Search results for: feed conversion

Authors: Awadhesh Kishore

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One of the most unique characteristics of rabbit feeding behaviour is caecotrophy, which involves the excretion and immediate consumption of specific faeces known as soft faeces. Caecotrophy in rabbits is the instinctual behaviour of eating soft faeces; reduced caecotrophy decreases rabbit growth and lipid synthesis in the liver. Caecotroph ingestion is highest when rabbits are fed a diet high in indigestible fibre. The colon produces two types of waste: hard and soft pellets. The hard pellets are expelled, but the soft pellets are re-ingested by the rabbit directly upon being expelled from the anus by twisting itself around and sucking in those pellets as they emerge from the anus. The type of alfalfa hay in the feed of the rabbits does not affect volatile fatty acid concentration, the pattern of fermentation, or pH in the faeces. The cecal content and the soft faeces contain significant amounts of retinoids and carotenoids, while in the tissues (blood, liver, and kidney), these pigments do not occur in substantial amounts. Preventing caecotrophy reduced growth and altered lipid metabolism, depressing the development of new approaches for rabbit feeding and production. Relative abundance is depressed for genes related to metabolic pathways such as vitamin C and sugar metabolism, vitamin B2 metabolism, and bile secretion. The key microorganisms that regulate the rapid growth performance of rabbits may provide useful references for future research and the development of microecological preparations.

Keywords: caecocolonic microorganisms, caecotrophy, fasting caecotrophy, rabbits, soft pellets

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Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a new robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics and using the weighted sum-squared prediction error as the residual. The recursive orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. The several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control

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Authors: Stephanie Fabris Russo, Daiane Costa Guimarães, Jonas Pedro Fabris, Maria Emilia Camargo, Suzana Leitão Russo, José Augusto Andrade Filho

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Among renewable energy sources, solar energy is the one that has stood out. Solar radiation can be used as a thermal energy source and can also be converted into electricity by means of effects on certain materials, such as thermoelectric and photovoltaic panels. These panels are often used to generate energy in homes, buildings, arenas, etc., and have low pollution emissions. Thus, a technological prospecting was performed to find patents related to the use of photovoltaic plates in urban residences. The patent search was based on ESPACENET, associating the keywords photovoltaic and home, where we found 136 patent documents in the period of 1994-2015 in the fields title and abstract. Note that the years 2009, 2010, 2011, 2012, 2013 and 2014 had the highest number of applicants, with respectively, 11, 13, 23, 29, 15 and 21. Regarding the country that deposited about this technology, it is clear that China leads with 67 patent deposits, followed by Japan with 38 patents applications. It is important to note that most depositors, 50% are companies, 44% are individual inventors and only 6% are universities. On the International Patent classification (IPC) codes, we noted that the most present classification in results was H02J3/38, which represents provisions in parallel to feed a single network by two or more generators, converters or transformers. Among all categories, there is the H session, which means Electricity, with 70% of the patents.

Keywords: photovoltaic, urban residences, technology forecasting, prospecting

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Authors: Abdelhak Djoudi, Hachemi Chekireb, El Madjid Berkouk

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The doubly fed induction generator (DFIG) received recently an important consideration in medium and high power wind energy conversion systems integration, due to its advantages compared to other generators types. The stator power sliding mode control (SPSMC) proves a great efficiency judge against other control laws and schemes. In the SPSMC laws elaborated by several authors, only the slide surface tracking conditions are elaborated using Lyapunov functions, and the boundedness of the DFIG states is never treated. Some works have validated theirs approaches by experiments results in the case of specified machines, but these verifications stay insufficient to generalize to other machines range. Adding to this argument, the DFIG states boundedness demonstration is widely suggested in goal to ensure that in the application of the SPSMC, the states evaluates within theirs tolerable bounds. Our objective in the present paper is to highlight the efficiency of the SPSMC by stability analysis. The boundedness of the DFIG states such as the stator current and rotor flux is discussed. Moreover, the states trajectories are finding using analytical proves taking into consideration the SPSMC gains.

Keywords: Doubly Fed Induction Generator (DFIG), Stator Powers Sliding Mode Control (SPSMC), lyapunov function, stability, states boundedness, trajectories mathematical proves

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Authors: Pankaj Chandna, Dinesh Kumar

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The present work analyses different parameters of end milling to minimize the surface roughness for AISI D2 steel. D2 Steel is generally used for stamping or forming dies, punches, forming rolls, knives, slitters, shear blades, tools, scrap choppers, tyre shredders etc. Surface roughness is one of the main indices that determines the quality of machined products and is influenced by various cutting parameters. In machining operations, achieving desired surface quality by optimization of machining parameters, is a challenging job. In case of mating components the surface roughness become more essential and is influenced by the cutting parameters, because, these quality structures are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects (i.e. on process environment). In this work, the effects of selected process parameters on surface roughness and subsequent setting of parameters with the levels have been accomplished by Taguchi’s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L9 orthogonal array. Experimental investigation of the end milling of AISI D2 steel with carbide tool by varying feed, speed and depth of cut and the surface roughness has been measured using surface roughness tester. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the contribution of the different process parameters on the process.

