 3D-Functionalization of Fully Zwitterionic Surface Coatings
Authors: Esther Van Andel, Stefanie C. Lange, Maarten M. J. Smulders, Han Zuilhof
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False outcomes of diagnostic tests are a major concern in medical health care. To improve the reliability of surface-based diagnostic tests, it is of crucial importance to diminish background signals that arise from the non-specific binding of biomolecules, a process called fouling. The aim is to create surfaces that repel all biomolecules except the molecule of interest. This can be achieved by incorporating antifouling protein repellent coatings in between the sensor surface and it’s recognition elements (e.g. antibodies, sugars, aptamers). Zwitterionic polymer brushes are considered excellent antifouling materials, however, to be able to bind the molecule of interest, the polymer brushes have to be functionalized and so far this was only achieved at the expense of either antifouling or binding capacity. To overcome this limitation, we combined both features into one single monomer: a zwitterionic sulfobetaine, ensuring antifouling capabilities, equipped with a clickable azide moiety which allows for further functionalization. By copolymerizing this monomer together with a standard sulfobetaine, the number of azides (and with that the number of recognition elements) can be tuned depending on the application. First, the clickable azido-monomer was synthesized and characterized, followed by copolymerizing this monomer to yield functionalizable antifouling brushes. The brushes were fully characterized using surface characterization techniques like XPS, contact angle measurements, G-ATR-FTIR and XRR. As a proof of principle, the brushes were subsequently functionalized with biotin via strain-promoted alkyne azide click reactions, which yielded a fully zwitterionic biotin-containing 3D-functionalized coating. The sensing capacity was evaluated by reflectometry using avidin and fibrinogen containing protein solutions. The surfaces showed excellent antifouling properties as illustrated by the complete absence of non-specific fibrinogen binding, while at the same time clear responses were seen for the specific binding of avidin. A great increase in signal-to-noise ratio was observed, even when the amount of functional groups was lowered to 1%, compared to traditional modification of sulfobetaine brushes that rely on a 2D-approach in which only the top-layer can be functionalized. This study was performed on stoichiometric silicon nitride surfaces for future microring resonator based assays, however, this methodology can be transferred to other biosensor platforms which are currently being investigated. The approach presented herein enables a highly efficient strategy for selective binding with retained antifouling properties for improved signal-to-noise ratios in binding assays. The number of recognition units can be adjusted to a specific need, e.g. depending on the size of the analyte to be bound, widening the scope of these functionalizable surface coatings.Keywords: antifouling, signal-to-noise ratio, surface functionalization, zwitterionic polymer brushes
Procedia PDF Downloads 301349 Detection the Ice Formation Processes Using Multiple High Order Ultrasonic Guided Wave Modes
Authors: Regina Rekuviene, Vykintas Samaitis, Liudas Mažeika, Audrius Jankauskas, Virginija Jankauskaitė, Laura Gegeckienė, Abdolali Sadaghiani, Shaghayegh Saeidiharzand
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Icing brings significant damage to aviation and renewable energy installations. Air-conditioning, refrigeration, wind turbine blades, airplane and helicopter blades often suffer from icing phenomena, which cause severe energy losses and impair aerodynamic performance. The icing process is a complex phenomenon with many different causes and types. Icing mechanisms, distributions, and patterns are still relevant to research topics. The adhesion strength between ice and surfaces differs in different icing environments. This makes the task of anti-icing very challenging. The techniques for various icing environments must satisfy different demands and requirements (e.g., efficient, lightweight, low power consumption, low maintenance and manufacturing costs, reliable operation). It is noticeable that most methods are oriented toward a particular sector and adapting them to or suggesting them for other areas is quite problematic. These methods often use various technologies and have different specifications, sometimes with no clear indication of their efficiency. There are two major groups of anti-icing methods: passive and active. Active techniques have high efficiency but, at the same time, quite high energy consumption and require intervention in the structure’s design. It’s noticeable that vast majority of these methods require specific knowledge and personnel skills. The main effect of passive methods (ice-phobic, superhydrophobic surfaces) is to delay ice formation and growth or reduce the adhesion strength between the ice and the surface. These methods are time-consuming and depend on forecasting. They can be applied on small surfaces only for specific targets, and most are non-biodegradable (except for anti-freezing proteins). There is some quite promising information on ultrasonic ice mitigation methods that employ UGW (Ultrasonic Guided Wave). These methods are have the characteristics of low energy consumption, low cost, lightweight, and easy replacement and maintenance. However, fundamental knowledge of ultrasonic de-icing methodology is still limited. The objective of this work was to identify the ice formation processes and its progress by employing ultrasonic guided wave technique. Throughout this research, the universal set-up for acoustic measurement of ice formation in a real condition (temperature range from +240 C to -230 C) was developed. Ultrasonic measurements were performed by using high frequency 5 MHz transducers in a pitch-catch configuration. The selection of wave modes suitable for detection of ice formation phenomenon on copper metal surface was performed. Interaction between the selected wave modes and ice formation processes was investigated. It was found that selected wave modes are sensitive to temperature changes. It was demonstrated that proposed ultrasonic technique could be successfully used for the detection of ice layer formation on a metal surface.Keywords: ice formation processes, ultrasonic GW, detection of ice formation, ultrasonic testing
Procedia PDF Downloads 57348 Regeneration of Cesium-Exhausted Activated Carbons by Microwave Irradiation
Authors: Pietro P. Falciglia, Erica Gagliano, Vincenza Brancato, Alfio Catalfo, Guglielmo Finocchiaro, Guido De Guidi, Stefano Romano, Paolo Roccaro, Federico G. A. Vagliasindi
