Search results for: carbon capture and utilization (CCU)

Authors: Vaclav Novak, Katerina Krizova, Petr Sarec

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Modern agriculture has to face many issues from which soil degradation and lack of organic matter in the soil are only a few of them. Apart from Climate Change, human utilization of landscape is the cause of a majority part of these problems. Cattle production in Czechia has been reduced by more than half in recent 30 years. However, cattle manure is considered as staple organic fertilizer, and its role in attempts for sustainable agriculture is irreplaceable. This study aims to describe the impact of so-called activators of biological manure transformation (Z´fix, Olmix Group) mainly on physical soil properties but also on crop status. The experiment has been established in 2017; nevertheless, initial measurements of implement draft have been performed before the treated manure application. In 2018, the physical soil properties and crop status (sugar beet) has been determined and compared with the untreated manure and control variant. Significant results have been observed already in the first year, where the implement draft decreased by 9.2 % within the treated manure variant in comparison with the control variant.

Keywords: field experiment, implement draft, vegetation index, sugar beet

Procedia PDF Downloads 135

Authors: Apichai Sawisit, Sirima Suvarnakuta Jantama, Sunthorn Kanchanatawee, Lonnie O. Ingram, Kaemwich Jantama

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Escherichia coli KJ122 was engineered to produce succinate from glucose using the wild type GalP for glucose uptake instead of the native phosphotransferase system (ptsI mutation). This strain ferments 10% (w/v) xylose poorly. Mutants were selected by serial transfers in AM1 mineral salts medium with 10% (w/v) xylose. Evolved mutants exhibited a similar improvement, co-fermentation of an equal mixture of xylose and glucose. One of these, AS1600a, produced 84.26±1.37 g/L succinate, equivalent to that produced by the parent (KJ122) strain from 10% glucose (85.46±1.78 g/L). AS1600a was sequenced and found to contain a mutation in galactose permease (GalP, G236D). Expressing the galP* mutation gene in KJ122ΔgalP resembled the xylose utilization phenotype of the mutant AS1600a. The strain AS1600a and KJ122ΔgalP (pLOI5746; galP*) also co-fermented a mixture of glucose, xylose, arabinose, and galactose in sugarcane bagasse hydrolysate for succinate production.

Keywords: xylose, furfural, succinat, sugarcane bagasse, E. coli

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Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

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Authors: Murray Olowa

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This article examines the studies investigating the Mathematical Knowledge for Teaching (MKT) of secondary preservice teachers in Papua New Guinea based on probabilities. This research was conducted due to the continuous issues faced in the country in both primary and secondary education, like changes in curriculum, emphasis on mathematics and science education, and a decline in mathematics performance. Moreover, the mathematics curriculum doesn’t capture Pedagogical Content Knowledge (PCK) or Subject Matter Knowledge (SMK). The two main domains that have been identified are SMK and PCK, which have been further sub-divided into Common Content Knowledge (CCK), Specialised Content Knowledge (SCK) and Horizon Content Knowledge (HCK), and Knowledge of Content and Students (KCS), Knowledge of Content and Teaching (KCT) and Knowledge of Content and Curriculum (KCC), respectively. The data collected from 15-_year-_ ones and 15-_year-_fours conducted at St Peter Chanel Secondary Teachers College revealed that there is no significant difference in subject matter knowledge between year one and year four since the P-value of 0.22>0.05. However, it was revealed that year fours have higher pedagogical content knowledge than year one since P-value was 0.007<0.05. Finally, the research has proven that year fours have higher MKT than year one. This difference occurred due to final year preservice teachers’ hard work and engagement in mathematics curriculum and teaching practice.

Keywords: mathematical knowledge for teaching, subject matter knowledge, pedagogical content knowledge, Papua New Guinea, preservice teachers, probability

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Authors: Racholsan Raj Nirmal, B. S. V. Patnaik, R. Jayaganthan