Keywords: D2 steel, orthogonal array, optimization, surface roughness, Taguchi methodology

Procedia PDF Downloads 543

Authors: Lifar M. S., Tereshchenko A. A., Bulgakov A. N., Guda S. A., Guda A. A., Soldatov A. V.

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Metal nanoparticles are widely used as heterogeneous catalysts to activate adsorbed molecules and reduce the energy barrier of the reaction. Reaction product yield depends on the interplay between elementary processes - adsorption, activation, reaction, and desorption. These processes, in turn, depend on the inlet feed concentrations, temperature, and pressure. At stationary conditions, the active surface sites may be poisoned by reaction byproducts or blocked by thermodynamically adsorbed gaseous reagents. Thus, the yield of reaction products can significantly drop. On the contrary, the dynamic control accounts for the changes in the surface properties and adjusts reaction parameters accordingly. Therefore dynamic control may be more efficient than stationary control. In this work, a reinforcement learning algorithm has been applied to control the simulation of CO oxidation on a catalyst. The policy gradient algorithm is learned to maximize the CO₂ production rate based on the CO and O₂ flows at a given time step. Nonstationary solutions were found for the regime with surface deactivation. The maximal product yield was achieved for periodic variations of the gas flows, ensuring a balance between available adsorption sites and the concentration of activated intermediates. This methodology opens a perspective for the optimization of catalytic reactions under nonstationary conditions.

Keywords: artificial intelligence, catalyst, co oxidation, reinforcement learning, dynamic control

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Authors: N. P. Eswara Reddy, S. Thahir Basha

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Here, we report the success stories of potential leaf, seed and root endophytes against soil borne as well as foliar plant pathogens which are nutritionally adequate and safe for consumption. Endophytes are the microorganisms that reside asymptomatically in the tissues of higher plants are a robust source of potential biocontrol agents and it is presumed that the survival ability of endophytes may be better when compared to phylloplane microflora. Of all the 68 putative leaf endophytes, the endophytes viz., EB9 (100%), and EB35 (100%) which were superior in controlling Colletotrichum gloeosporioides causing mango anthracnose were identified as Brevundimonas bullata (EB09) and Bacillus thuringiensis (EB35) and further delayed in ripening of mango fruits up to 21 days. As a part, the seed endophyte GSE-4 was identified as Archoromobacter spp. against Sclerotium rolfsii causing stem rot of groundnut and the root endophyte REB-8 against Rhizoctonia bataticola causing dry root rot of chickpea was identified as Bacillus subtilis. Both recorded least percent disease incidence (PDI) and increased plant growth promotion, respectively. Further, the novel Bacillus subtilis (SEB-2) against Macrophomina pahseolina causing charcoal rot of sunflower provides an ample scope for exploring the endophytes at large scale. The talc-based formulations of these endophytes developed can be commercialized after toxicological studies. At the bottom line these unexplored endophytes are the need of the hour against aggressive plant pathogens and to maintain the quality and abundance of food and feed and also to fetch marginal economy to the farmers will be discussed.

Keywords: endophytes, plant pathogens, commercialization, abundance of food

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Authors: Syed Atif Hassan, Luv Mehta, Syed Asif Hassan

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Hit song science is a field of investigation wherein machine learning techniques are applied to music tracks in order to extract such features from audio signals which can capture information that could explain the popularity of respective tracks. Record companies invest huge amounts of money into recruiting fresh talents and churning out new music each year. Gaining insight into the basis of why a song becomes popular will result in tremendous benefits for the music industry. This paper aims to extract basic musical and more advanced, acoustic features from songs while also taking into account external factors that play a role in making a particular song popular. We use a dataset derived from popular Spotify playlists divided by genre. We use ten genres (blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, rock), chosen on the basis of clear to ambiguous delineation in the typical sound of their genres. We feed these features into three different classifiers, namely, SVM with RBF kernel, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model at the end. Predicting song popularity is particularly important for the music industry as it would allow record companies to produce better content for the masses resulting in a more competitive market.