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Cesium-137 (¹³⁷Cs) is a major radionuclide in spent nuclear fuel processing, and it represents the most important cause of contamination related to nuclear accidents. Cesium-137 has long-term radiological effects representing a major concern for the human health. Several physico-chemical methods have been proposed for ¹³⁷Cs removal from impacted water: ion-exchange, adsorption, chemical precipitation, membrane process, coagulation, and electrochemical. However, these methods can be limited by ionic selectivity and efficiency, or they present very restricted full-scale application due to equipment and chemical high costs. On the other hand, adsorption is considered a more cost-effective solution, and activated carbons (ACs) are known as a low-cost and effective adsorbent for a wide range of pollutants among which radionuclides. However, adsorption of Cs onto ACs has been investigated in very few and not exhaustive studies. In addition, exhausted activated carbons are generally discarded in landfill, that is not an eco-friendly and economic solution. Consequently, the regeneration of exhausted ACs must be considered a preferable choice. Several alternatives, including conventional thermal-, solvent-, biological- and electrochemical-regeneration, are available but are affected by several economic or environmental concerns. Microwave (MW) irradiation has been widely used in industrial and environmental applications and it has attracted many attentions to regenerating activated carbons. The growing interest in MW irradiation is based on the passive ability of the irradiated medium to convert a low power irradiation energy into a rapid and large temperature increase if the media presents good dielectric features. ACs are excellent MW-absorbers, with a high mechanical strength and a good resistance towards heating process. This work investigates the feasibility of MW irradiation for the regeneration of Cs-exhausted ACs. Adsorption batch experiments were carried out using commercially available granular activated carbon (GAC), then Cs-saturated AC samples were treated using a controllable bench-scale 2.45-GHz MW oven and investigating different adsorption-regeneration cycles. The regeneration efficiency (RE), weight loss percentage, and textural properties of the AC samples during the adsorption-regeneration cycles were also assessed. Main results demonstrated a relatively low adsorption capacity for Cs, although the feasibility of ACs was strictly linked to their dielectric nature, which allows a very efficient thermal regeneration by MW irradiation. The weight loss percentage was found less than 2%, and an increase in RE after three cycles was also observed. Furthermore, MW regeneration preserved the pore structure of the regenerated ACs. For a deeper exploration of the full-scale applicability of MW regeneration, further investigations on more adsorption-regeneration cycles or using fixed-bed columns are required.Keywords: adsorption mechanisms, cesium, granular activated carbons, microwave regeneration
Procedia PDF Downloads 136347 Establishment of Precision System for Underground Facilities Based on 3D Absolute Positioning Technology
Authors: Yonggu Jang, Jisong Ryu, Woosik Lee
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The study aims to address the limitations of existing underground facility exploration equipment in terms of exploration depth range, relative depth measurement, data processing time, and human-centered ground penetrating radar image interpretation. The study proposed the use of 3D absolute positioning technology to develop a precision underground facility exploration system. The aim of this study is to establish a precise exploration system for underground facilities based on 3D absolute positioning technology, which can accurately survey up to a depth of 5m and measure the 3D absolute location of precise underground facilities. The study developed software and hardware technologies to build the precision exploration system. The software technologies developed include absolute positioning technology, ground surface location synchronization technology of GPR exploration equipment, GPR exploration image AI interpretation technology, and integrated underground space map-based composite data processing technology. The hardware systems developed include a vehicle-type exploration system and a cart-type exploration system. The data was collected using the developed exploration system, which employs 3D absolute positioning technology. The GPR exploration images were analyzed using AI technology, and the three-dimensional location information of the explored precise underground facilities was compared to the integrated underground space map. The study successfully developed a precision underground facility exploration system based on 3D absolute positioning technology. The developed exploration system can accurately survey up to a depth of 5m and measure the 3D absolute location of precise underground facilities. The system comprises software technologies that build a 3D precise DEM, synchronize the GPR sensor's ground surface 3D location coordinates, automatically analyze and detect underground facility information in GPR exploration images and improve accuracy through comparative analysis of the three-dimensional location information, and hardware systems, including a vehicle-type exploration system and a cart-type exploration system. The study's findings and technological advancements are essential for underground safety management in Korea. The proposed precision exploration system significantly contributes to establishing precise location information of underground facility information, which is crucial for underground safety management and improves the accuracy and efficiency of exploration. The study addressed the limitations of existing equipment in exploring underground facilities, proposed 3D absolute positioning technology-based precision exploration system, developed software and hardware systems for the exploration system, and contributed to underground safety management by providing precise location information. The developed precision underground facility exploration system based on 3D absolute positioning technology has the potential to provide accurate and efficient exploration of underground facilities up to a depth of 5m. The system's technological advancements contribute to the establishment of precise location information of underground facility information, which is essential for underground safety management in Korea.Keywords: 3D absolute positioning, AI interpretation of GPR exploration images, complex data processing, integrated underground space maps, precision exploration system for underground facilities
Procedia PDF Downloads 55346 A Practical Construction Technique to Enhance the Performance of Rock Bolts in Tunnels
Authors: Ojas Chaudhari, Ali Nejad Ghafar, Giedrius Zirgulis, Marjan Mousavi, Tommy Ellison, Sandra Pousette, Patrick Fontana
