Search results for: master planning process

Authors: Gloria James, S. K. Nema, T. S. Anantha Singh, P. Vadivel Murugan

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The usage of tyre has increased enormously in day to day life. The used tyre and rubber products pose major threat to the environment. Conventional thermal techniques such as low temperature pyrolysis and incineration produce high molecular organic compounds (condensed and collected as aromatic oil) and carbon soot particles. Plasma gasification technique can dispose tyre waste and generate combustible gases and avoid the formation of high molecular aromatic compounds. These gases generated in plasma gasification process can be used to generate electricity or as fuel wherever required. Although many experiments have been done on plasma pyrolysis of tyres, very little work has been done on plasma gasification of tyres. In this work plasma gasification of waste tyres have been conducted in a fixed bed reactor having graphite electrodes and direct current (DC) arc plasma system. The output of this work has been compared with the previous work done on plasma pyrolysis of tyres by different authors. The aim of this work is to compare different process based on gas generation, efficiency of the process and explore the most effective option for energy recovery from waste tyres.

Keywords: plasma, gasification, syngas, tyre waste

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Authors: Marianna Maiaru, Gregory M. Odegard, Josh Kemppainen, Ivan Gallegos, Michael Olaya

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Ceramic matrix composites (CMCs) are typically used in applications that require long-term mechanical integrity at elevated temperatures. CMCs are usually fabricated using a polymer precursor that is initially polymerized in situ with fiber reinforcement, followed by a series of cycles of pyrolysis to transform the polymer matrix into a rigid glass or ceramic. The pyrolysis step typically generates volatile gasses, which creates porosity within the polymer matrix phase of the composite. Subsequent cycles of monomer infusion, polymerization, and pyrolysis are often used to reduce the porosity and thus increase the durability of the composite. Because of the significant expense of such iterative processing cycles, new generations of CMCs with improved durability and manufacturability are difficult and expensive to develop using standard Edisonian approaches. The goal of this research is to develop a computational process-modeling-based approach that can be used to design the next generation of CMC materials with optimized material and processing parameters for maximum strength and efficient manufacturing. The process modeling incorporates computational modeling tools, including molecular dynamics (MD), to simulate the material at multiple length scales. Results from MD simulation are used to inform the continuum-level models to link molecular-level characteristics (material structure, temperature) to bulk-level performance (strength, residual stresses). Processing parameters are optimized such that process-induced residual stresses are minimized and laminate strength is maximized. The multiscale process modeling method developed with this research can play a key role in the development of future CMCs for high-temperature and high-strength applications. By combining multiscale computational tools and process modeling, new manufacturing parameters can be established for optimal fabrication and performance of CMCs for a wide range of applications.

Keywords: digital engineering, finite elements, manufacturing, molecular dynamics

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Authors: Chitaranjan Sharma

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The present paper deals with the analysis of a fuel supply system in an automobile engine of a four wheeler which is having both the option of fuel i.e. PETROL and CNG. Since CNG is cheaper than petrol so the priority is given to consume CNG as compared to petrol. An automatic switch is used to start petrol supply at the time of failure of CNG supply. Using regenerative point technique with Markov renewal process, the reliability characteristics which are useful to system designers are obtained.

Keywords: reliability, redundancy, repair time, transition, probability, regenerative points, markov renewal, process

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Authors: Wiwat Onnakklum

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Clarification is the turbidity removal process of water treatment plant. This paper was to study the factors affecting on energy consumption in order to control energy saving strategy. The factors studied were raw water turbidity in the range of 26-40 NTU and production rate in the range of 3.76-5.20 m³/sec. Clarifiers were sludge blanket and sludge recirculation clarifier. Experimental results found that the raw water turbidity was not affected significantly by energy consumption, while the production rate was affected significantly by energy consumption. Sludge blanket clarifier provided lower energy consumption than sludge recirculation clarifier about 32-37%. Subsequently, the operating pattern in production rate can be arranged to decreased energy consumption. The results showed that it can be reduced about 5.09 % of energy saving of clarification process about 754,655 Baht per year.

Keywords: sludge blanket clarifier, sludge recirculation clarifier, water treatment plant, energy

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Authors: Radul Shishkov

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This research paper presents an in-depth exploration of the use of generative design in urban residential architecture, with a dual focus on aligning aesthetic values with legal and environmental constraints. The study aims to demonstrate how generative design methodologies can innovate residential building designs that are not only legally compliant and environmentally conscious but also aesthetically compelling. At the core of our research is a specially developed generative design framework tailored for urban residential settings. This framework employs computational algorithms to produce diverse design solutions, meticulously balancing aesthetic appeal with practical considerations. By integrating site-specific features, urban legal restrictions, and environmental factors, our approach generates designs that resonate with the unique character of urban landscapes while adhering to regulatory frameworks. The paper explores how modern digital tools, particularly computational design and algorithmic modelling, can optimize the early stages of residential building design. By creating a basic parametric model of a residential district, the paper investigates how automated design tools can explore multiple design variants based on predefined parameters (e.g., building cost, dimensions, orientation) and constraints. The paper aims to demonstrate how these tools can rapidly generate and refine architectural solutions that meet the required criteria for quality of life, cost efficiency, and functionality. The study utilizes computational design for database processing and algorithmic modelling within the fields of applied geodesy and architecture. It focuses on optimizing the forms of residential development by adjusting specific parameters and constraints. The results of multiple iterations are analyzed, refined, and selected based on their alignment with predefined quality and cost criteria. The findings of this research will contribute to a modern, complex approach to residential area design. The paper demonstrates the potential for integrating BIM models into the design process and their application in virtual 3D Geographic Information Systems (GIS) environments. The study also examines the transformation of BIM models into suitable 3D GIS file formats, such as CityGML, to facilitate the visualization and evaluation of urban planning solutions. In conclusion, our research demonstrates that a generative parametric approach based on real geodesic data and collaborative decision-making could be introduced in the early phases of the design process. This gives the designers powerful tools to explore diverse design possibilities, significantly improving the qualities of the investment during its entire lifecycle.