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The deformation behaviour of additively manufactured AlSi10Mg alloy under low strains, high strain rates and elevated temperature conditions is essential to analyse and predict its response against dynamic loading such as impact and thermomechanical fatigue. The constitutive relation of Johnson-Cook is used to capture the strain rate sensitivity and thermal softening effect in AlSi10Mg alloy. Johnson-Cook failure model is widely used for exploring damage mechanics and predicting the fracture in many materials. In this present work, Johnson-Cook material and damage model parameters for additively manufactured AlSi10Mg alloy have been determined numerically from four types of uniaxial tensile test. Three different uniaxial tensile tests with dynamic strain rates (0.1, 1, 10, 50, and 100 s^-1) and elevated temperature tensile test with three different temperature conditions (450 K, 500 K and 550 K) were performed on 3D printed AlSi10Mg alloy in ABAQUS/Explicit. Hexahedral elements are used to discretize tensile specimens and fracture energy value of 43.6 kN/m was used for damage initiation. Levenberg Marquardt optimization method was used for the evaluation of Johnson-Cook model parameters. It was observed that additively manufactured AlSi10Mg alloy has shown relatively higher strain rate sensitivity and lower thermal stability as compared to the other Al alloys.

Keywords: ABAQUS, additive manufacturing, AlSi10Mg, Johnson-Cook model

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Authors: Khaldi Youcef

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This investigation seeks to inquire into the effectiveness of using authentic videos for grammar teaching purposes. In this investigation, an English animated situation, Hercules, was used as a type of authentic multimedia to teach a particular grammatical structure, namely conditional sentences. This study also aims at investigating the EFL learners’ attitudes toward grammar learning after being exposed to such an authentic video. To reach that purpose, 56 EFL learners were required ultimately to respond to a questionnaire with an aim to reveal their attitudes towards grammar as a language entity and as a subject for being learned. Then, as a second stage of the investigation, the EFL learners were divided into a control group and an experimental group with 28 learners in each. The first group was taught grammar -conditional sentences- using a deductive-inductive approach, while the second group was exposed to an authentic video to learn conditional sentences. There was a post-lesson stage that included a questionnaire to be answered by learners of each group. The aim of this stage is to capture any change in learners' attitudes shown in the pre-lesson questionnaire. The findings of the first stage revealed learners' negative attitudes towards grammar learning. And the third stage results showed the effectiveness of authentic videos in entirely turning learners' attitudes toward grammar learning to be significantly positive. Also, the utility of authentic videos in highly motivating EFL learners can be deduced. The findings of this survey asserted the need for incorporation and integration of authentic videos in EFL classrooms as they resulted in rising effectively learners’ awareness of grammar and looking at it from a communicative perspective.

Keywords: multimedia, authentic videos, negative attitudes, grammar learning, EFL learners

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Authors: R. Kanthavel, R. Yogesh Kumar, T. Narendrakumar, B. Santhosh, S. Surya Prakash

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This paper primarily focuses on developing an affordable personal assistant and the implementation of it in the field of Artificial Intelligence (AI) to create a virtual assistant/friend. The problem in existing home automation techniques is that it requires the usage of exact command words present in the database to execute the corresponding task. Our proposed work is ATOM a.k.a ‘Artificial intelligence Talking Omnipresent Machine’. Our inspiration came from an unlikely source- the movie ‘Iron Man’ in which a character called J.A.R.V.I.S has omnipresence, and device controlling capability. This device can control household devices in real time and send the live information to the user. This device does not require the user to utter the exact commands specified in the database as it can capture the keywords from the uttered commands, correlates the obtained keywords and perform the specified task. This ability to compare and correlate the keywords gives the user the liberty to give commands which are not necessarily the exact words provided in the database. The proposed work has a higher flexibility (due to its keyword extracting ability from the user input) comparing to the existing work Intelligent Home automation System (IHAS), is more accurate, and is much more affordable as it makes use of WI-FI module and raspberry pi 2 instead of ZigBee and a computer respectively.

Keywords: home automation, speech recognition, voice control, personal assistant, artificial intelligence