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In Swedish tunnel construction, a critical issue that has been repeatedly acknowledged is corrosion and, consequently, failure of the rock bolts in rock support systems. The defective installation of rock bolts results in the formation of cavities in the cement mortar that is regularly used to fill the area under the dome plates. These voids allow for water-ingress to the rock bolt assembly, which results in corrosion of rock bolt components and eventually failure. In addition, the current installation technique consists of several manual steps with intense labor works that are usually done in uncomfortable and exhausting conditions, e.g., under the roof of the tunnels. Such intense tasks also lead to a considerable waste of materials and execution errors. Moreover, adequate quality control of the execution is hardly possible with the current technique. To overcome these issues, a non-shrinking/expansive cement-based mortar filled in the paper packaging has been developed in this study which properly fills the area under the dome plates without or with the least remaining cavities, ultimately that diminishes the potential of corrosion. This article summarizes the development process and the experimental evaluation of this technique for the installation of rock bolts. In the development process, the cementitious mortar was first developed using specific cement and shrinkage reducing/expansive additives. The mechanical and flow properties of the mortar were then evaluated using compressive strength, density, and slump flow measurement methods. In addition, isothermal calorimetry and shrinkage/expansion measurements were used to elucidate the hydration and durability attributes of the mortar. After obtaining the desired properties in both fresh and hardened conditions, the developed dry mortar was filled in specific permeable paper packaging and then submerged in water bath for specific intervals before the installation. The tests were enhanced progressively by optimizing different parameters such as shape and size of the packaging, characteristics of the paper used, immersion time in water and even some minor characteristics of the mortar. Finally, the developed prototype was tested in a lab-scale rock bolt assembly with various angles to analyze the efficiency of the method in real life scenario. The results showed that the new technique improves the performance of the rock bolts by reducing the material wastage, improving environmental performance, facilitating and accelerating the labor works, and finally enhancing the durability of the whole system. Accordingly, this approach provides an efficient alternative for the traditional way of tunnel bolt installation with considerable advantages for the Swedish tunneling industry.Keywords: corrosion, durability, mortar, rock bolt
Procedia PDF Downloads 107345 An Overview of Bioinformatics Methods to Detect Novel Riboswitches Highlighting the Importance of Structure Consideration
Authors: Danny Barash
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Riboswitches are RNA genetic control elements that were originally discovered in bacteria and provide a unique mechanism of gene regulation. They work without the participation of proteins and are believed to represent ancient regulatory systems in the evolutionary timescale. One of the biggest challenges in riboswitch research is that many are found in prokaryotes but only a small percentage of known riboswitches have been found in certain eukaryotic organisms. The few examples of eukaryotic riboswitches were identified using sequence-based bioinformatics search methods that include some slight structural considerations. These pattern-matching methods were the first ones to be applied for the purpose of riboswitch detection and they can also be programmed very efficiently using a data structure called affix arrays, making them suitable for genome-wide searches of riboswitch patterns. However, they are limited by their ability to detect harder to find riboswitches that deviate from the known patterns. Several methods have been developed since then to tackle this problem. The most commonly used by practitioners is Infernal that relies on Hidden Markov Models (HMMs) and Covariance Models (CMs). Profile Hidden Markov Models were also carried out in the pHMM Riboswitch Scanner web application, independently from Infernal. Other computational approaches that have been developed include RMDetect by the use of 3D structural modules and RNAbor that utilizes Boltzmann probability of structural neighbors. We have tried to incorporate more sophisticated secondary structure considerations based on RNA folding prediction using several strategies. The first idea was to utilize window-based methods in conjunction with folding predictions by energy minimization. The moving window approach is heavily geared towards secondary structure consideration relative to sequence that is treated as a constraint. However, the method cannot be used genome-wide due to its high cost because each folding prediction by energy minimization in the moving window is computationally expensive, enabling to scan only at the vicinity of genes of interest. The second idea was to remedy the inefficiency of the previous approach by constructing a pipeline that consists of inverse RNA folding considering RNA secondary structure, followed by a BLAST search that is sequence-based and highly efficient. This approach, which relies on inverse RNA folding in general and our own in-house fragment-based inverse RNA folding program called RNAfbinv in particular, shows capability to find attractive candidates that are missed by Infernal and other standard methods being used for riboswitch detection. We demonstrate attractive candidates found by both the moving-window approach and the inverse RNA folding approach performed together with BLAST. We conclude that structure-based methods like the two strategies outlined above hold considerable promise in detecting riboswitches and other conserved RNAs of functional importance in a variety of organisms.Keywords: riboswitches, RNA folding prediction, RNA structure, structure-based methods
Procedia PDF Downloads 231344 A Fast Multi-Scale Finite Element Method for Geophysical Resistivity Measurements
Authors: Mostafa Shahriari, Sergio Rojas, David Pardo, Angel Rodriguez- Rozas, Shaaban A. Bakr, Victor M. Calo, Ignacio Muga
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Logging-While Drilling (LWD) is a technique to record down-hole logging measurements while drilling the well. Nowadays, LWD devices (e.g., nuclear, sonic, resistivity) are mostly used commercially for geo-steering applications. Modern borehole resistivity tools are able to measure all components of the magnetic field by incorporating tilted coils. The depth of investigation of LWD tools is limited compared to the thickness of the geological layers. Thus, it is a common practice to approximate the Earth’s subsurface with a sequence of 1D models. For a 1D model, we can reduce the dimensionality of the problem using a Hankel transform. We can solve the resulting system of ordinary differential equations (ODEs) either (a) analytically, which results in a so-called semi-analytic method after performing a numerical inverse Hankel transform, or (b) numerically. Semi-analytic methods are used by the industry due to their high performance. However, they have major limitations, namely: -The analytical solution of the aforementioned system of ODEs exists only for piecewise constant resistivity distributions. For arbitrary resistivity distributions, the solution of the system of ODEs is unknown by today’s knowledge. -In geo-steering, we need to solve inverse problems with respect to the inversion variables (e.g., the constant resistivity value of each layer and bed boundary positions) using a gradient-based inversion method. Thus, we need to compute the corresponding derivatives. However, the analytical derivatives of cross-bedded formation and the analytical derivatives with respect to the bed boundary positions have not been published to the best of our knowledge. The main contribution of this work is to overcome the aforementioned limitations of semi-analytic methods by solving each 1D model (associated