Keywords: algorithmic modeling, architectural design, residential buildings, urban development, generative design, parametric models

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Authors: Jia Zhang, Fengmei Yao, Yanjing Tan

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The accurate estimation of crop yield is of great importance for the food security. In this study, a process-based mechanism model was modified to estimate yield of C4 crop by modifying the carbon metabolic pathway in the photosynthesis sub-module of the RS-P-YEC (Remote-Sensing-Photosynthesis-Yield estimation for Crops) model. The yield was calculated by multiplying net primary productivity (NPP) and the harvest index (HI) derived from the ratio of grain to stalk yield. The modified RS-P-YEC model was used to simulate maize yield in the Northeast China Plain during the period 2002-2011. The statistical data of maize yield from study area was used to validate the simulated results at county-level. The results showed that the Pearson correlation coefficient (R) was 0.827 (P < 0.01) between the simulated yield and the statistical data, and the root mean square error (RMSE) was 712 kg/ha with a relative error (RE) of 9.3%. From 2002-2011, the yield of maize planting zone in the Northeast China Plain was increasing with smaller coefficient of variation (CV). The spatial pattern of simulated maize yield was consistent with the actual distribution in the Northeast China Plain, with an increasing trend from the northeast to the southwest. Hence the results demonstrated that the modified process-based model coupled with remote sensing data was suitable for yield prediction of maize in the Northeast China Plain at the spatial scale.

Keywords: process-based model, C4 crop, maize yield, remote sensing, Northeast China Plain

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Authors: Tugba Altin

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In an era marked by pronounced climate change consequences, communities are observed to confront traumatic events that yield both tangible and intangible repercussions. Such events not only cause discernible damage to the landscape but also deeply affect the intangible aspects, including emotional distress and disruptions to cultural landscapes. The Lytton Creek Fire of 2021 serves as a case in point. Beyond the visible destruction, the less overt but profoundly impactful disturbance to place attachment (PA) is scrutinized. PA, representing the emotional and cognitive bonds individuals establish with their environments, is crucial for understanding how such events impact cultural identity and connection to the land. The study underscores the significance of addressing both tangible and intangible traumas for holistic community recovery. As communities renegotiate their affiliations with altered environments, the cultural landscape emerges as instrumental in shaping place-based identities. This renewed understanding is pivotal for reshaping adaptation planning. The research advocates for adaptation strategies rooted in the lived experiences and testimonies of the affected populations. By incorporating both the tangible and intangible facets of trauma, planning efforts are suggested to be more culturally attuned and emotionally insightful, fostering true resonance with the affected communities. Through such a comprehensive lens, this study contributes enriching the climate change discourse, emphasizing the intertwined nature of tangible recovery and the imperative of emotional and cultural healing after environmental disasters. Following the pronounced aftermath of the Lytton Creek Fire in 2021, research aims to deeply understand its impact on place attachment (PA), encompassing the emotional and cognitive bonds individuals form with their environments. The interpretive phenomenological approach, enriched by a hermeneutic framework, is adopted, emphasizing the experiences of the Lytton community and co-researchers. Phenomenology informed the understanding of 'place' as the focal point of attachment, providing insights into its formation and evolution after traumatic events. Data collection departs from conventional methods. Instead of traditional interviews, walking audio sessions and photo elicitation methods are utilized. These allow co-researchers to immerse themselves in the environment, re-experience, and articulate memories and feelings in real-time. Walking audio facilitates reflections on spatial narratives post-trauma, while photo voices captured intangible emotions, enabling the visualization of place-based experiences. The analysis is collaborative, ensuring the co-researchers' experiences and interpretations are central. Emphasizing their agency in knowledge production, the process is rigorous, facilitated by the harmonious blend of interpretive phenomenology and hermeneutic insights. The findings underscore the need for adaptation and recovery efforts to address emotional traumas alongside tangible damages. By exploring PA post-disaster, the research not only fills a significant gap but advocates for an inclusive approach to community recovery. Furthermore, the participatory methodologies employed challenge traditional research paradigms, heralding potential shifts in qualitative research norms.