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Authors: Raymond Olayinka

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The last three decades have witnessed myriads of definitions of knowledge management proposed by researchers and industry practitioners. Despite the magnitude of research and available literature on knowledge management, there is yet to be a consensus on what constitutes a good definition. There exists an in-exhaustive list of definitions which can appear confusing, conflicting and overlapping. What is even more daunting is the lack of common terminology in describing knowledge management processes and the inconsistency in the sequence in which the processes take. Whilst newbies to knowledge management research would struggle to make sense of knowledge management definitions, industry practitioners would struggle with their applicability. Against this backdrop, this study aimed to re-evaluate knowledge management definitions and terminologies. The objectives were threefold: (1) to conduct a critical review of an existing body of work around knowledge management concepts and definitions (2) to analyse and synthesise findings (3) to present conclusions and recommendations. The methodology for this study centres around the review of the literature and secondary data sources. A total of 48 knowledge management processes were found and extracted from various definitions (e.g. ‘identify’, ‘capture’, ‘codify’, ‘store’…). A taxonomy of the processes was created based on the commonality of the entities. The 48 processes were classified under 8 headings which were further converged into 3 main headings namely ‘acquire’, ‘exploit’ and ‘evaluate’, of which all definitions therefore hinge. The study concludes that in the multitude of knowledge management definitions, there is a consistent pattern to which the processes are organised and should be utilised. The contribution of this study is in the synthesis of previous work by various authors and the presentation of a more holistic approach to knowledge management definitions and terminologies.

Keywords: knowledge management definitions, knowledge management terminologies, knowledge management processes, literature review

Procedia PDF Downloads 241

Authors: Asım Egitmen, Aysen Demir, Burcu Darendeli, Fatma Ulusal, Bilgehan Güzel

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Synthesizing supercritical carbon dioxide (scCO₂) soluble precursors would be helpful for many processes of material syntheses based on scCO₂. Ligand (amphi-(1Z, 2Z)-N-(2-fluoro-3-(trifluoromethyl) phenyl)-N'-hydroxy-2-(hydroxyimino) were synthesized from chloro glyoxime and flourus aniline and Pd(II) complex (precursor) prepared. For scCO₂ deposition method, organometallic precursor was dissolved in scCO₂ and impregnated onto the SBA-15 at 90 °C and 3000 psi. Then the organometallic precursor was reduced with H₂ in the CO₂ mixture (150 psi H₂ + 2850 psi CO₂). Pd deposited support material was characterized by ICP-OES, XRD, FE-SEM, TEM and EDX analyses. The Pd loading of the prepared catalyst, measured by ICP-OES showed a value of about 1.64% mol/g Pd of catalyst. Average particle size was found 5.3 nm. The catalytic activity of prepared catalyst was investigated over Suzuki-Miyaura C-C coupling reaction in different solvent with K₂CO₃ at 50 ^oC. The conversion ratio was determined by gas chromatography.

Keywords: nanoparticle, nanotube, oximes, precursor, supercritical CO2

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Authors: Andrea Dragu, Solen Kinayyigit, Valerie Colliere, Karin Karin Philippot, Camelia Bala, Vasile I. Parvulescu

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The production of transportation fuels from biomass has gained a growing attention due to diminishing fossil fuel reserves, rising petroleum prices and increasing concern about global warming. In recent years, renewable hydrocarbons that are completely fungible with fossil fuels have been suggested to be efficiently produced by catalytic deoxygenation of fatty acids and their derivatives viadecarboxylation / decarbonylation. Several triglycerides (tall oil fatty acids) and saturated/unsaturated fatty acids and their corresponding esters were used as feedstocks. Their impact together with the influence of the reaction conditions and the catalyst composition on the nature of the reaction pathways of the deoxygenation of vegetable oils and their derivatives were recently reviewed. Following this state of the art the aim of the present study was the investigation of Pd NPs deposited onto mesoporous carbon supports as active and stable catalysts for the deoxygenation of oleic acid. The catalysts were prepared by the deposition of Pd NPs synthesised following an organometallic route on mesoporous carbons with different characteristics. Experiments were carried out under both batch and flow conditions. They demonstrated that under batch conditions (200 atm; 573K), the extent of the reaction depended, firstly, on the Pd loading and then on the metal dispersion and the oxidation state of palladium, both influenced by the way the support has been treated before the NPs deposition and by the preparation/stabilization methodology of Pd NPs. No aromatic compounds were detected in the reaction products but octadecanol and octadecane were observed in large extents. Under flow conditions (4 atm; 573 K), the conversion of stearic acid was superior to that observed in batch conditions. The product mixture contained over 20% heptadecane. No octadecanol, octadecane, and aromatic compounds were detected. The maxima in performances are obtained after only 0.5 h. After that, the yields in heptadecane suffer from a severe decrease until 3h reaction time. However, at that time, stopping feeding the reactor with oleic acid and flushing the catalyst only with mesitylene recovered the activity and the selectivity of the catalysts. With the complete removal of H2, the analysis revealed the presence of heptadecene in high excess compared to heptadecane (almost 7 to 1), thus suggesting decarbonylation as the main route. ICP-OES measurements indicated no leaching of palladium and simple washing of catalysts with mesitylene allowed recycling without any change in conversion or product distribution. Noteworthy, mesitylene as solvent exhibited no effect in this reaction. In conclusion, this study demonstrates the feasibility of such catalysts for the green production of fuels from biomass.