with each Hankel mode) using an efficient multi-scale finite element method. The main idea is to divide our computations into two parts: (a) offline computations, which are independent of the tool positions and we precompute only once and use them for all logging positions, and (b) online computations, which depend upon the logging position. With the above method, (a) we can consider arbitrary resistivity distributions along the 1D model, and (b) we can easily and rapidly compute the derivatives with respect to any inversion variable at a negligible additional cost by using an adjoint state formulation. Although the proposed method is slower than semi-analytic methods, its computational efficiency is still high. In the presentation, we shall derive the mathematical variational formulation, describe the proposed multi-scale finite element method, and verify the accuracy and efficiency of our method by performing a wide range of numerical experiments and comparing the numerical solutions to semi-analytic ones when the latest are available.Keywords: logging-While-Drilling, resistivity measurements, multi-scale finite elements, Hankel transform
Procedia PDF Downloads 380343 Moderate Electric Field and Ultrasound as Alternative Technologies to Raspberry Juice Pasteurization Process
Authors: Cibele F. Oliveira, Debora P. Jaeschke, Rodrigo R. Laurino, Amanda R. Andrade, Ligia D. F. Marczak
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Raspberry is well-known as a good source of phenolic compounds, mainly anthocyanin. Some studies pointed out the importance of these bioactive compounds consumption, which is related to the decrease of the risk of cancer and cardiovascular diseases. The most consumed raspberry products are juices, yogurts, ice creams and jellies and, to ensure the safety of these products, raspberry is commonly pasteurized, for enzyme and microorganisms inactivation. Despite being efficient, the pasteurization process can lead to degradation reactions of the bioactive compounds, decreasing the products healthy benefits. Therefore, the aim of the present work was to evaluate moderate electric field (MEF) and ultrasound (US) technologies application on the pasteurization process of raspberry juice and compare the results with conventional pasteurization process. For this, phenolic compounds, anthocyanin content and physical-chemical parameters (pH, color changes, titratable acidity) of the juice were evaluated before and after the treatments. Moreover, microbiological analyses of aerobic mesophiles microorganisms, molds and yeast were performed in the samples before and after the treatments, to verify the potential of these technologies to inactivate microorganisms. All the pasteurization processes were performed in triplicate for 10 min, using a cylindrical Pyrex® vessel with a water jacket. The conventional pasteurization was performed at 90 °C using a hot water bath connected to the extraction cell. The US assisted pasteurization was performed using 423 and 508 W cm-2 (75 and 90 % of ultrasound intensity). It is important to mention that during US application the temperature was kept below 35 °C; for this, the water jacket of the extraction cell was connected to a water bath with cold water. MEF assisted pasteurization experiments were performed similarly to US experiments, using 25 and 50 V. Control experiments were performed at the maximum temperature of US and MEF experiments (35 °C) to evaluate only the effect of the aforementioned technologies on the pasteurization. The results showed that phenolic compounds concentration in the juice was not affected by US and MEF application. However, it was observed that the US assisted pasteurization, performed at the highest intensity, decreased anthocyanin content in 33 % (compared to in natura juice). This result was possibly due to the cavitation phenomena, which can lead to free radicals formation and accumulation on the medium; these radicals can react with anthocyanin decreasing the content of these antioxidant compounds in the juice. Physical-chemical parameters did not present statistical differences for samples before and after the treatments. Microbiological analyses results showed that all the pasteurization treatments decreased the microorganism content in two logarithmic cycles. However, as values were lower than 1000 CFU mL-1 it was not possible to verify the efficacy of each treatment. Thus, MEF and US were considered as potential alternative technologies for pasteurization process, once in the right conditions the application of the technologies decreased microorganism content in the juice and did not affected phenolic and anthocyanin content, as well as physical-chemical parameters. However, more studies are needed regarding the influence of MEF and US processes on microorganisms’ inactivation.Keywords: MEF, microorganism inactivation, anthocyanin, phenolic compounds
Procedia PDF Downloads 237342 Integrating Natural Language Processing (NLP) and Machine Learning in Lung Cancer Diagnosis
Authors: Mehrnaz Mostafavi
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The assessment and categorization of incidental lung nodules present a considerable challenge in healthcare, often necessitating resource-intensive multiple computed tomography (CT) scans for growth confirmation. This research addresses this issue by introducing a distinct computational approach leveraging radiomics and deep-learning methods. However, understanding local services is essential before implementing these advancements. With diverse tracking methods in place, there is a need for efficient and accurate identification approaches, especially in the context of managing lung nodules alongside pre-existing cancer scenarios. This study explores the integration of text-based algorithms in medical data curation, indicating their efficacy in conjunction with machine learning and deep-learning models for identifying lung nodules. Combining medical images with text data has demonstrated superior data retrieval compared to using each modality independently. While deep learning and text analysis show potential in detecting previously missed nodules, challenges persist, such as increased false positives. The presented research introduces a Structured-Query-Language (SQL) algorithm designed for identifying pulmonary nodules in a tertiary cancer center, externally validated at another hospital. Leveraging natural language processing (NLP) and machine learning, the algorithm categorizes lung nodule reports based on sentence features, aiming to facilitate research and assess clinical pathways. The hypothesis posits that the algorithm can accurately identify lung nodule CT scans and predict concerning nodule features using machine-learning classifiers. Through a retrospective observational study spanning a decade, CT scan reports were collected, and an algorithm was developed to extract and classify data. Results underscore the complexity of lung nodule cohorts in cancer centers, emphasizing the importance of careful evaluation before assuming a metastatic origin. The SQL and NLP algorithms demonstrated high accuracy in identifying lung nodule sentences, indicating potential for local service evaluation and research dataset creation. Machine-learning models exhibited strong accuracy in predicting concerning changes in lung nodule scan reports. While limitations include variability in disease group attribution, the potential for correlation rather than causality in clinical findings, and the need for further external validation, the algorithm's accuracy and potential to support clinical decision-making and healthcare automation represent a significant stride in lung nodule management and research.Keywords: lung cancer diagnosis, structured-query-language (SQL), natural language processing (NLP), machine learning, CT scans