Keywords: wildfire recovery, place attachment, trauma recovery, cultural landscape, visual methodologies

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Authors: Fumihiro Ima, Shinichi Watanabe, Shingo Maeda, Haruna Imai, Hiroki Niimi

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It is important to know growth rate of brain tumors before surgery because it influences treatment planning including not only surgical resection strategy but also adjuvant therapy after surgery. Amide proton transfer (APT) imaging is an emerging molecular magnetic resonance imaging (MRI) technique based on chemical exchange saturation transfer without administration of contrast medium. The underlying assumption in APT imaging of tumors is that there is a close relationship between the proliferative activity of the tumor and mobile protein synthesis. We aimed to evaluate the diagnostic performance of APT imaging of pre-and post-treatment brain tumors. Ten patients with brain tumor underwent conventional and APT-weighted sequences on a 3.0 Tesla MRI before clinical intervention. The maximum and the minimum APT-weighted signals (APTWmax and APTWmin) in each solid tumor region were obtained and compared before and after clinical intervention. All surgical specimens were examined for histopathological diagnosis. Eight of ten patients underwent adjuvant therapy after surgery. Histopathological diagnosis was glioma in 7 patients (WHO grade 2 in 2 patients, WHO grade 3 in 3 patients and WHO grade 4 in 2 patients), meningioma WHO grade1 in 2 patients and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW-signals than that in low-grade gliomas. APTWmax in one huge parasagittal meningioma infiltrating into the skull bone was higher than that in glioma WHO grade 4. On the other hand, APTWmax in another convexity meningioma was the same as that in glioma WHO grade 3. Diagnosis of primary lymphoma of the brain was possible with APT imaging before pathological confirmation. APTW-signals in residual tumors decreased dramatically within one year after adjuvant therapy in all patients. APT imaging demonstrated excellent diagnostic performance for the planning of surgery and adjuvant therapy of brain tumors.

Keywords: amides, magnetic resonance imaging, brain tumors, cell proliferation

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Authors: Xuan Li

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The English language occupies a crucial position in the Chinese educational system and is officially introduced in the school curriculum from the third year of primary school onward. However, it is worth noting that along with the movement to remove primary-oriented education from preschools, the teaching of English is banned in preschools. Considering the worldwide trend of learning English at a young age, whether this ban can be implemented successfully is doubtful. With an initial focus on the interaction of language-in-education planning and policy (LEPP) at the macro level and actual practice at the micro level, this research selected three private preschools and two public preschools to explore what is taking place in terms of English education. All data collected is qualitative and is gained from documentary analysis, school observation, interviews, and focus groups. The findings show that: (1) although the English ban in preschool education aims to regulate all types of preschools and all adult Chinese participants are aware of this ban, there are very different scenarios according to type of preschool, such that no English classes are found in public schools while private preschools commonly provide some kind of English education; (2) even public schools do not have an English-free environment and parents’ demand for English education is high; (3) there is an obvious top-down hierarchy in both public and private schools, in which administrators make the decisions while others have little power to influence the school curriculum; (4) there is a clear gap in the perception of English teaching between children and adults, in which adults prefer foreign English teachers and think English teaching is just playing, while children do not have a clear preference regarding teachers and do not think English class is just for fun; (5) without macro support, there are many challenges involved in preschool English education, including the shortage of qualified teachers and teaching resources, ineffective personnel management and few opportunities for speaking English in daily life. Hopefully, this research will not only highlight the interaction of LEPP at different levels and the importance of individual agency but also raise the awareness of how to provide qualified and equal education for all children.

Keywords: individual agency, language-in-education planning and policy, micro context, preschool English education

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Authors: Abdulmutallib U. Baraya, Aishatu M. Chadi, Zainab A. Aliyu, Agatha Samson

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Learning Resources is the field of study that investigates the process of analyzing, designing, developing, implementing, and evaluating learning materials, learners, and the learning process in order to improve teaching and learning in university-level education essential for empowering students and various sectors of Nigeria’s economy to succeed in a fast-changing global economy. Innovation in the information age of the 21st century is the use of educational technologies in the classroom for instructional delivery, it involves the use of appropriate educational technologies like smart boards, computers, projectors and other projected materials to facilitate learning and improve performance. The study examined learning resources as determinants for improving the teaching and learning process in Abubakar Tafawa Balewa University (ATBU), Bauchi, Bauchi state of Nigeria. Three objectives, three research questions and three null hypotheses guided the study. The study adopted a Survey research design. The population of the study was 880 lecturers. A sample of 260 was obtained using the research advisor table for determining sampling, and 250 from the sample was proportionately selected from the seven faculties. The instrument used for data collection was a structured questionnaire. The instrument was subjected to validation by two experts. The reliability of the instrument stood at 0.81, which is reliable. The researchers, assisted by six research assistants, distributed and collected the questionnaire with a 75% return rate. Data were analyzed using mean and standard deviation to answer the research questions, whereas simple linear regression was used to test the null hypotheses at a 0.05 level of significance. The findings revealed that physical facilities and digital technology tools significantly improved the teaching and learning process. Also, consumables, supplies and equipment do not significantly improve the teaching and learning process in the faculties. It was recommended that lecturers in the various faculties should strengthen and sustain the use of digital technology tools, and there is a need to strive and continue to properly maintain the available physical facilities. Also, the university management should, as a matter of priority, continue to adequately fund and upgrade equipment, consumables and supplies frequently to enhance the effectiveness of the teaching and learning process.