Keywords: fuels from biomass, green catalyst, Pd nano-particles , recycble catalyst

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Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

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Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

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Authors: Hireni Mankodi

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The textile preforms for thermoplastic composite play a key role in providing the mechanical properties and gives the idea about preparing combination of yarn from Glass, Basalt, Carbon as reinforcement and PP, PET, Nylon as thermoplastic matrix at yarn stage for preforms to improve the quality and performance of laminates. The main objectives of this work are to develop the hybrid yarn using different yarn manufacturing process and prepare different performs using hybrid yarns. It has been observed that the glass/pp combination give homogeneous distribution in yarn. The proportion varied to optimize the glass/pp composition. The different preform has been prepared with combination of hybrid yarn, PP, glass combination. Further studies will investigate the effect of glass content in fabric, effect of weave, warps and filling density, number of layer plays significant role in deciding mechanical properties of thermoplastic laminates.

Keywords: thermoplastic, preform, laminates, hybrid yarn, glass

Procedia PDF Downloads 567

Authors: Patrizia Frontera, Anastasia Macario, Simona Crispi, Angela Malara, Pierantonio De Luca, Stefano Trocino

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The exploration of solar energy for the photoelectrochemical splitting of water into hydrogen and oxygen has been extensively researched as a means of generating sustainable H₂ fuel. However, despite these efforts, commercialization of this technology has not yet materialized. Presently, the primary impediments to commercialization include low solar-to-hydrogen efficiency (2-3% in PEC with an active area of up to 10-15 cm²), the utilization of costly and critical raw materials (e.g., BiVO₄), and energy losses during the separation of H₂ from O₂ and H₂O vapours in the output stream. The SERGIO partners have identified an advanced approach to fabricate photoelectrode materials, coupled with an appropriate scientific direction to achieve cost-effective solar-driven H₂ production in a tandem photoelectrochemical cell. This project is designed to reach Technology Readiness Level (TRL) 4 by validating the technology in the laboratory using a cell with an active area of up to 10 cm², boasting a solar-to-hydrogen efficiency of 5%, and ensuring acceptable hydrogen purity (99.99%). Our objectives include breakthroughs in cost efficiency, conversion efficiency, and H₂ purity.

Keywords: photoelectrolysis, green hydrogen, photoelectrochemical cell, semiconductors

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Authors: Hasan Aydogan

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The changes in the performance, emission and combustion characteristics of bioethanol-safflower biodiesel and diesel fuel blends used in a common rail diesel engine were investigated in this experimental study. E20B20D60 (20% bioethanol, 20% biodiesel, 60% diesel fuel by volume), E30B20D50, E50B20D30 and diesel fuel (D) were used as fuel. The tests were performed at full throttle valve opening and variable engine speeds. The results of the tests showed decreases in engine power, engine torque, carbon monoxide (CO), hydrocarbon (HC) and smoke density values with the use of bioethanol-biodiesel and diesel fuel blends, whereas, increases were observed in nitrogen oxide (NOx) and brake specific fuel consumption (BSFC) values. When combustion characteristics were examined, it was seen that the values were close to one another.

Keywords: bioethanol, biodiesel, safflower, combustion characteristics

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Authors: Zhanat Shomanova, Ruslan Safarov, Yuri Nosenko, Zheneta Tashmuchambetova, Alima Zharmagambetova

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An effective way of utilization of ferroalloy production wastes is preparing hydrocarbon refining catalysts from them. It is possible due to accordable transition metals containing in the wastes. In the work, we are presenting the results on elemental analysis of sludge samples from Aksu ferroalloy plant (Aksu, Kazakhstan), method of catalysts preparing, results of physical-chemical analysis of obtained catalysts (X-ray analysis, electron microscopy, the BET method etc.), results of using the catalysts in some hydrocarbons refining processes such as hydrocracking of rubber waste, cracking of gasoil, oxidation of cyclohexane. The main results of catalytic activity research are: a) In hydrocracking of rubber waste 64.9% of liquid products were fuel fractions; b) In cracking of gasoil conversion was 51% and selectivity by liquid products was 99%; c) In oxidation of cyclohexane the maximal product yield 87.9% and selectivity by cyclohexanol 93.0% were achieved.

