Search results for: map optimization tool

Authors: Adijat Olubukola Olateju

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Women empowerment is an essential developmental tool in every economy especially in less developed countries; as it helps to enhance women's socio-economic well-being. Some empirical evidence has shown that microcredit has been an effective tool in enhancing women empowerment, especially in developing countries. This paper therefore, investigates the impact of microcredit programme on women empowerment in Lagos State, Nigeria. The study used Cowries Microfinance Bank (CMB) as a case study bank, and a total of 359 women entrepreneurs were selected by simple random sampling technique from the list of Cowries Microfinance Bank. Selection bias which could arise from non-random selection of participants or non-random placement of programme, was adjusted for by dividing the data into participant women entrepreneurs and non-participant women entrepreneurs. The data were analyzed with a Propensity Score Matching (PSM) technique. The result of the Average Treatment Effect on the Treated (ATT) obtained from the PSM indicates that the credit programme has a significant effect on the empowerment of women in the study area. It is therefore, recommended that microfinance banks should be encouraged to give loan to women and for more impact of the loan to be felt by the beneficiaries the loan programme should be complemented with other programmes such as training, grant, and periodic monitoring of programme should be encouraged.

Keywords: empowerment, microcredit, socio-economic wellbeing, development

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Authors: Choy Sonny Yip Hong

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This abstract presents an exploration into the creation of a sustainable bio-polymer compound for additive manufacturing, specifically 3D printing, with a focus on eggshells and polylactide (PLA) polymer. The project initially conducted experiments using a variety of food by-products to create bio-polymers, and promising results were obtained when combining eggshells with PLA polymer. The research journey involved precise measurements, drying of PLA to remove moisture, and the utilization of a filament-making machine to produce 3D printable filaments. The project began with exploratory research and experiments, testing various combinations of food by-products to create bio-polymers. After careful evaluation, it was discovered that eggshells and PLA polymer produced promising results. The initial mixing of the two materials involved heating them just above the melting point. To make the compound 3D printable, the research focused on finding the optimal formulation and production process. The process started with precise measurements of the PLA and eggshell materials. The PLA was placed in a heating oven to remove any absorbed moisture. Handmade testing samples were created to guide the planning for 3D-printed versions. The scrap PLA was recycled and ground into a powdered state. The drying process involved gradual moisture evaporation, which required several hours. The PLA and eggshell materials were then placed into the hopper of a filament-making machine. The machine's four heating elements controlled the temperature of the melted compound mixture, allowing for optimal filament production with accurate and consistent thickness. The filament-making machine extruded the compound, producing filament that could be wound on a wheel. During the testing phase, trials were conducted with different percentages of eggshell in the PLA mixture, including a high percentage (20%). However, poor extrusion results were observed for high eggshell percentage mixtures. Samples were created, and continuous improvement and optimization were pursued to achieve filaments with good performance. To test the 3D printability of the DIY filament, a 3D printer was utilized, set to print the DIY filament smoothly and consistently. Samples were printed and mechanically tested using a universal testing machine to determine their mechanical properties. This testing process allowed for the evaluation of the filament's performance and suitability for additive manufacturing applications. In conclusion, the project explores the creation of a sustainable bio-polymer compound using eggshells and PLA polymer for 3D printing. The research journey involved precise measurements, drying of PLA, and the utilization of a filament-making machine to produce 3D printable filaments. Continuous improvement and optimization were pursued to achieve filaments with good performance. The project's findings contribute to the advancement of additive manufacturing, offering opportunities for design innovation, carbon footprint reduction, supply chain optimization, and collaborative potential. The utilization of eggshell PLA polymer in additive manufacturing has the potential to revolutionize the manufacturing industry, providing a sustainable alternative and enabling the production of intricate and customized products.

Keywords: additive manufacturing, 3D printing, eggshell PLA polymer, design innovation, carbon footprint reduction, supply chain optimization, collaborative potential

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Authors: A. Irudaya Veni Mary, M. Victor Louis Anthuvan, P. Christie, A. Indira

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In India, social enterprises are working to create social value in various fields including education; health; women and child development; environment protection and community development. Although social enterprises have brought about tremendous changes in the lives of beneficiaries, the importance of their works is not understood thoroughly. One of the ways to prove themselves is to measure the impact, which in recent times has received much attention. This paper focuses on the study of social value created by the social enterprises in the field of community development. It also aims to put forth a research tool for measuring the social value created by the social enterprises in the field of community development. A close-ended interview schedule was prepared to measure the social value creation and it was administered among 60 beneficiaries of two social enterprises who work in the field of community development. The study results show that the social enterprises have brought four types of impact in the life of their beneficiaries; economic impact, social impact, political impact and cultural impact. This study is limited to the social enterprises those who work towards community development. This empirical finding will enable the reader to understand various types of social value created by the social enterprises working in the field of community development. This study will also serve as guide for social enterprises in community development activities to measure their impact and thereby improve their operation towards the betterment of the society. This paper is derived from an empirical research carried out to describe the different types of social value created by the social enterprises in India.