Keywords: education, facilities, learning-resources, technology-tools

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Authors: Anish Shah, Steve A. Wakelin, Derrick Moot, Aurélie Laugraud, Hayley J. Ridgway

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A mixed pasture system of ryegrass-clover is used in New Zealand, where clovers are generally inoculated with commercially available strains of rhizobia. The community of rhizobia living in the soil and the way in which they interact with the plant are affected by different biotic and abiotic factors. In general, bacterial richness and diversity in soil varies by soil pH. pH also affects cell physiology and acts as a master variable that controls the wider soil physiochemical conditions such as P availability, Al release and micronutrient availability. As such, pH can have both primary and secondary effects on soil biology and processes. The aim of this work was to investigate the effect of soil pH on the genetic diversity and metabolic profile of Rhizobium leguminosarum strains nodulating clover. Soils were collected from 12 farms across New Zealand which had a pH(water) range of between 4.9 and 7.5, with four acidic (pH 4.9 – 5.5), four ‘neutral’ (5.8 – 6.1) and four alkaline (6.5 – 7.5) soils. Bacteria were recovered from nodules of Trifolium repens (white clover) and T. subterraneum (subterranean clover) grown in the soils. The strains were cultured and screened against a range of pH-amended media to demonstrate whether they were adapted to pH levels similar to their native soils. The strains which showed high relative growth at a given pH (~20% of those isolated) were selected for metabolic and taxonomic profiling. The Omnilog (Biolog Inc., Hayward, CA) phenotype array was used to perform assays on carbon (C) utilisation for selected strains. DNA was extracted from the strains which had differing C utilisation profiles and PCR products for both forward and reverse primers were sequenced for the following genes: 16S rRNA, recA, nodC, nodD and nifH (symbiotic).

Keywords: bacterial diversity, clover, metabolic and taxonomic profiling, pH adaptation, rhizobia

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Authors: Jae-Ho Jang, Jung-Soo Kim, Byung-Jun Kim, Dae-Geun Nam, Uoo-Chang Jung, Yoon-Suk Choi

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Low alloy steels are widely used for pressure vessels, spent fuel storage, and steam generators required to withstand the internal pressure and prevent unexpected failure in nuclear power plants, which these may suffer embrittlement by high levels of radiation and heat for a long period. Therefore, it is important to improve mechanical properties of low alloy steels for the integrity of structure materials at an early stage of fabrication. Recently, it showed that a double austenitizing and tempering (DTA) process resulted in a significant improvement of strength and toughness by refinement of prior austenite grains. In this study, it was investigated that the mechanism of improving mechanical properties according to the change of microstructure by the second fully austenitizing temperature of the DAT process for low alloy steel required the structural integrity. Compared to conventional single austenitizing and tempering (SAT) process, the tensile elongation properties have improved about 5%, DBTTs have obtained result in reduction of about -65℃, and grain size has decreased by about 50% in the DAT process conditions. Grain refinement has crack propagation interference effect due to an increase of the grain boundaries and amount of energy absorption at low temperatures. The higher first austenitizing temperature in the DAT process, the more increase the spheroidized carbides and strengthening the effect of fine precipitates in the ferrite grain. The area ratio of the dimple in the transition area has increased by proportion to the effect of spheroidized carbides. This may the primary mechanisms that can improve low-temperature toughness and elongation while maintaining a similar hardness and strength.

Keywords: double austenitizing, Ductile Brittle transition temperature, grain refinement, heat treatment, low alloy steel, low-temperature toughness

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Authors: Seulki Lee, Seoung Bum Kim

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Statistical process control (SPC) is a practical and effective method for quality control. The most important and widely used technique in SPC is a control chart. The main goal of a control chart is to detect any assignable changes that affect the quality output. Most conventional control charts, such as Hotelling’s T2 charts, are commonly based on the assumption that the quality characteristics follow a multivariate normal distribution. However, in modern complicated manufacturing systems, appropriate control chart techniques that can efficiently handle the nonnormal processes are required. To overcome the shortcomings of conventional control charts for nonnormal processes, several methods have been proposed to combine statistical learning algorithms and multivariate control charts. Statistical learning-based control charts, such as support vector data description (SVDD)-based charts, k-nearest neighbors-based charts, have proven their improved performance in nonnormal situations compared to that of the T2 chart. Beside the nonnormal property, time-varying operations are also quite common in real manufacturing fields because of various factors such as product and set-point changes, seasonal variations, catalyst degradation, and sensor drifting. However, traditional control charts cannot accommodate future condition changes of the process because they are formulated based on the data information recorded in the early stage of the process. In the present paper, we propose a SVDD algorithm-based control chart, which is capable of adaptively monitoring time-varying and nonnormal processes. We reformulated the SVDD algorithm into a time-adaptive SVDD algorithm by adding a weighting factor that reflects time-varying situations. Moreover, we defined the updating region for the efficient model-updating structure of the control chart. The proposed control chart simultaneously allows efficient model updates and timely detection of out-of-control signals. The effectiveness and applicability of the proposed chart were demonstrated through experiments with the simulated data and the real data from the metal frame process in mobile device manufacturing.