Procedia PDF Downloads 81341 Contribution of Word Decoding and Reading Fluency on Reading Comprehension in Young Typical Readers of Kannada Language
Authors: Vangmayee V. Subban, Suzan Deelan. Pinto, Somashekara Haralakatta Shivananjappa, Shwetha Prabhu, Jayashree S. Bhat
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Introduction and Need: During early years of schooling, the instruction in the schools mainly focus on children’s word decoding abilities. However, the skilled readers should master all the components of reading such as word decoding, reading fluency and comprehension. Nevertheless, the relationship between each component during the process of learning to read is less clear. The studies conducted in alphabetical languages have mixed opinion on relative contribution of word decoding and reading fluency on reading comprehension. However, the scenarios in alphasyllabary languages are unexplored. Aim and Objectives: The aim of the study was to explore the role of word decoding, reading fluency on reading comprehension abilities in children learning to read Kannada between the age ranges of 5.6 to 8.6 years. Method: In this cross sectional study, a total of 60 typically developing children, 20 each from Grade I, Grade II, Grade III maintaining equal gender ratio between the age range of 5.6 to 6.6 years, 6.7 to 7.6 years and 7.7 to 8.6 years respectively were selected from Kannada medium schools. The reading fluency and reading comprehension abilities of the children were assessed using Grade level passages selected from the Kannada text book of children core curriculum. All the passages consist of five questions to assess reading comprehension. The pseudoword decoding skills were assessed using 40 pseudowords with varying syllable length and their Akshara composition. Pseudowords are formed by interchanging the syllables within the meaningful word while maintaining the phonotactic constraints of Kannada language. The assessment material was subjected to content validation and reliability measures before collecting the data on the study samples. The data were collected individually, and reading fluency was assessed for words correctly read per minute. Pseudoword decoding was scored for the accuracy of reading. Results: The descriptive statistics indicated that the mean pseudoword reading, reading comprehension, words accurately read per minute increased with the Grades. The performance of Grade III children found to be higher, Grade I lower and Grade II remained intermediate of Grade III and Grade I. The trend indicated that reading skills gradually improve with the Grades. Pearson’s correlation co-efficient showed moderate and highly significant (p=0.00) positive co-relation between the variables, indicating the interdependency of all the three components required for reading. The hierarchical regression analysis revealed 37% variance in reading comprehension was explained by pseudoword decoding and was highly significant. Subsequent entry of reading fluency measure, there was no significant change in R-square and was only change 3%. Therefore, pseudoword-decoding evolved as a single most significant predictor of reading comprehension during early Grades of reading acquisition. Conclusion: The present study concludes that the pseudoword decoding skills contribute significantly to reading comprehension than reading fluency during initial years of schooling in children learning to read Kannada language.Keywords: alphasyllabary, pseudo-word decoding, reading comprehension, reading fluency
Procedia PDF Downloads 255340 Preparation of Activated Carbon From Waste Feedstock: Activation Variables Optimization and Influence
Authors: Oluwagbemi Victor Aladeokin
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In the last decade, the global peanut cultivation has seen increased demand, which is attributed to their health benefits, rising to ~ 41.4 MMT in 2019/2020. Peanut and other nutshells are considered as waste in various parts of the world and are usually used for their fuel value. However, this agricultural by-product can be converted to a higher value product such as activated carbon. For many years, due to the highly porous structure of activated carbon, it has been widely and effectively used as an adsorbent in the purification and separation of gases and liquids. Those used for commercial purposes are primarily made from a range of precursors such as wood, coconut shell, coal, bones, etc. However, due to difficulty in regeneration and high cost, various agricultural residues such as rice husk, corn stalks, apricot stones, almond shells, coffee beans, etc, have been explored to produce activated carbons. In the present study, the potential of peanut shells as precursors in the production of activated carbon and their adsorption capacity is investigated. Usually, precursors used to produce activated carbon have carbon content above 45 %. A typical raw peanut shell has 42 wt.% carbon content. To increase the yield, this study has employed chemical activation method using zinc chloride. Zinc chloride is well known for its effectiveness in increasing porosity of porous carbonaceous materials. In chemical activation, activation temperature and impregnation ratio are parameters commonly reported to be the most significant, however, this study has also studied the influence of activation time on the development of activated carbon from peanut shells. Activated carbons are applied for different purposes, however, as the application of activated carbon becomes more specific, an understanding of the influence of activation variables to have a better control of the quality of the final product becomes paramount. A traditional approach to experimentally investigate the influence of the activation parameters, involves varying each parameter at a time. However, a more efficient way to reduce the number of experimental runs is to apply design of experiment. One of the objectives of this study is to optimize the activation variables. Thus, this work has employed response surface methodology of design of experiment to study the interactions between the activation parameters and consequently optimize the activation parameters (temperature, impregnation ratio, and activation time). The optimum activation conditions found were 485 °C, 15 min and 1.7, temperature, activation time, and impregnation ratio respectively. The optimum conditions resulted in an activated carbon with relatively high surface area ca. 1700 m2/g, 47 % yield, relatively high density, low ash, and high fixed carbon content. Impregnation ratio and temperature were found to mostly influence the final characteristics of the produced activated carbon from peanut shells. The results of this study, using response surface methodology technique, have revealed the potential and the most significant parameters that influence the chemical activation process, of peanut shells to produce activated carbon which can find its use in both liquid and gas phase adsorption applications.Keywords: chemical activation, fixed carbon, impregnation ratio, optimum, surface area