Keywords: classifier, machine learning, music tracks, popularity, prediction

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Authors: Ashwin Bala, K. Panthalaraja Kumaran, S. Prithviraj, R. Pradeep, J. Udhayakumar, S. Ajith

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In this paper, studies have been carried out for an in-house design of a waste heat recovery system for effectively utilizing the domestic air conditioner heat energy for producing hot water. Theoretical studies have been carried to optimizing the flow rate for getting maximum output with a minimum size of the heater. Critical diameter, wall thickness, and total length of the water pipeline have been estimated from the conventional heat transfer model. Several combinations of pipeline shapes viz., spiral, coil, zigzag wound through the radiator has been attempted and accordingly shape has been optimized using heat transfer analyses. The initial condition is declared based on the water flow rate and temperature. Through the parametric analytical studies we have conjectured that water flow rate, temperature difference between incoming water and radiator skin temperature, pipe material, radiator material, geometry of the water pipe viz., length, diameter, and wall thickness are having bearing on the lucrative design of a waste heat recovery system for air conditioners. Results generated through the numerical studies have been validated using an in-house waste heat recovery system for air conditioners.

Keywords: air conditioner design, energy conversion system, radiator design for energy recovery systems, waste heat recovery system

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Authors: Julie Ann L. Gadin, Andrearose C. Igano, Carl Joseph S. Ignacio, Christopher C. Bacungan

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Corn production has become an important and pervasive industry in the Visayas for many years. Its role as a substitute commodity to rice heightens demand for health-particular consumers. Unfortunately, the corn industry is confronted with several challenges, such as weak institutions. Considering these issues, the paper examined the factors that influence corn production in the three administrative regions in the Visayas, namely, Western Visayas, Central Visayas, and Eastern Visayas. The data used was retrieved from a variety of publicly available data sources such as the Philippine Statistics Authority, the Department of Agriculture, the Philippine Crop Insurance Corporation, and the International Disaster Database. Utilizing a dataset from 2002 to 2019, the indicators were tested using three multiple linear regression (MLR) models. Results showed that the land area harvested (p=0.02), and the value of corn production (p=0.00) are statistically significant variables that influence corn production in the Visayas. Given these findings, it is suggested that the policy of forest conversion and sustainable land management should be effective in enabling farmworkers to obtain land to grow corn crops, especially in rural regions. Furthermore, the Biofuels Act of 2006, the Livestock Industry Restructuring and Rationalization Act, and supported policy, Senate Bill No. 225, or an Act Establishing the Philippine Corn Research Institute and Appropriating Funds, should be enforced inclusively in order to improve the demand for the corn-allied industries which may lead to an increase in the value and volume of corn production in the Visayas.

Keywords: corn, industry, production, MLR, Visayas

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Authors: Andrey Norov

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In the recent years, Samoilov Research Institute for Mineral Fertilizers JSC “NIUIF”, the oldest (established in September 1919) industry-oriented institute in Russia, has developed a range of sustainable, environment-friendly, zero-waste technologies that ensure minimal consumption of materials and energy resources and fully consistent with the principles of Green Chemistry that include: - Ecofriendly energy and resource saving technology of sulfuric acid from sulfur according to DC-DA scheme (double conversion - double absorption); - Improved zero-waste technology of wet phosphoric acid (WPA) by dihydrate-hemihydrate process applicable to various types of phosphate raw materials; - Flexible, efficient, zero-waste, universal technology of NP / NPS / NPK / NPKS fertilizers with maximum heat recovery from chemical processes; - Novel, zero-waste, no-analogue technology of granular PK / PKS / NPKS fertilizers with controlled dissolution rate and nutrient supply into the soil, which allows to process a number of wastes and by-products; - Innovative resource-saving joint processing of wastes from the production of phosphogypsum and fluorosilicic acid (FSA) into ammonium sulfate with simultaneous neutralization of fluoride compounds with no lime used. - New fertilizer technology of increased environmental and agrochemical efficiency (currently under development). All listed green technologies are patented with Russian and Eurasian patents. The development of ecofriendly, safe, green technologies is ongoing in JSC “NIUIF”.

Keywords: NPKS fertilizers, FSA, sulfuric acid, WPA

Procedia PDF Downloads 93

Authors: Martial Pouzet, Marc Dubois, Karine Charlet, Alexis Béakou

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The availability, the ecologic and economic characteristics of wood are advantages which explain the very wide scope of applications of this material, in several domains such as paper industry, furniture, carpentry and building. However, wood is a hygroscopic material highly sensitive to ambient humidity and temperature. The swelling and the shrinking caused by water absorption and desorption cycles lead to crack and deformation in the wood volume, making it incompatible for such applications. In this study, dynamic fluorination using F2 gas was applied to wood samples (douglas and silver fir species) to decrease their hydrophilic character. The covalent grafting of fluorine atoms onto wood surface through a conversion of C-OH group into C-F was validated by Fourier-Transform infrared spectroscopy and 19F solid state Nuclear Magnetic Resonance. It revealed that the wood, which is initially hydrophilic, acquired a hydrophobic character comparable to that of the Teflon, thanks to fluorination. A good durability of this treatment was also determined by aging tests under ambient atmosphere and under UV irradiation. Moreover, this treatment allowed obtaining hydrophobic character without major structural (morphology, density and colour) or mechanical changes. The maintaining of these properties after fluorination, which requires neither toxic solvent nor heating, appears as a remarkable advantage over other more traditional physical and chemical wood treatments.