Keywords: multivariate control chart, nonparametric method, support vector data description, time-varying process

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Authors: Achim Washington, Reece Clothier, Jose Silva

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System Safety Regulations (SSR) are a central component to the airworthiness certification of Unmanned Aircraft Systems (UAS). There is significant debate on the setting of appropriate SSR for UAS. Putting this debate aside, the challenge lies in how to apply the system safety process to UAS, which lacks the data and operational heritage of conventionally piloted aircraft. The limited knowledge and lack of operational data result in uncertainty in the system safety assessment of UAS. This uncertainty can lead to incorrect compliance findings and the potential certification and operation of UAS that do not meet minimum safety performance requirements. The existing system safety assessment and compliance processes, as used for conventional piloted aviation, do not adequately account for the uncertainty, limiting the suitability of its application to UAS. This paper discusses the challenges of undertaking system safety assessments for UAS and presents current and envisaged research towards addressing these challenges. It aims to highlight the main advantages associated with adopting a risk based framework to the System Safety Performance Requirement (SSPR) compliance process that is capable of taking the uncertainty associated with each of the outputs of the system safety assessment process into consideration. Based on this study, it is made clear that developing a framework tailored to UAS, would allow for a more rational, transparent and systematic approach to decision making. This would reduce the need for conservative assumptions and take the risk posed by each UAS into consideration while determining its state of compliance to the SSR.

Keywords: Part 1309 regulations, risk models, uncertainty, unmanned aircraft systems

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Authors: Satya Srii, V., Nethra, N.

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An image analyzer system is described to study the process of imbibition in Melia dubia seeds. The experimental system consisted of control C (seeds with intact pericarp) with two treatments, namely T1 (seeds with pericarp punctured) and T2 (naked seeds without pericarp). The measurement software in the image analyzer can determine the area and perimeter as descriptors of changes in seed size during swelling resulting from imbibition. Using the area and perimeter parameter, the imbibition process in C, T1, and T2 was described by a series of curves similar to the triphasic pattern of water uptake, with the extent and rate depending upon the treatment. Naked seeds without pericarp (T2) took lesser time to reach phase III during imbition followed by seeds with pericarp punctured (T1) while the seeds with intact pericarp (C) were the slowest to attain phase III. This shows the effect of pericarp in acting as a potential inhibitor to imbibition inducing a large delay in germination. The sensitivity and feasibility of the method to investigate individual seeds within a population imply that the image analyzer has high potential in seed biology studies.

Keywords: germination, imbibition, image analyzer, Melia dubia, pericarp

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Authors: Edgar Gasafi, Robert Pardemann, Linus Perander

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For the production of lithium carbonate or hydroxide out of lithium bearing ores, a thermal activation (calcination/decrepitation) is required for the phase transition in the mineral to enable an acid respectively soda leaching in the downstream hydrometallurgical section. In this paper, traditional processing in Lithium industry is reviewed, and opportunities to reduce energy consumption and improve product quality and recovery rate will be discussed. The conventional process approach is still based on rotary kiln calcination, a technology in use since the early days of lithium ore processing, albeit not significantly further developed since. A new technology, at least for the Lithium industry, is fluidized bed calcination. Decrepitation of lithium ore was investigated at Outotec’s Frankfurt Research Centre. Focusing on fluidized bed technology, a study of major process parameters (temperature and residence time) was performed at laboratory and larger bench scale aiming for optimal product quality for subsequent processing. The technical feasibility was confirmed for optimal process conditions on pilot scale (400 kg/h feed input) providing the basis for industrial process design. Based on experimental results, a comprehensive Aspen Plus flow sheet simulation was developed to quantify mass and energy flow for the rotary kiln and fluidized bed system. Results show a significant reduction in energy consumption and improved process performance in terms of temperature profile, product quality and plant footprint. The major conclusion is that a substantial reduction of energy consumption can be achieved in processing Lithium bearing ores by using fluidized bed based systems. At the same time and different from rotary kiln process, an accurate temperature and residence time control is ensured in fluidized-bed systems leading to a homogenous temperature profile in the reactor which prevents overheating and sintering of the solids and results in uniform product quality.

Keywords: calcination, decrepitation, fluidized bed, lithium, spodumene

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Authors: Oluwaseun K. Oyebode, Josiah A. Adeyemo

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Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.

Keywords: computational modelling, evolutionary algorithms, genetic programming, hydrological modelling

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Authors: Abdellatif Amouri, Sami Boudabbous

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The current study provides insights on the importance of entrepreneurial coaching as a source of developing entrepreneurial intentions among entrepreneurs and a determinant factor of business creation process and growth. Coaching, which implies exchange of adequate information and a mutual understanding between entrepreneurs and their partners, requires a better mutual knowledge of the representations and the perceptions of ideas which are widely present in their dealings and transactions. Therefore, to analyze entrepreneurs’ perceptions of business creation, we addressed a survey questionnaire to a group of Tunisian entrepreneurs and experts in business creation to indicate their level of approval concerning the prominence of coaching. The factor analysis indicates that more than 60% of the respondents believe that each statement reflects an aspect of coaching, with no bias to its position in the entrepreneurial process. Therefore, the image drawn from our respondents’ perceptions is that an entrepreneur is rather "constructed" and "shaped" by multiple apprenticeships both before and during the entrepreneurial act, through an accompaniment process and within interactions with trainers, consultants or professionals in starting a business. Similarly, the results indicate that the poor support structures and lack of accompaniment procedures stand as an obstacle impeding the development of entrepreneurial intention among business creators.