Keywords: catalyst, cyclohexane oxidation, ferroalloy production waste, gasoil cracking

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Authors: Sangwon Han, Chengquan Jin

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Time-cost trade-off (TCTO) is one of the most significant part of construction project management. Despite the significance, current TCTO analysis, based on the Critical Path Method, does not consider resource constraint, and accordingly sometimes generates an impractical and/or infeasible schedule planning in terms of resource availability. Therefore, resource constraint needs to be considered when doing TCTO analysis. In this research, genetic algorithms (GA) based optimization model is created in order to find the optimal schedule. This model is utilized to compare four distinct scenarios (i.e., 1) initial CPM, 2) TCTO without considering resource constraint, 3) resource allocation after TCTO, and 4) TCTO with considering resource constraint) in terms of duration, cost, and resource utilization. The comparison results identify that ‘TCTO with considering resource constraint’ generates the optimal schedule with the respect of duration, cost, and resource. This verifies the need for consideration of resource constraint when doing TCTO analysis. It is expected that the proposed model will produce more feasible and optimal schedule.

Keywords: time-cost trade-off, genetic algorithms, critical path, resource availability

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Authors: Yang Zhou, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is a fundamental problem in urban environment, facilitating the smart management of various businesses, such as taxi dispatching, bike relocation, and stampede alert. Most earlier methods rely on identifying the intrinsic spatial-temporal correlation to forecast. However, the complex nature of this problem entails a more sophisticated solution that can simultaneously capture the mutual influence of both adjacent and far-flung areas, with the information of time-dimension also incorporated seamlessly. To tackle this difficulty, we propose a new multi-phase architecture, DSTDS (Dual Spatial-Temporal Data Scheme for traffic prediction), that aims to reveal the underlying relationship that determines future traffic trend. First, a graph-based neural network with an attention mechanism is devised to obtain the static features of the road network. Then, a multi-granularity recurrent neural network is built in conjunction with the knowledge from a grid-based model. Subsequently, the preceding output is fed into a spatial-temporal super-resolution module. With this 3-phase structure, we carry out extensive experiments on several real-world datasets to demonstrate the effectiveness of our approach, which surpasses several state-of-the-art methods.

Keywords: traffic prediction, spatial-temporal, recurrent neural network, dual data scheme

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Authors: Margarida Plana

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One of the most important energy challenge of the European policies is the transition to a Net Zero Energy Building (NZEB) model. A NZEB is a new concept of building that has the aim of reducing both the energy consumption and the carbon emissions to nearly zero of the course of a year. To achieve this nearly zero consumption, apart from being buildings with high efficiency levels, the energy consumed by the building has to be produced on-site. This paper is focused on presenting the results of the analysis developed on basis of real projects’ data in order to quantify the impact of end-users behavior. The analysis is focused on how the behavior of building’s occupants can vary the achievement of the energy savings targets and how they can be limited. The results obtained show that on this kind of project, with very high energy performance, is required to limit the end-users interaction with the system operation to be able to reach the targets fixed.

Keywords: end-users impacts, energy efficiency, energy savings, NZEB model

Procedia PDF Downloads 357

Authors: T. P. Oladele, C. A. Snyders, S. M. Bradshaw, G. Akdogan

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The effect of temperature, contact time and agitation during pre-treatment was investigated on the elution of gold from granular activated carbon at fixed caustic-cyanide concentration and elution conditions. It was shown that there are interactions between parameters during pre-treatment. At 80oC, recovery is independent of the contact time while the maximum recovery is obtained in the absence of agitation (0rpm). Increase in agitation speed from 0 rev/min to 1200 rev/min showed a decrease in recovery of approximately 20 percent at 80°C. Recovery with increased time from 15 minutes to 45 minutes is only pronounced at 25°C with approximately 4 percent increase at all agitation speeds. The results from elution recovery are aimed to give insight into the mechanisms of pre-treatment under the combinations of the chosen parameters.