Keywords: social enterprise, social entrepreneurs, social impact, social value, tool for social impact measurement

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Authors: Miguel Pereira, Lígia Pimentel, Manuela Pintado

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Animal blood is a major by-product of slaughterhouses and still represents a cost and environmental problem in some countries. To be eliminated, blood should be stabilised by cooking and afterwards the slaughterhouses must have to pay for its incineration. In order to reduce the elimination costs and valorise the high protein content the aim of this study was the optimization of hydrolysis conditions, in terms of enzyme ratio and time, in order to obtain hydrolysates with biological activity. Two enzymes were tested in this assay: pepsin and proteases from Cynara cardunculus (cardosins). The latter has the advantage to be largely used in the Portuguese Dairy Industry and has a low price. The screening assays were carried out in a range of time between 0 and 10 h and using a ratio of enzyme/reaction volume between 0 and 5%. The assays were performed at the optimal conditions of pH and temperature for each enzyme: 55 °C at pH 5.2 for cardosins and 37 °C at pH 2.0 for pepsin. After reaction, the hydrolysates were evaluated by FPLC (Fast Protein Liquid Chromatography) and tested for their antioxidant activity by ABTS method. FPLC chromatograms showed different profiles when comparing the enzymatic reactions with the control (no enzyme added). The chromatogram exhibited new peaks with lower MW that were not present in control samples, demonstrating the hydrolysis by both enzymes. Regarding to the antioxidant activity, the best results for both enzymes were obtained using a ratio enzyme/reactional volume of 5% during 5 h of hydrolysis. However, the extension of reaction did not affect significantly the antioxidant activity. This has an industrial relevant aspect in what concerns to the process cost. In conclusion, the enzymatic blood hydrolysis can be a better alternative to the current elimination process allowing to the industry the reuse of an ingredient with biological properties and economic value.

Keywords: antioxidant activity, blood, by-products, enzymatic hydrolysis

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Authors: Rahul R. Gurpude, Pallvita Yadav, Amrut Mulay

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In recent years, there has been a growing focus on advanced manufacturing processes, and one such emerging process is wire electric discharge machining (WEDM). WEDM is a precision machining process specifically designed for cutting electrically conductive materials with exceptional accuracy. It achieves material removal from the workpiece metal through spark erosion facilitated by electricity. Initially developed as a method for precision machining of hard materials, WEDM has witnessed significant advancements in recent times, with numerous studies and techniques based on electrical discharge phenomena being proposed. These research efforts and methods in the field of ED encompass a wide range of applications, including mirror-like finish machining, surface modification of mold dies, machining of insulating materials, and manufacturing of micro products. WEDM has particularly found extensive usage in the high-precision machining of complex workpieces that possess varying hardness and intricate shapes. During the cutting process, a wire with a diameter ranging from 0.18mm is employed. The evaluation of EDM performance typically revolves around two critical factors: material removal rate (MRR) and surface roughness (SR). To comprehensively assess the impact of machining parameters on the quality characteristics of EDM, an Analysis of Variance (ANOVA) was conducted. This statistical analysis aimed to determine the significance of various machining parameters and their relative contributions in controlling the response of the EDM process. By undertaking this analysis, optimal levels of machining parameters were identified to achieve desirable material removal rates and surface roughness.

Keywords: WEDM, MRR, optimization, surface roughness

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Authors: Pegah Ebrahimi, Farshad Oveissi, Iman Manavi-Tehrani, Sina Naficy, David F. Fletcher, Fariba Dehghani, David S. Winlaw