Keywords: cellulose, spectroscopy, surface treatment, water absorption

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Authors: Azizza Mala, Babo Fadlalla, Elnour Mohamed, Siran Wang, Junfeng Li, Tao Shao

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Sweet sorghum is considered one of the best plants for silage production and is now a more important feed crop in many countries worldwide. It is simple to ensile because of its high water-soluble carbohydrates (WSC) concentration and low buffer capacity. This study investigated the effect of adding Pediococcus acidilactici AZZ5 and Lactobacillus plantarum AZZ4 isolated from elephant grass on the fermentation quality of sweet sorghum silage. One commercial bacteria Lactobacillus Plantarum, Ecosyl MTD/1(C.B.)), and two strains were used as additives Pediococcus acidilactici (AZZ5), Lactobacillus plantarum subsp. Plantarum (AZZ4) at 6 log colony forming units (cfu)/g of fresh sweet sorghum grass in laboratory silos (1000g). After 15, 30, and 60 days, the silos for each treatment were opened. All of the isolated strains enhanced the silage quality of sweet sorghum silage compared to the control, as evidenced by significantly (P < 0.05) lower ammonia nitrogen (NH3-N) content and undesirable microbial counts, as well as greater lactic acid (L.A.) contents and lactic acid/acetic acid (LA/AA) ratios. In addition, AZZ4 performed better than all other inoculants during ensiling, as evidenced by a significant (P < 0.05) reduction in pH and ammonia-N contents and a significant increase in lactic acid contents.

Keywords: fermentation, lactobacillus plantarum, lactic acid bacteria, pediococcus acidilactic, sweet sorghum

Procedia PDF Downloads 89

Authors: Tzu-Wen Liu, Yi-Feng Lin, Yu-Shao Chen

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CO_2 is believed to be partly responsible for changes to the global climates. Carbon capture and storage (CCS) is one way to reduce carbon dioxide emissions in the past. Recently, how to convert the captured CO_2 into fine chemicals gets lots of attention owing to reducing carbon dioxide emissions and providing greener feedstock for the chemicals industry. A variety of products can be manufactured from carbon dioxide and the most attractive products are cyclic carbonates. Therefore, the kind of catalyst plays an important role in cycloaddition of carbon dioxide to epoxides. Magnesium oxide can be an efficiency heterogeneous catalyst for the cycloaddition of carbon dioxide to epoxides because magnesium oxide has both acid and base active sites and can provide the adsorption of carbon dioxide, promoting ring-opening reaction. Spinning disk reactor (SDR) is one of the device of high-gravity technique and has successfully used for synthesis of nanoparticles by precipitation methods because of the high mass transfer rate. Synthesis of nanoparticles in SDR has advantages of low energy consumption and easy to scale up. The aim of this research is to synthesize magnesium hydroxide nanoparticles in SDR as precursors for magnesium oxide. Experimental results showed that the calcination temperature of magnesium hydroxide to magnesium oxide, and the pressure and temperature of cycloaddition reaction had significantly effect on the conversion and selectivity of the reaction.

Keywords: magnesium oxide, catalyst, cycloaddition, spinning disk reactor, carbon dioxide

Procedia PDF Downloads 294

Authors: Osung Im, Neha Yadav, Eui Hoon Lee, Joong Hoon Kim

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Artificial Neural Network (ANN) approach is commonly used in lots of fields for forecasting. In water resources engineering, forecast of water level or inflow of reservoir is useful for various kind of purposes. Due to advantages of ANN, many papers were written for inflow prediction in river networks, but in this study, ANN is used in urban sewer networks. The growth of severe rain storm in Korea has increased flood damage severely, and the precipitation distribution is getting more erratic. Therefore, effective pump operation in pump station is an essential task for the reduction in urban area. If real time inflow of pump station reservoir can be predicted, it is possible to operate pump effectively for reducing the flood damage. This study used ANN model for pump station reservoir inflow prediction using upstream sewer depth data. For this study, rainfall events, sewer depth, and inflow into Banpo pump station reservoir between years of 2013-2014 were considered. Feed – Forward Back Propagation (FFBF), Cascade – Forward Back Propagation (CFBP), Elman Back Propagation (EBP) and Nonlinear Autoregressive Exogenous (NARX) were used as ANN model for prediction. A comparison of results with ANN model suggests that ANN is a powerful tool for inflow prediction using the sewer depth data.

Keywords: artificial neural network, forecasting, reservoir inflow, sewer depth

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Authors: Naum Simanovsky MD, Michael Zaidman MD, Vladimir Goldman MD.