Keywords: Entrepreneurial Behavior, Entrepreneurial Coaching, Entrepreneurial Intention, Perceptions, Venture Creation

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Authors: Mostafa Fanaei, Shahram R. Sistani, Athare Nazri-Panjaki

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Introduction: Critical thinking skills are increasingly recognized as vital for academic success, particularly in higher education. This study examines the influence of critical thinking on learning achievement among undergraduate and master's students enrolled in foreign language programs. By investigating this correlation, educators can gain valuable insights into optimizing teaching methodologies and enhancing academic outcomes. Methods: This cross-sectional study involved 150 students from the Shahid Bahonar University of Kerman, recruited via random sampling. Participants completed the Critical Thinking Questionnaire (CThQ), assessing dimensions such as analysis, evaluation, creation, remembering, understanding, and application. Academic performance was measured using the students' GPA (0-20). Results: The participants' mean age was 21.46 ± 5.2 years, with 62.15% being female. The mean scores for critical thinking subscales were as follows: Analyzing (13.2 ± 3.5), Evaluating (12.8 ± 3.4), Creating (18.6 ± 4.8), Remembering (9.4 ± 2.1), Understanding (12.9 ± 3.3), and Applying (12.5 ± 3.2). The overall critical thinking score was 79.4 ± 18.1, and the average GPA was 15.7 ± 2.4. Significant positive correlations were found between GPA and several critical thinking subscales: Analyzing (r = 0.45, p = 0.013), Creating (r = 0.52, p < 0.001), Remembering (r = 0.29, p = 0.021), Understanding (r = 0.41, p = 0.002), and the overall CThQ score (r = 0.54, p = 0.043). Conclusion: The study demonstrates a significant positive relationship between critical thinking skills and learning achievement in foreign language programs. Enhancing critical thinking skills through educational interventions could potentially improve academic performance. Further research is recommended to explore the underlying mechanisms and long-term impacts of critical thinking on academic success.

Keywords: critical thinking, learning achievement, higher education, foreign language programs, student success

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Authors: Jin Zhi

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This study focuses on a green screen keying method developed especially for film visual effects. There are a series of ways of using existing tools for creating mattes from green or blue screen plates. However, it is still a time-consuming process, and the results vary especially when it comes to retaining tiny details, such as hair and fur. This paper introduces an alternative concept and method for retaining edge details of characters on a green screen plate, also, a number of connected mathematical equations are explored. At the end of this study, a simplified process of applying this method in real productions is also introduced.

Keywords: green screen, visual effects, compositing, matte

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Authors: Aprajeeta Jha, Punyadarshini P. Tripathy

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Drying is one of the most critical unit operations for prolonging the shelf-life of food grains in order to ensure global food security. Photovoltaic integrated solar dryers can be a sustainable solution for replacing energy intensive thermal dryers as it is capable of drying in off-sunshine hours and provide better control over drying conditions. But, performance and reliability of PV based solar dryers depend hugely on climatic conditions thereby, drastically affecting process parameters. Therefore, to ensure quality and prolonged shelf-life of paddy, optimization of process parameters for solar dryers is critical. Proper moisture distribution within the grains is most detrimental factor to enhance the shelf-life of paddy therefore; modeling of mass transport can help in providing a better insight of moisture migration. Hence, present work aims at optimizing the process parameters and to develop a 3D finite element model (FEM) for predicting moisture profile in paddy during solar drying. Optimization of process parameters (power level, air velocity and moisture content) was done using box Behnken model in Design expert software. Furthermore, COMSOL Multiphysics was employed to develop a 3D finite element model for predicting moisture profile. Optimized model for drying paddy was found to be 700W, 2.75 m/s and 13% wb with optimum temperature, milling yield and drying time of 42˚C, 62%, 86 min respectively, having desirability of 0.905. Furthermore, 3D finite element model (FEM) for predicting moisture migration in single kernel for every time step has been developed. The mean absolute error (MAE), mean relative error (MRE) and standard error (SE) were found to be 0.003, 0.0531 and 0.0007, respectively, indicating close agreement of model with experimental results. Above optimized conditions can be successfully used to dry paddy in PV integrated solar dryer in order to attain maximum uniformity, quality and yield of product to achieve global food and energy security

Keywords: finite element modeling, hybrid solar drying, mass transport, paddy, process optimization

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Authors: Marina Borgert Moraes, Wesley Francisco, Filipe Vargas, Gilmar Patrocínio Thim

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In recent years, carbon nanotubes (CNT) and graphene oxide (GO), especially the functionalized ones, have been added to epoxy resin in order to increase the mechanical, electrical and thermal properties of nanocomposites. However, it's still unknown how the presence of these nanoparticles influences the curing process and the final mechanical properties as well. In this work, kinetic and mechanical properties of the nanocomposites were analyzed, where the kinetic process was followed by DSC and the mechanical properties by DMA. Initially, CNT was annealed at high temperature (1800 °C) under vacuum atmosphere, followed by a chemical treatment using acids and ethylenediamine. GO was synthesized through chemical route, washed clean, dried and ground to #200. The presence of functional groups on CNT and GO surface was confirmed by XPS spectra and FT-IR. Then, epoxy resin, nanoparticles and acetone were mixed by sonication in order to obtain the composites. DSC analyses were performed on samples with different curing cycles (1h 80°C + 2h 120°C; 3h 80°C + 2h 120°C; 5h 80°C) and samples with different times at constant temperature (120°C). Results showed that the kinetic process and the mechanical strength are very dependent on the presence of graphene and functionalized-CNT in the nanocomposites.