Procedia PDF Downloads 138339 Magnetofluidics for Mass Transfer and Mixing Enhancement in a Micro Scale Device
Authors: Majid Hejazian, Nam-Trung Nguyen
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Over the past few years, microfluidic devices have generated significant attention from industry and academia due to advantages such as small sample volume, low cost and high efficiency. Microfluidic devices have applications in chemical, biological and industry analysis and can facilitate assay of bio-materials and chemical reactions, separation, and sensing. Micromixers are one of the important microfluidic concepts. Micromixers can work as stand-alone devices or be integrated in a more complex microfluidic system such as a lab on a chip (LOC). Micromixers are categorized as passive and active types. Passive micromixers rely only on the arrangement of the phases to be mixed and contain no moving parts and require no energy. Active micromixers require external fields such as pressure, temperature, electric and acoustic fields. Rapid and efficient mixing is important for many applications such as biological, chemical and biochemical analysis. Achieving fast and homogenous mixing of multiple samples in the microfluidic devices has been studied and discussed in the literature recently. Improvement in mixing rely on effective mass transport in microscale, but are currently limited to molecular diffusion due to the predominant laminar flow in this size scale. Using magnetic field to elevate mass transport is an effective solution for mixing enhancement in microfluidics. The use of a non-uniform magnetic field to improve mass transfer performance in a microfluidic device is demonstrated in this work. The phenomenon of mixing ferrofluid and DI-water streams has been reported before, but mass transfer enhancement for other non-magnetic species through magnetic field have not been studied and evaluated extensively. In the present work, permanent magnets were used in a simple microfluidic device to create a non-uniform magnetic field. Two streams are introduced into the microchannel: one contains fluorescent dye mixed with diluted ferrofluid to induce enhanced mass transport of the dye, and the other one is a non-magnetic DI-water stream. Mass transport enhancement of fluorescent dye is evaluated using fluorescent measurement techniques. The concentration field is measured for different flow rates. Due to effect of magnetic field, a body force is exerted on the paramagnetic stream and expands the ferrofluid stream into non-magnetic DI-water flow. The experimental results demonstrate that without a magnetic field, both magnetic nanoparticles of the ferrofluid and the fluorescent dye solely rely on molecular diffusion to spread. The non-uniform magnetic field, created by the permanent magnets around the microchannel, and diluted ferrofluid can improve mass transport of non-magnetic solutes in a microfluidic device. The susceptibility mismatch between the fluids results in a magnetoconvective secondary flow towards the magnets and subsequently the mass transport of the non-magnetic fluorescent dye. A significant enhancement in mass transport of the fluorescent dye was observed. The platform presented here could be used as a microfluidics-based micromixer for chemical and biological applications.Keywords: ferrofluid, mass transfer, micromixer, microfluidics, magnetic
Procedia PDF Downloads 218338 Evaluation of Modern Natural Language Processing Techniques via Measuring a Company's Public Perception
Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu
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Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish
Procedia PDF Downloads 136337 Using Convolutional Neural Networks to Distinguish Different Sign Language Alphanumerics
Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin
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Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.Keywords: convolutional neural networks, deep learning, shallow correctors, sign language
Procedia PDF Downloads 96336 Application of Typha domingensis Pers. in Artificial Floating for Sewage Treatment
Authors: Tatiane Benvenuti, Fernando Hamerski, Alexandre Giacobbo, Andrea M. Bernardes, Marco A. S. Rodrigues
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Population growth in urban areas has caused damages to the environment, a consequence of the uncontrolled dumping of domestic and industrial wastewater. The capacity of some plants to purify domestic and agricultural wastewater has been demonstrated by several studies. Since natural wetlands have the ability to transform, retain and remove nutrients, constructed wetlands have been used for wastewater treatment. They are widely recognized as an economical, efficient and environmentally acceptable means of treating many different types of wastewater. T. domingensis Pers. species have shown a good performance and low deployment cost to extract, detoxify and sequester pollutants. Constructed Floating Wetlands (CFWs) consist of emergent vegetation established upon a buoyant structure, floating on surface waters. The upper parts of the vegetation grow and remain primarily above the water level, while the roots extend down in the water column, developing an extensive under water-level root system. Thus, the vegetation grows hydroponically, performing direct nutrient uptake from the water column. Biofilm is attached on the roots and rhizomes, and as physical and biochemical processes take place, the system functions as a natural filter. The aim of this study is to diagnose the application of macrophytes in artificial floating in the treatment of domestic sewage in south Brazil. The T. domingensis Pers. plants were placed in a flotation system (polymer structure), in full scale, in a sewage treatment plant. The sewage feed rate was 67.4 m³.d⁻¹ ± 8.0, and the hydraulic retention time was 11.5 d ± 1.3. This CFW treat the sewage generated by 600 inhabitants, which corresponds to 12% of the population served by this municipal treatment plant. During 12 months, samples were collected every two weeks, in order to evaluate parameters as chemical oxygen demand (COD), biochemical oxygen demand in 5 days (BOD5), total Kjeldahl nitrogen (TKN), total phosphorus, total solids, and metals. The average removal of organic matter was around 55% for both COD and BOD5. For nutrients, TKN was reduced in 45.9% what was similar to the total phosphorus removal, while for total solids the reduction was 33%. For metals, aluminum, copper, and cadmium, besides in low concentrations, presented the highest percentage reduction, 82.7, 74.4 and 68.8% respectively. Chromium, iron, and manganese removal achieved values around 40-55%. The use of T. domingensis Pers. in artificial floating for sewage treatment is an effective and innovative alternative in Brazilian sewage treatment systems. The evaluation of additional parameters in the treatment system may give useful information in order to improve the removal efficiency and increase the quality of the water bodies.Keywords: constructed wetland, floating system, sewage treatment, Typha domingensis Pers.