Keywords: gold, temperature, contact time, agitation speed, recovery

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Authors: Lekgowa Collen Makola, Cecil Naphtaly Moro Ouma, Sharon Moeno, Langelihle Dlamini

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In recent years, advancement in the field of nanotechnology has evolved new strategies to address energy and environmental issues. Amongst the developing technologies, visible-light-driven photocatalysis is regarded as a sustainable approach for energy production and environmental detoxifications, where transition metal oxides (TMOs) and metal-free carbon-based semiconductors such as graphitic carbon nitride (CN) evidenced notable potential in this matter. Herein, g-C₃N₄@WO₃@Ti₃C₂Tx three-component multijunction photocatalyst was fabricated via facile ultrasonic-assisted self-assembly, followed by calcination to facilitate extensive integrations of the materials. A series of different Ti₃C₂ wt% loading in the g-C₃N4@WO₃@Ti₃C₂Tx were prepared and represented as 1-CWT, 3-CWT, 5-CWT, and 7-CWT corresponding to 1, 3, 5, and 7wt%, respectively. Systematic characterization using spectroscopic and microscopic techniques were employed to validate the successful preparation of the photocatalysts. Enhanced optoelectronic and photoelectrochemical properties were observed for the WO₃@Ti₃C2@g-C₃N4 heterostructure with respect to the individual materials. Photoluminescence spectra and Nyquist plots show restrained recombination rates and improved photocarrier conductivities, respectively, and this was credited to the synergistic coupling effect and the presence of highly conductive Ti₃C2 MXene. The strong interfacial contact surfaces upon the formation of the composite were confirmed using XPS. Multiple charge transfer mechanisms were proposed for the WO3@Ti3C₂@g-C3N4, which couples Z-scheme and Schottky-junction mediated with Ti3C2 MXene. Bode phase plots show improved charge carrier life-times upon the formation of the multijunctional photocatalyst. Moreover, transient photocurrent density of 7-CWT is 40 and seven (7) times higher compared to that of g-C₃N4 and WO3, correspondingly. Unlike in the traditional Z-Scheme, the formed ternary heterostructure possesses interfaces through the metallic 2D Ti₃C₂ MXene, which provided charge transfer channels for efficient photocarrier transfers with carrier concentrations (ND) of 17.49×1021 cm-3 and 4.86% photo-to-chemical conversion efficiency. The as-prepared ternary g-C₃N₄@WO₃@Ti₃C₂Tx exhibited excellent photoelectrochemical properties with reserved redox band potential potencies to facilitate efficient photo-oxidation and -reduction reactions. The fabricated multijunction photocatalyst exhibits potentials to be used in an extensive range of photocatalytic process vis., production of valuable hydrocarbons from CO₂, production of H₂, and degradation of a plethora of pollutants from wastewater.

Keywords: photocatalysis, Z-scheme, multijunction heterostructure, Ti₃C₂ MXene, g-C₃N₄

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Authors: Mostafa Kazemi, Zahra N. Farkhani

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This paper proposes an integrated Data Envelopment Analysis (DEA) and Variance Inflation Factor (VIF) model for measuring the technical efficiency of decision making units. The model is validated using a set of 69% sales representatives’ dairy products. The analysis is done in two stages, in the first stage, VIF technique is used to distinguish independent effective factors of resellers, and in the second stage we used DEA for measuring efficiency for both constant and variable return to scales status. Further DEA is used to examine the utilization of environmental factors on efficiency. Results of this paper indicated an average managerial efficiency of 83% in the whole sales representatives’ dairy products. In addition, technical and scale efficiency were counted 96% and 80% respectively. 38% of sales representative have the technical efficiency of 100% and 72% of the sales representative in terms of managerial efficiency are quite efficient.High levels of relative efficiency indicate a good condition for sales representative efficiency.

Keywords: data envelopment analysis (DEA), relative efficiency, sales representatives’ dairy products, variance inflation factor (VIF)

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Authors: Majid Bagherinia

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Lime and cement are frequently used as binders in the Deep Mixing Method (DMM) to improve soft clay soils. The most significant disadvantages of these materials are carbon dioxide emissions and the consumption of natural resources. In this study, three different biopolymers, guar gum, locust bean gum, and sodium alginate, were investigated for the improvement of soft clay using DMM. In the experimental study, the effects of the additive ratio and curing time on the Unconfined Compressive Strength (UCS) of stabilized specimens were investigated. According to the results, the UCS values of the specimens increased as the additive ratio and curing time increased. The most effective additive was sodium alginate, and the highest strength was obtained after 28 days.