Keywords: carbon nanotube, epoxy resin, Graphene oxide, nanocomposite

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Lopez J., Mehrvar M., Quinones E., Suarez A., Romero C.

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Membrane Distillation is an emerging technology that uses thermal and membrane steps for the desalination process to get drinking water. In this study, silver nanoparticles (AgNP) were deposited by dip-coating process over Polyvinylidene Fluoride, Fiberglass hydrophilic, and Polytetrafluoroethylene hydrophobic commercial membranes as substrate. Membranes were characterized and used in a Vacuum Membrane Distillation cell under Ultraviolet light with sea salt feed solution. The presence of AgNP increases the absorption of energy on the membrane, which improves the transmembrane flux.

Keywords: silver nanoparticles, membrane distillation, desalination technologies, heat deliver

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Authors: Vânia Graça, Paula Quadros-Flores, Altina Ramos

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The use of Digital Technologies in teaching and learning processes is currently a reality, namely in initial teacher training. This study aims at knowing the digital reality of students in initial teacher training in order to improve training in the educational use of ICT and to promote digital technology integration strategies in an educational context. It is part of the IFITIC Project "Innovate with ICT in Initial Teacher Training to Promote Methodological Renewal in Pre-school Education and in the 1st and 2nd Basic Education Cycle" which involves the School of Education, Polytechnic of Porto and Institute of Education, University of Minho. The Project aims at rethinking educational practice with ICT in the initial training of future teachers in order to promote methodological innovation in Pre-school Education and in the 1st and 2nd Cycles of Basic Education. A qualitative methodology was used, in which a questionnaire survey was applied to teachers in initial training. For data analysis, the techniques of content analysis with the support of NVivo software were used. The results point to the following aspects: a) future teachers recognize that they have more technical knowledge about ICT than pedagogical knowledge. This result makes sense if we consider the objective of Basic Education, so that the gaps can be filled in the Master's Course by students who wish to follow the teaching; b) the respondents are aware that the integration of digital resources contributes positively to students' learning and to the life of children and young people, which also promotes preparation in life; c) to be a teacher in the digital age there is a need for the development of digital literacy, lifelong learning and the adoption of new ways of teaching how to learn. Thus, this study aims to contribute to a reflection on the teaching profession in the digital age.

Keywords: digital technologies, initial teacher training, pedagogical use of ICT, skills

Procedia PDF Downloads 126

Authors: Virgino Stephano Moniaga

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Thermal comfort inside a building can affect students in their learning process. The learning process of students can be improved if the condition of the classrooms is comfortable. This study will be conducted in SMA Negeri 1 Amurang which is a senior high school building located in South Minahasa Regency. Based on preliminary survey, generally, students were not satisfied with the existing level of comfort, which subsequently affected the teaching and learning process in the classroom. The purpose of this study is to analyze the comfort level of classrooms occupants and recommend building design solutions that can improve the thermal comfort of classrooms. In this study, three classrooms will be selected for thermal comfort measurements. The thermal comfort measurements will be taken in naturally ventilated classrooms. The measured data comprise of personal data (clothing and students activity), air humidity, air temperature, mean radiant temperature and air flow velocity. Simultaneously, the students will be asked to fill out a questionnaire that asked about the level of comfort that was felt at the time. The results of field measurements and questionnaires will be analyzed based on the PMV and PPD indices. The results of the analysis will decide whether the classrooms are comfortable or not. This study can be continued to obtain a more optimal design solution to improve the thermal comfort of the classrooms. The expected results from this study can improve the quality of teaching and learning process between teachers and students which can further assist the government efforts to improve the quality of national education.

Keywords: classrooms, PMV, PPD, thermal comfort

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Authors: Arash Dara, Mahsa Mokhtari, Nafiseh Zamindar