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105 plain AP radiographs of normal adult pelvises (210 hips) were evaluated. Different measurements of normal and dysplastic hip joints in 45 patients were analyzed. Attempt was made to establish reproducible, easy applicable in practice approach for evaluation and follow up of patients with hip dysplasia. The youngest of our patients was 11 years and the oldest was 47 years. Only one of our patients needed conversion to total hip replacement (THR) during ten years of follow-up. It was emphasized that selected set of measurements was built for purpose to serve, especially those who’s scheduled or undergone PAO. This approach was based on concept of acetabulum-femoral head complex and importance of reliable reference points of measurements. Comparative analysis of measured parameters between normal and dysplastic hips was performed. Among 10 selected parameters, we use already well established such as lateral center edge angle and head extrusion index, but to serve specific group of patients with PAO, new parameters were considered such as complex lateralization and complex proximal migration. By our opinion proposed approach is easy applicable in busy clinical practice, satisfactorily delineate hip pathology and give to surgeon who’s going to perform PAO guidelines in condensed form. It is also useful tools for postoperative follow up after PAO.

Keywords: periacetabular osteotomy, plain radiograph’s measurements, adolescents, adult

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Authors: Ketan Mahawer, Abeer Mutto, S. K. Gupta

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The mining wastewater contains inorganic metal salts, which makes it saline and additionally contributes to contaminating the surface and underground freshwater reserves that exist nearby mineral processing industries. Therefore, treatment of wastewater and water recovery is obligatory by any available technology before disposing it into the environment. Currently, reverse osmosis (RO) is the commercially acceptable conventional membrane process for saline wastewater treatment, but consumes an enormous amount of energy and makes the process expensive. To solve this industrial problem with minimum energy consumption, we tested the feasibility of forward osmosis-nanofiltration (FO-NF) hybrid process for the mining wastewater treatment. The FO-NF process experimental results for 0.029M concentration of saline wastewater treated by 0.42 M sodium-sulfate based draw solution shows that specific energy consumption of the FO-NF process compared with standalone NF was slightly above (between 0.5-1 kWh/m3) from conventional process. However, average freshwater recovery was 30% more from standalone NF with same feed and operating conditions. Hence, FO-NF process in place of RO/NF offers a huge possibility for treating mining industry wastewater and concentrates the metals as the by-products without consuming an excessive/large amount of energy and in addition, mitigates the fouling in long periods of treatment, which also decreases the maintenance and replacement cost of the separation process.

Keywords: forward osmosis, nanofiltration, mining, draw solution, divalent solute

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Authors: Sandesh Achar

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Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

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Authors: I. S. R. Butswat, D. Zahraddeen

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This study identified and described some skill-based and necessity-driven entrepreneurship in animal agriculture (AA). AA is an integral segment of the world food industry, and provides a good and rapid source of income. The contribution of AA to the Sub-Saharan economy is quite significant, and there are still large opportunities that remain untapped in the sector. However, it is imperative to understand, simplify and package the various components of AA in order to pave way for rapid wealth creation, poverty eradication and women empowerment programmes in sub-Saharan Africa and other developing countries. The entrepreneurial areas of AA highlighted were animal breeding, livestock fattening, dairy production, poultry farming, meat production (beef, mutton, chevon, etc.), rabbit farming, wool/leather production, animal traction, animal feed industry, commercial pasture management, fish farming, sport animals, micro livestock production, private ownership of abattoirs, slaughter slabs, animal parks and zoos, among others. This study concludes that reproductive biotechnology such as oestrous synchronization, super-/multiple ovulation, artificial insemination and embryo transfer can be employed as a tool for improvement of genetic make-up of low-yielding animals in terms of milk, meat, egg, wool, leather production and other economic traits that will necessitate sustainable job and wealth creations.

Keywords: animal, agriculture, entreprenurship, wealth

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Authors: Neelu Raina, Parvez Singh Slathia, Deepali Bhagat, Preeti Sharma

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Pretreatment of lignocellulosic biomass for generating suitable substrates (starch/ sugars) for conversion to bioethanol is the most crucial step. In present study waste from furniture industry i.e sawdust from softwood Cedrus deodara (deodar) and hardwood Shorea robusta (sal) was used as lignocellulosic biomass. Thermochemical pretreatment was given by autoclaving at 121°C temperature and 15 psi pressure. Acids (H2SO4,HCl,HNO3,H3PO4), alkali (NaOH,NH4OH,KOH,Ca(OH)2) and organic acids (C6H8O7,C2H2O4,C4H4O4) were used at 0.1%, 0.5% and 1% concentration without giving any residence time. 1% HCl gave maximum sugar yield of 3.6587g/L in deodar and 6.1539 g/L in sal. For biological pretreatment a fungi isolated from decaying wood was used , sawdust from deodar tree species was used as a lignocellulosic substrate and before thermochemical pretreatment sawdust was treated with fungal culture at 37°C under submerged conditions with a residence time of one week followed by a thermochemical pretreatment methodology. Higher sugar yields were obtained with sal tree species followed by deodar tree species, i.e., 6.0334g/L in deodar and 8.3605g/L in sal was obtained by a combined biological and thermochemical pretreatment. Use of acids along with biological pretreatment is a favourable factor for breaking the lignin seal and thus increasing the sugar yield. Sugar estimation was done using Dinitrosalicyclic assay method. Result validation is being done by statistical analysis.