Keywords: deep mixing method, soft clays, ground improvement, biopolymers, unconfined compressive strength

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Authors: Masoud Shahmanzari

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The aim of this paper is to present a Variable Neighborhood Search (VNS) with Tabu Search (TS) conditions for the Roaming Salesman Problem (RSP). The RSP is a special case of the well-known traveling salesman problem (TSP) where a set of cities with time-dependent rewards and a set of campaign days are given. Each city can be visited on any day and a subset of cities can be visited multiple times. The goal is to determine an optimal campaign schedule consist of daily open/closed tours that visit some cities and maximizes the total net benefit while respecting daily maximum tour duration constraints and the necessity to return campaign base frequently. This problem arises in several real-life applications and particularly in election logistics where depots are not fixed. We formulate the problem as a mixed integer linear programming (MILP), in which we capture as many real-world aspects of the RSP as possible. We also present a hybrid metaheuristic algorithm based on a VNS with TS conditions. The initial feasible solution is constructed via a new matheuristc approach based on the decomposition of the original problem. Next, this solution is improved in terms of the collected rewards using the proposed local search procedure. We consider a set of 81 cities in Turkey and a campaign of 30 days as our largest instance. Computational results on real-world instances show that the developed algorithm could find near-optimal solutions effectively.

Keywords: optimization, routing, election logistics, heuristics

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: Lindelwa Mngomezulu, Tonderai Muchenje

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Over the decades, E-mails provide easy, fast and timely communication enabling businesses and state owned agencies to communicate with their stakeholders and with their own employees in real-time. Moreover, since the launch of Microsoft office 365 and many other clouds based E-mail services, many businesses have been migrating from the on premises E-mail services to the cloud and more precisely since the beginning of the Covid-19 pandemic, there has been a significant increase of E-mails utilization, which then leads to the increase of cyber-attacks. In that regard, E-mail security has become very important in the E-mail transportation to ensure that the E-mail gets to the recipient without the data integrity being compromised. The classification of the features to enhance E-mail security for further from the enhanced cyber-attacks as we are aware that since the technology is advancing so at the cyber-attacks. Therefore, in order to maximize the data integrity we need to also maximize security of the E-mails such as enhanced E-mail authentication. The successful enhancement of E-mail security in the future may lessen the frequency of information thefts via E-mails, resulting in the data of South African State-owned agencies not being compromised.

Keywords: e-mail security, cyber-attacks, data integrity, authentication

Procedia PDF Downloads 115

Authors: Sahar Al-Qahtani, Rabeeh Ayaz Abbasi, Naif Radi Aljohani

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Many universities use social media platforms as new communication channels to disseminate information and promptly communicate with their audience. As Twitter is one of the widely used social media platforms, this research aims to explore the adaption and utilization of Twitter by universities. We propose a framework called 'Social Network Analysis for Universities on Twitter' (SNAUT) to analyze the usage of Twitter by universities and to measure their interaction with public. The study includes a sample of around 110,000 tweets from 36 Saudi universities, including both public and private universities. Using SNAUT, we can (1) investigate the purpose of using Twitter by universities, (2) determine the broad topics discussed by them, and (3) identify the groups closely associated with the universities. The results show that most of the Saudi universities (whether public or private) actively use Twitter. Results also reveal that public universities respond to public queries more frequently, but private universities stand out more in terms of information dissemination using retweets and diverse hashtags. Finally, we develop a ranking mechanism in SNAUT for ranking universities based on their social interaction with the public on Twitter.