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The aim of this study was to determine the effect of thermal resistance, temperature, voltage, and pH changes in an ohmic heating system on reducing the logarithmic number of Byssochlamys fulva species (PTCC 5062) in tomato juice water and to investigate the quantitative properties of tomato juice in the ohmic heating pasteurization system. The percentage of thermal degradation by ohmic heating was determined in tomato juice for the kinetics of Byssochlamys fulva in ohmic chamber at the temperatures of 88, 93, and 98°C, with two voltages of 30 and 40 volts and two pH levels of 3.5 and 4.5; this was done using Weibull frequency distribution model. Three different parameters (pH = 3.5, two voltages of 30 and 40, at three temperatures 88, 93, and 98) and (pH = 4.5, two voltages 30 and 40, at three temperatures 88, 93, and 98) in three replications were considered in the ohmic system. Heating time for the temperature of 88°C was 20 minutes once every 2 minutes, while for the temperature of 93°C, it was 10 minutes once every 1 minute. At the temperature of 98°C, the first time was 0.5 minutes, and for other times, sampling was done every 1 minute. In each condition, the qualitative characteristics, including acidity, Brix, and pH, were measured before and after the ohmic process in the tomato juice. This study demonstrates that the differences in pH and voltage due to different temperatures in the ohmic process can greatly affect the inactivation of Byssochlamys fulva fungus and the qualitative characteristics of the tomato juice. This is the first study using the Weibull frequency method to model the inactivation of Byssochlamys fulva in tomato juice. Variation in parameters such as temperature, voltage, and pH can prevent the presence of Byssochlamys fulva in the pasteurized juices.

Keywords: pasteurization, ohmic heating process, Byssochlamys fulva, tomato juice, heat resistance, voltage, pH

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Authors: Hen Friman

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Various categories of aqueous solutions are discharged within residential, institutional, commercial, and industrial structures. To safeguard public health and preserve the environment, it is imperative to subject wastewater to treatment processes that eliminate pathogens (such as bacteria and viruses), nutrients (such as nitrogen and phosphorus), and other compounds. Failure to address untreated sewage accumulation can result in an array of adverse consequences. Israel exemplifies a special case in wastewater management. Appropriate wastewater treatment significantly benefits sectors such as agriculture, tourism, horticulture, and industry. Nevertheless, untreated sewage in settlements lacking proper sewage collection or transportation networks remains an ongoing and substantial threat. Notably, the process of wastewater treatment entails substantial energy consumption. Consequently, this study explores the integration of solar energy as a renewable power source within the wastewater treatment framework. By incorporating renewable energy sources into the process, costs can be minimized, and decentralized facilities can be established even in areas lacking adequate infrastructure for traditional treatment methods.

Keywords: renewable energy, solar energy, innovative, wastewater treatment

Procedia PDF Downloads 114

Authors: Tarek Duzan

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Fractures are a fundamental property of most reservoirs. Despite their abundance, they remain difficult to detect and quantify. The most effective characterization of fractured reservoirs is accomplished by integrating geological, geophysical, and engineering data. Detection of fractures and defines their relative contribution is crucial in the early stages of exploration and later in the production of any field. Because fractures could completely change our thoughts, efforts, and planning to produce a specific field properly. From the structural point of view, all reservoirs are fractured to some point of extent. North Gialo field is thought to be a naturally fractured reservoir to some extent. Historically, natural fractured reservoirs are more complicated in terms of their exploration and production efforts, and most geologists tend to deny the presence of fractures as an effective variable. Our aim in this paper is to determine the degree of fracturing, and consequently, our evaluation and planning can be done properly and efficiently from day one. The challenging part in this field is that there is no enough data and straightforward well testing that can let us completely comfortable with the idea of fracturing; however, we cannot ignore the fractures completely. Logging images, available well testing, and limited core studies are our tools in this stage to evaluate, model, and predict possible fracture effects in this reservoir. The aims of this study are both fundamental and practical—to improve the prediction and diagnosis of natural-fracture attributes in N. Gialo hydrocarbon reservoirs and accurately simulate their influence on production. Moreover, the production of this field comes from 2-phase plan; a self depletion of oil and then gas injection period for pressure maintenance and increasing ultimate recovery factor. Therefore, well understanding of fracturing network is essential before proceeding with the targeted plan. New analytical methods will lead to more realistic characterization of fractured and faulted reservoir rocks. These methods will produce data that can enhance well test and seismic interpretations, and that can readily be used in reservoir simulators.

Keywords: natural fracture, sandstone reservoir, geological, geophysical, and engineering data

Procedia PDF Downloads 97

Authors: D. S. C. Soares, D. G. Costa, J. T. S., A. K. S. Abud, T. P. Nunes, A. M. Oliveira Júnior

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Mathematical models of drying are used for the purpose of understanding the drying process in order to determine important parameters for design and operation of the dryer. The jackfruit is a fruit with high consumption in the Northeast and perishability. It is necessary to apply techniques to improve their conservation for longer in order to diffuse it by regions with low consumption. This study aimed to analyse several mathematical models (Page, Lewis, and Midilli) to indicate one that best fits the conditions of convective drying process using performance indicators associated with each model: accuracy (Af) and noise factors (Bf), mean square error (RMSE) and standard error of prediction (% SEP). Jackfruit drying was carried out in convective type tray dryer at a temperature of 50°C for 9 hours. It is observed that the model Midili was more accurate with Af: 1.39, Bf: 1.33, RMSE: 0.01%, and SEP: 5.34. However, the use of the Model Midilli is not appropriate for purposes of control process due to need four tuning parameters. With the performance indicators used in this paper, the Page model showed similar results with only two parameters. It is concluded that the best correlation between the experimental and estimated data is given by the Page’s model.

Keywords: drying, models, jackfruit, biotechnology

Procedia PDF Downloads 383