Keywords: lignocellulosic biomass, bioethanol, pretreatment, sawdust

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Authors: Zong-Sheng Chen

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With the advancement of technology, human activities have increased greenhouse gas emissions and fossil fuel energy production, leading to increasingly severe global warming. To mitigate global warming, energy conservation and carbon reduction have become global goals. Solar energy, a renewable energy source, not only helps achieve energy conservation and carbon reduction but also serves as an efficient energy generation method. Solar energy, derived from sunlight, is an endless and promising energy source capable of meeting high energy demands sustainably. In recent years, many countries around the world have been developing the solar energy industry, and Taiwan is no exception. Positioned in the subtropical region, Taiwan possesses geographical advantages conducive to solar energy utilization. Furthermore, Taiwan's well-developed semiconductor technology and sophisticated equipment make it highly suitable for the development of high-efficiency solar cells. This study focuses on investigating the anti-reflection properties of solar cells. Through metal-assisted chemical etching, pyramid structures are etched to allow sunlight to pass through, achieving secondary or higher-order reflections on the surface of these structures. This trapping of light within the substrate reduces reflection rates and increases conversion efficiency.

Keywords: solar cell, reflectance, pyramidal structure, potassium hydroxide

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Authors: Sajid Shah, Yoshimitsu Uemura, Katsuki Kusakabe

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Sol-gel derived hydrophobic silica membranes with pore sizes less than 1 nm are quite attractive for gas separation in a wide range of temperatures. A nano-structured hydrophobic membrane was prepared by sol-gel technique on a porous α–Al₂O₃ tubular support with yttria stabilized zirconia (YSZ) as an intermediate layer. Bistriethoxysilylethane (BTESE) derived sol was modified by adding phenyltriethoxysilylethane (PhTES) as an organic template. Six times dip coated modified silica membrane having a thickness of about 782 nm was characterized by field emission scanning electron microscopy. Thermogravimetric analysis, together along contact angle and Fourier transform infrared spectroscopy, showed that hydrophobic properties were improved by increasing the PhTES content. The contact angle of water droplet increased from 37° for pure to 111.5° for the modified membrane. The permeance of single gas H₂ was higher than H₂:CO₂ ratio of 75:25 binary feed mixtures. However, the permeance of H₂ for 60:40 H₂:CO₂ was found lower than single and binary mixture 75:25 H₂:CO₂. The binary selectivity values for 75:25 H₂:CO₂ were 24.75, 44, and 57, respectively. Selectivity had an inverse relation with PhTES content. Hydrophobicity properties were improved by increasing PhTES content in the silica matrix. The system exhibits proper three layers adhesion or integration, and smoothness. Membrane system suitable in steam environment and high-temperature separation. It was concluded that the hydrophobic silica membrane is highly promising for the separation of H₂/CO₂ mixture from various H₂-containing process streams.

Keywords: gas separation, hydrophobic properties, silica membrane, sol–gel method

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Srijitra Khanpakdee, Teera Butburee, Jung-Ho Yun, Miaoqiang Lyu, Supphasin Thaweesak, Piangjai Peerakiatkhajohn

Abstract:

The synthesis of titanium dioxide (TiO₂) nanorods (NRs) on fluorine-doped tin oxide (FTO) glass via hydrothermal methods was investigated to determine the optimal reaction time for enhanced photocatalytic and optical performance. Reaction times of 4, 6, and 8 hours were studied. Characterization through SEM, UV-vis, XRD, FTIR, Raman spectroscopy and photoelectrochemical (PEC) techniques revealed significant differences in the properties of the TiO₂ NRs based on the reaction duration. XRD and Raman spectroscopy analysis confirmed the formation of the rutile phase of TiO₂. As photoanodes in PEC cells, TiO₂ NRs synthesized for 4 hours exhibited the best photocatalytic activity, with the highest photocurrent density and superior charge transport properties, attributed to their densely packed vertical structure. Longer reaction times resulted in less optimal morphological and photoelectrochemical characteristics. The bandgap of the TiO₂ NRs remained consistent around 3.06 eV, with only slight variations observed. This study highlights the critical role of reaction time in hydrothermal synthesis, identifying 4 hours as the optimal duration for producing TiO₂ NRs with superior photoelectrochemical performance. These findings provide valuable insights for optimizing TiO₂-based materials for solar energy conversion and renewable energy applications.