Procedia PDF Downloads 206335 Electro-Hydrodynamic Effects Due to Plasma Bullet Propagation
Authors: Panagiotis Svarnas, Polykarpos Papadopoulos
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Atmospheric-pressure cold plasmas continue to gain increasing interest for various applications due to their unique properties, like cost-efficient production, high chemical reactivity, low gas temperature, adaptability, etc. Numerous designs have been proposed for these plasmas production in terms of electrode configuration, driving voltage waveform and working gas(es). However, in order to exploit most of the advantages of these systems, the majority of the designs are based on dielectric-barrier discharges (DBDs) either in filamentary or glow regimes. A special category of the DBD-based atmospheric-pressure cold plasmas refers to the so-called plasma jets, where a carrier noble gas is guided by the dielectric barrier (usually a hollow cylinder) and left to flow up to the atmospheric air where a complicated hydrodynamic interplay takes place. Although it is now well established that these plasmas are generated due to ionizing waves reminding in many ways streamer propagation, they exhibit discrete characteristics which are better mirrored on the terms 'guided streamers' or 'plasma bullets'. These 'bullets' travel with supersonic velocities both inside the dielectric barrier and the channel formed by the noble gas during its penetration into the air. The present work is devoted to the interpretation of the electro-hydrodynamic effects that take place downstream of the dielectric barrier opening, i.e., in the noble gas-air mixing area where plasma bullet propagate under the influence of local electric fields in regions of variable noble gas concentration. Herein, we focus on the role of the local space charge and the residual ionic charge left behind after the bullet propagation in the gas flow field modification. The study communicates both experimental and numerical results, coupled in a comprehensive manner. The plasma bullets are here produced by a custom device having a quartz tube as a dielectric barrier and two external ring-type electrodes driven by sinusoidal high voltage at 10 kHz. Helium gas is fed to the tube and schlieren photography is employed for mapping the flow field downstream of the tube orifice. Mixture mass conservation equation, momentum conservation equation, energy conservation equation in terms of temperature and helium transfer equation are simultaneously solved, leading to the physical mechanisms that govern the experimental results. Namely, we deal with electro-hydrodynamic effects mainly due to momentum transfer from atomic ions to neutrals. The atomic ions are left behind as residual charge after the bullet propagation and gain energy from the locally created electric field. The electro-hydrodynamic force is eventually evaluated.Keywords: atmospheric-pressure plasmas, dielectric-barrier discharges, schlieren photography, electro-hydrodynamic force
Procedia PDF Downloads 134334 Voyage Analysis of a Marine Gas Turbine Engine Installed to Power and Propel an Ocean-Going Cruise Ship
Authors: Mathias U. Bonet, Pericles Pilidis, Georgios Doulgeris
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A gas turbine-powered cruise Liner is scheduled to transport pilgrim passengers from Lagos-Nigeria to the Islamic port city of Jeddah in Saudi Arabia. Since the gas turbine is an air breathing machine, changes in the density and/or mass flow at the compressor inlet due to an encounter with variations in weather conditions induce negative effects on the performance of the power plant during the voyage. In practice, all deviations from the reference atmospheric conditions of 15 oC and 1.103 bar tend to affect the power output and other thermodynamic parameters of the gas turbine cycle. Therefore, this paper seeks to evaluate how a simple cycle marine gas turbine power plant would react under a variety of scenarios that may be encountered during a voyage as the ship sails across the Atlantic Ocean and the Mediterranean Sea before arriving at its designated port of discharge. It is also an assessment that focuses on the effect of varying aerodynamic and hydrodynamic conditions which deteriorate the efficient operation of the propulsion system due to an increase in resistance that results from some projected levels of the ship hull fouling. The investigated passenger ship is designed to run at a service speed of 22 knots and cover a distance of 5787 nautical miles. The performance evaluation consists of three separate voyages that cover a variety of weather conditions in winter, spring and summer seasons. Real-time daily temperatures and the sea states for the selected transit route were obtained and used to simulate the voyage under the aforementioned operating conditions. Changes in engine firing temperature, power output as well as the total fuel consumed per voyage including other performance variables were separately predicted under both calm and adverse weather conditions. The collated data were obtained online from the UK Meteorological Office as well as the UK Hydrographic Office websites, while adopting the Beaufort scale for determining the magnitude of sea waves resulting from rough weather situations. The simulation of the gas turbine performance and voyage analysis was effected through the use of an integrated Cranfield-University-developed computer code known as ‘Turbomatch’ and ‘Poseidon’. It is a project that is aimed at developing a method for predicting the off design behavior of the marine gas turbine when installed and operated as the main prime mover for both propulsion and powering of all other auxiliary services onboard a passenger cruise liner. Furthermore, it is a techno-economic and environmental assessment that seeks to enable the forecast of the marine gas turbine part and full load performance as it relates to the fuel requirement for a complete voyage.Keywords: cruise ship, gas turbine, hull fouling, performance, propulsion, weather
Procedia PDF Downloads 162333 3D Classification Optimization of Low-Density Airborne Light Detection and Ranging Point Cloud by Parameters Selection
Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa
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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.Keywords: classification, airborne LiDAR, parameters selection, support vector machine
Procedia PDF Downloads 144332 Tall Building Transit-Oriented Development (TB-TOD) and Energy Efficiency in Suburbia: Case Studies, Sydney, Toronto, and Washington D.C.