Keywords: social media, twitter, social network analysis, universities, higher education, Saudi Arabia

Procedia PDF Downloads 117

Authors: Avantika Vats, Kushal Thakur

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This paper displays the point at issue, improvement, and utilization of a Monarch Butterfly Optimization (MBO) rather than a Genetic Algorithm (GA) in cognitive radio for the channel portion. This approach offers a satisfactory approach to get the accessible range of both the users, i.e., primary users (PUs) and secondary users (SUs). The proposed enhancement procedure depends on a nature-inspired metaheuristic algorithm. In MBO, all the monarch butterfly individuals are located in two distinct lands, viz. Southern Canada and the northern USA (land 1), and Mexico (Land 2). The positions of the monarch butterflies are modernizing in two ways. At first, the offsprings are generated (position updating) by the migration operator and can be adjusted by the migration ratio. It is trailed by tuning the positions for different butterflies by the methods for the butterfly adjusting operator. To keep the population unaltered and minimize fitness evaluations, the aggregate of the recently produced butterflies in these two ways stays equivalent to the first population. The outcomes obviously display the capacity of the MBO technique towards finding the upgraded work values on issues regarding the genetic algorithm.

Keywords: cognitive radio, channel allocation, monarch butterfly optimization, evolutionary, computation

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Authors: Abdulrahman K. Alshegaifi, Chun-Hsi Huang

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Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.

Keywords: hit rate, locality of program, stack cache, stack data

Procedia PDF Downloads 289

Authors: Rajat Kapoor

Abstract:

Indian Real Estate sector is the second largest employer after agriculture and is slated to grow at 30 percent over the next decade. Indian cities have shown tumultuous growth since last two decades. With the growing need of infrastructure, it has become inevitable for real estate sector to adopt more organized and transparent system of investment. SPVs such as REITs ensure transparency facilitating accessibility to invest in real estate for those who find it difficult to purchase real estate as an investment option with a realistic income expectation from their investment. RIETs or real estate investment trusts is an instrument of pooling funds similar to that of mutual funds. In a simpler term REIT is an Investment Vehicle in the form a trust which holds & manages large commercial rent¬ earning properties on behalf of investors and distributes most of its profit as dividends. REIT enables individual investors to invest their money in commercial real estate assets in a diversified portfolio and on the other hand provides fiscal liquidity to developers as easy exit option and channel funds for new projects. However, the success REIT is very much dependent on the taxation structure making such models attractive and adaptive enough for both developers and investors to opt for such investment option. This paper is intended to capture an overview of REITs with context to Indian real estate scenario.

Keywords: Indian real estate, real estate infrastructure trusts, urban finance, infrastructure investment trusts

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Authors: Miran Sabah Ibrahim, Nahit Aktas

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The utilization of emulsifiers is highly important in the process of breaking emulsions. This examination employed five commercial demulsifiers in various temperatures for evaluating the separation efficiency. Furthermore, two different crude oils (Khurmala and Demir Dagh crude oil) were utilized for preparing emulsion. The outcomes revealed that the application commercial demulsifiers for Khurmala crude oil at 55°C and 100 ppm (KD-3100, KD-3200, FD-6144, FD-6210 and RI35Q) the separation efficiency were (78, 80.6, 78, 86 and 90 %) respectively. However, at 65 °C and 100 ppm (KD-3100, KD-3200, FD-6144, FD-6210 and RI35Q) separation efficiency were (87, 85, 91.3, 94 and 97 %) respectively. Nonetheless, utilizing Demir Dagh crude oil at 55 °C and 100 ppm (KD-3100, KD-3200, FD-6144, FD-6210 and RI35Q) resulted in the separation efficiency of (63.3, 66.6, 65, 73 and 76.6 %) respectively, and at 65 °C and 100 ppm (KD-3100, KD-3200, FD-6144, FD-6210 and RI35Q) were (77, 76.6, 80, 82 and 85 %) respectively. The combinations of FD-6144 and RI35Q at 55°C and ratio of (1:1) and (1:3) for Khurmala crude oil led to (96 and 90.6 %) efficiency respectively. However, the efficiency decreased to (98.6 and 93.3 %) respectively at 65 °C. The same combinations applied on Demir Dagh Crude oil and the results were (78 and 63.3 %) at 55 °C and (86.6 and 71 %) at 65 °C. Three different brine concentrations (NaCl) (0.5, 2 and 3.5 %) were prepared and utilized. It was found that the optimum NaCl concentration was at 3.5 % NaCl concentration for both khurmala and Demir dagh crude oil at 55 °C and 65 °C.

Keywords: demulsifier, emulsion, breaking emulsion, emulsifying agent (surfactant)

Procedia PDF Downloads 322