Keywords: titanium dioxide, nanorods, hydrothermal, photocatalytic, photoelectrochemical

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Authors: Mohammed T. Hayajneh

Abstract:

Machining of Metal Matrix Composites (MMCs) is very significant process and has been a main problem that draws many researchers to investigate the characteristics of MMCs during different machining process. The poor machining properties of hard particles reinforced MMCs make drilling process a rather interesting task. Unlike drilling of conventional materials, many problems can be seriously encountered during drilling of MMCs, such as tool wear and cutting forces. Cutting tool wear is a very significant concern in industries. Cutting tool wear not only influences the quality of the drilled hole, but also affects the cutting tool life. Prediction the cutting tool life during drilling is essential for optimizing the cutting conditions. However, the relationship between tool life and cutting conditions, tool geometrical factors and workpiece material properties has not yet been established by any machining theory. In this research work, fuzzy subtractive clustering system has been used to model the cutting tool life in drilling of Al₂O₃ particle reinforced aluminum alloy composite to investigate of the effect of cutting conditions on cutting tool life. This investigation can help in controlling and optimizing of cutting conditions when the process parameters are adjusted. The built model for prediction the tool life is identified by using drill diameter, cutting speed, and cutting feed rate as input data. The validity of the model was confirmed by the examinations under various cutting conditions. Experimental results have shown the efficiency of the model to predict cutting tool life.

Keywords: composite, fuzzy, tool life, wear

Procedia PDF Downloads 295

Authors: N. Hatraf, l. Merabeti, M. Abbas

Abstract:

The interest in air conditioning using renewable energies is increasing. The Thermal energy produced from the solar energy can be transformed to useful cooling and heating through the thermo chemical or thermo physical processes by using thermally activated energy conversion system. Solid desiccant conditioning systems can represent a reliable alternative solution compared with other thermal cooling technologies. Their basic characteristics refer to the capability to regulate both temperature and humidity of the conditioned space in one side and to its potential in electrical energy saving in the other side. The ambient air contains so much water that very high dehumidification rates are required. For a continuous dehumidification of the process air the water adsorbed on the desiccant material has to be removed, which is done by allowing hot air to flow through the desiccant material (regeneration). Basically, solid desiccant cooling system transfers moisture from the inlet air to the silica gel by using two processes: absorption process and the regeneration process; The silica gel in the desiccant wheel which is the most important device in the system absorbs the moisture from the incoming air to the desiccant material in this case the silica gel, then it changes the heat with an rotary heat exchanger, after that the air passes through an humidifier to have the humidity required before entering to the local. The main aim of this paper is to study how the dehumidification rate, the generation temperature and many other factors influence the efficiency of a solid desiccant system by using TRNSYS software.

Keywords: desiccation, dehumidification, TRNSYS, efficiency

Procedia PDF Downloads 417

Authors: Mateen Abbas, Abdul Muqeet Khan, Sadia Bashir, Muhammad Awais Khalid, Aamir Ghafoor, Zara Hussain, Mashal Shahid

Abstract:

The irrational use of insecticides in everyday life has drawn attention worldwide towards its harmful effects. To mitigate the toxic effects of insecticides to humans, present study was planned on the degradation/detoxification of the neonicotinoid insecticides including imidacloprid and acetamiprid. Biocarbon of fruit peels (Banana & Watermelon) and biochar (activated or non-activated) of rice husk was utilized as adsorbents for degradation of selected pesticides. Both activated and non-activated biochar were prepared for treatment and then applied in different concentrations (0.5 to 2.0 ppm) and dosage (1.0 to 2.5g) to insecticides (Acetamiprid & Imidacloprid) as well as studied at different times (30-120 minutes). Reverse Phase-High Performance Liquid Chromatography (RP-HPLC) coupled with Photodiode array detector was used to quantify the insecticides. Results depicted that activated biochar of rice husk minimized the 73% concentrations of both insecticides however, watermelon activated biocarbon degraded 72% of imidacloprid and 56% of acetamiprid. Results proved the efficiency of the method employed and it was also inferred that high concentration of biocarbon resulted in larger percentage of degradation. The applied method is cheaper, easy and accessible that can be used to minimize the pesticide residues in animal feed. Degradation using biochar proved significant degradation, eco-friendly and economic method to reduce toxicity of insecticides.