Authors: Narjes Abbasabadi
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As the world continues to urbanize and suburbanize, where suburbanization associated with mass sprawl has been the dominant form of this expansion, sustainable development challenges will be more concerned. Sprawling, characterized by low density and automobile dependency, presents significant environmental issues regarding energy consumption and Co2 emissions. This paper examines the vertical expansion of suburbs integrated into mass transit nodes as a planning strategy for boosting density, intensification of land use, conversion of single family homes to multifamily dwellings or mixed use buildings and development of viable alternative transportation choices. It analyzes the spatial patterns of tall building transit-oriented development (TB-TOD) of suburban regions in Sydney (Australia), Toronto (Canada), and Washington D.C. (United States). The main objectives of this research seek to understand the effect of the new morphology of suburban tall, the physical dimensions of individual buildings and their arrangement at a larger scale with energy efficiency. This study aims to answer these questions: 1) why and how can the potential phenomenon of vertical expansion or high-rise development be integrated into suburb settings? 2) How can this phenomenon contribute to an overall denser development of suburbs? 3) Which spatial pattern or typologies/ sub-typologies of the TB-TOD model do have the greatest energy efficiency? It addresses these questions by focusing on 1) energy, heat energy demand (excluding cooling and lighting) related to design issues at two levels: macro, urban scale and micro, individual buildings—physical dimension, height, morphology, spatial pattern of tall buildings and their relationship with each other and transport infrastructure; 2) Examining TB-TOD to provide more evidence of how the model works regarding ridership. The findings of the research show that the TB-TOD model can be identified as the most appropriate spatial patterns of tall buildings in suburban settings. And among the TB-TOD typologies/ sub-typologies, compact tall building blocks can be the most energy efficient one. This model is associated with much lower energy demands in buildings at the neighborhood level as well as lower transport needs in an urban scale while detached suburban high rise or low rise suburban housing will have the lowest energy efficiency. The research methodology is based on quantitative study through applying the available literature and static data as well as mapping and visual documentations of urban regions such as Google Earth, Microsoft Bing Bird View and Streetview. It will examine each suburb within each city through the satellite imagery and explore the typologies/ sub-typologies which are morphologically distinct. The study quantifies heat energy efficiency of different spatial patterns through simulation via GIS software.Keywords: energy efficiency, spatial pattern, suburb, tall building transit-oriented development (TB-TOD)
Procedia PDF Downloads 252331 Mapping Potential Soil Salinization Using Rule Based Object Oriented Image Analysis
Authors: Zermina Q., Wasif Y., Naeem S., Urooj S., Sajid R. A.
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Land degradation, a leading environemtnal problem and a decrease in the quality of land has become a major global issue, caused by human activities. By land degradation, more than half of the world’s drylands are affected. The worldwide scope of main saline soils is approximately 955 M ha, whereas inferior salinization affected approximately 77 M ha. In irrigated areas, a total of 58% of these soils is found. As most of the vegetation types requires fertile soil for their growth and quality production, salinity causes serious problem to the production of these vegetation types and agriculture demands. This research aims to identify the salt affected areas in the selected part of Indus Delta, Sindh province, Pakistan. This particular mangroves dominating coastal belt is important to the local community for their crop growth. Object based image analysis approach has been adopted on Landsat TM imagery of year 2011 by incorporating different mathematical band ratios, thermal radiance and salinity index. Accuracy assessment of developed salinity landcover map was performed using Erdas Imagine Accuracy Assessment Utility. Rain factor was also considered before acquiring satellite imagery and conducting field survey, as wet soil can greatly affect the condition of saline soil of the area. Dry season considered best for the remote sensing based observation and monitoring of the saline soil. These areas were trained with the ground truth data w.r.t pH and electric condutivity of the soil samples. The results were obtained from the object based image analysis of Keti bunder and Kharo chan shows most of the region under low saline soil.Total salt affected soil was measured to be 46,581.7 ha in Keti Bunder, which represents 57.81 % of the total area of 80,566.49 ha. High Saline Area was about 7,944.68 ha (9.86%). Medium Saline Area was about 17,937.26 ha (22.26 %) and low Saline Area was about 20,699.77 ha (25.69%). Where as total salt affected soil was measured to be 52,821.87 ha in Kharo Chann, which represents 55.87 % of the total area of 94,543.54 ha. High Saline Area was about 5,486.55 ha (5.80 %). Medium Saline Area was about 13,354.72 ha (14.13 %) and low Saline Area was about 33980.61 ha (35.94 %). These results show that the area is low to medium saline in nature. Accuracy of the soil salinity map was found to be 83 % with the Kappa co-efficient of 0.77. From this research, it was evident that this area as a whole falls under the category of low to medium saline area and being close to coastal area, mangrove forest can flourish. As Mangroves are salt tolerant plant so this area is consider heaven for mangrove plantation. It would ultimately benefit both the local community and the environment. Increase in mangrove forest control the problem of soil salinity and prevent sea water to intrude more into coastal area. So deforestation of mangrove should be regularly monitored.Keywords: indus delta, object based image analysis, soil salinity, thematic mapper
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