Keywords: insecticides, acetamiprid, imidacloprid, biochar, HPLC

Procedia PDF Downloads 151

Authors: Mahnoosh Aliahmadi, Akbar Esmaeili

Abstract:

This study synthesized new modified imaging nanocapsules (NCs) of gallium@deferoxamine/folic acid/chitosan/polyaniline/polyvinyl alcohol (Ga@DFA/FA/CS/PANI/PVA) containing Morus nigra extract by selenium nanoparticles prepared from Lactobacillus acidophilus. Se nanoparticles were then deposited on (Ga@DFA/FA/CS/PANI/PVA) using the impregnation method. The modified contrast agents were mixed with M. nigra extract, and their antibacterial activities were investigated by applying them to L929 cell lines. The influence of variable factors including surfactant, solvent, aqueous phase, pH, buffer, minimum Inhibitory concentration (MIC), minimum bactericidal concentration (MBC), cytotoxicity on cancer cells, antibiotic, antibiogram, release and loading, stirring effect, the concentration of nanoparticle, olive oil, and thermotical methods was investigated. The structure and morphology of the synthesized contrast agents were characterized by zeta potential sizer analysis (ZPS), X-Ray diffraction (XRD), Fourier-transform infrared (FT-IR), and energy-dispersive X-ray (EDX), ultraviolet-visible (UV-Vis) spectra, and scanning electron microscope (SEM). The experimental section was conducted and monitored by response surface methods (RSM) and MTT conversion assay. Antibiogram testing of NCs on Pseudomonas aeruginosa bacteria was successful, and the MIC=2 factor was obtained with a less harmful effect.

Keywords: imaging contrast agent, nanoparticles, response surface method, Lactobacillus acidophilus, selenium

Procedia PDF Downloads 78

Authors: Youngmok Yun, Bosung Kim, Sungho Lee, Kyeongsu Jeon, Hyunwook Hwangbo, Byounggun Choi

Abstract:

A betavoltaic battery converts nuclear energy released as beta particles (β-) directly into electrical energy. Betavoltaic cells are analogous to photovoltaic cells. The beta particle’s kinetic energy enters a p-n junction and creates electron-hole pairs. Subsequently, the built-in potential of the p-n junction accelerates the electrons and ions to their respective collectors. The major challenges are electrical conversion efficiencies and exact evaluation. In this study, the performance of betavoltaic battery was evaluated. The betavoltaic cell was evaluated in the same condition as radiation from radioactive isotope using by FE-SEM(field emission scanning electron microscope). The average energy of the radiation emitted from the Ni-63 radioisotope is 17.42 keV. FE-SEM is capable of emitting an electron beam of 1-30keV. Therefore, it is possible to evaluate betavoltaic cell without radioactive isotopes. The betavoltaic battery consists of radioisotope that is physically connected on the surface of Si-based PN diode. The performance of betavoltaic battery can be estimated by the efficiency of PN diode unit cell. The current generated by scanning electron microscope with fixed accelerating voltage (17keV) was measured by using faraday cup. Electrical characterization of the p-n junction diode was performed by using Nano Probe Work Station and I-V measurement system. The output value of the betavoltaic cells developed by this research team was 0.162 μw/cm2 and the efficiency was 1.14%.

Keywords: betavoltaic, nuclear, battery, Ni-63, radio-isotope

Procedia PDF Downloads 256

Authors: M. Juffrie, Siti Helmyati, Toto Sudargo, B. J. Istiti Kandarina

Abstract:

Background: Iron fortification is one potential way to overcome anemia but it can cause gut microbiota imbalance. Probiotics addition can increase the growth of good gut bacteria while prebiotics can support the probiotics growth. Tempeh is rich in nutrients required for hemoglobin synthesis, such as protein, vitamin B12, vitamin C, zinc, iron and copper. Objective: To know the efficacy of fermented tempeh extract fortified with iron and synbiotic in maintain gut microbiota balance. Methods: Fermented synbiotic tempeh extract was made using Lactobacillus plantarum Dad13 and Fructo-oligosaccharides. A total of 32 anemic Wistar rats underwent the iron repletion phase then divided into 4 groups, given: 1) Fermented synbiotic tempeh extract with 50 ppm Fe/NaFeEDTA (Na), 2) Fermented synbiotic tempeh extract with 50 ppm Fe/FeSO4 (Fe), 3) Fermented synbiotic tempeh extract (St), and 4) not receive any interventions (Co). Rats were feed AIN-93 free Fe during intervention. Gut microbiota was measured with culture technique using selective media agar while hemoglobin concentration (Hb) was measured with photometric method before and after intervention. Results: There were significant increase in Hb after intervention in Na, Fe, and St, 6.85 to 11.80; 6.41 to 11.48 and 6.47 to 11.03 mg/dL, respectively (p <0.05). Co did not show increase in Hb (6.40 vs. 6.28 mg/dL). Lactobacilli increased in all groups while both of Bifidobacteria increased and E. coli decreased only in Na and St groups. Conclusion: Iron fortification of fermented synbiotic tempeh extract can increase hemoglobin concentrations in anemic animal, increase Lactobacilli and decrease E. coli. It can be an alternative solution to conduct iron fortification without deteriorate the gut microbiota.

Keywords: tempeh, synbiotic, iron, haemoglobin, gut microbiota

Procedia PDF Downloads 456