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Despite advances in modern surgery, congenital heart disease remains a medical challenge and a major cause of infant mortality. Cardiovascular prostheses are routinely used in surgical procedures to address congenital malformations, for example establishing a pathway from the right ventricle to the pulmonary arteries in pulmonary valvar atresia. Current off-the-shelf options including human and adult products have limited biocompatibility and durability, and their fixed size necessitates multiple subsequent operations to upsize the conduit to match with patients’ growth over their lifetime. Non-physiological blood flow is another major problem, reducing the longevity of these prostheses. These limitations call for better designs that take into account the hemodynamical and anatomical characteristics of different patients. We have integrated tissue engineering techniques with modern medical imaging and image processing tools along with mathematical modeling to optimize the design of cardiovascular grafts in a patient-specific manner. Computational Fluid Dynamics (CFD) analysis is done according to models constructed from each individual patient’s data. This allows for improved geometrical design and achieving better hemodynamic performance. Tissue engineering strives to provide a material that grows with the patient and mimic the durability and elasticity of the native tissue. Simulations also give insight on the performance of the tissues produced in our lab and reduce the need for costly and time-consuming methods of evaluation of the grafts. We are also developing a methodology for the fabrication of the optimized designs.

Keywords: computational fluid dynamics, cardiovascular grafts, design optimization, tissue engineering

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Authors: Amir Abbas Fatemi, Zahra Tabrizian, Kabir Sadeghi

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To find the location and severity of damage that occurs in a structure, characteristics changes in dynamic and static can be used. The non-destructive techniques are more common, economic, and reliable to detect the global or local damages in structures. This paper presents a non-destructive method in structural damage detection and assessment using GA and static data. Thus, a set of static forces is applied to some of degrees of freedom and the static responses (displacements) are measured at another set of DOFs. An analytical model of the truss structure is developed based on the available specification and the properties derived from static data. The damages in structure produce changes to its stiffness so this method used to determine damage based on change in the structural stiffness parameter. Changes in the static response which structural damage caused choose to produce some simultaneous equations. Genetic Algorithms are powerful tools for solving large optimization problems. Optimization is considered to minimize objective function involve difference between the static load vector of damaged and healthy structure. Several scenarios defined for damage detection (single scenario and multiple scenarios). The static damage identification methods have many advantages, but some difficulties still exist. So it is important to achieve the best damage identification and if the best result is obtained it means that the method is Reliable. This strategy is applied to a plane truss. This method is used for a plane truss. Numerical results demonstrate the ability of this method in detecting damage in given structures. Also figures show damage detections in multiple damage scenarios have really efficient answer. Even existence of noise in the measurements doesn’t reduce the accuracy of damage detections method in these structures.

Keywords: damage detection, finite element method, static data, non-destructive, genetic algorithm

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Authors: M. Amrita, R. R. Srikant, A. V. Sita Rama Raju

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Water miscible cutting fluids are conventionally used to lubricate and cool the machining zone. But issues related to health hazards, maintenance and disposal costs have limited their usage, leading to application of Minimum Quantity Lubrication (MQL). To increase the effectiveness of MQL, nanocutting fluids are proposed. In the present work, water miscible nanographite cutting fluids of varying concentration are applied at cutting zone by two systems A and B. System A utilizes high pressure air and supplies cutting fluid at a flow rate of 1ml/min. System B uses low pressure air and supplies cutting fluid at a flow rate of 5ml/min. Their performance in machining is evaluated by measuring cutting temperatures, tool wear, cutting forces and surface roughness and compared with dry machining and flood machining. Application of nano cutting fluid using both systems showed better performance than dry machining. Cutting temperatures and cutting forces obtained by both techniques are more than flood machining. But tool wear and surface roughness showed improvement compared to flood machining. Economic analysis has been carried out in all the cases to decide the applicability of the techniques.

Keywords: economic analysis, machining, minimum quantity lubrication, nanofluid

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Authors: Usarat Thawornchaisit, Kamalasiri Juthaisong, Kasama Parsongjeen, Phonsiri Phoengchan

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In this study, sludge samples that were collected from the wastewater treatment plant of a printed circuit board manufacturing industry in Thailand were subjected to acid extraction using sulfuric acid as the chemical extracting agent. The effects of sulfuric acid concentration (A), the ratio of a volume of acid to a quantity of sludge (B) and extraction time (C) on the efficiency of copper extraction were investigated with the aim of finding the optimal conditions for maximum removal of copper from the wastewater treatment sludge. Factorial experimental design was employed to model the copper extraction process. The results were analyzed statistically using analysis of variance to identify the process variables that were significantly affected the copper extraction efficiency. Results showed that all linear terms and an interaction term between volume of acid to quantity of sludge ratio and extraction time (BC), had statistically significant influence on the efficiency of copper extraction under tested conditions in which the most significant effect was ascribed to volume of acid to quantity of sludge ratio (B), followed by sulfuric acid concentration (A), extraction time (C) and interaction term of BC, respectively. The remaining two-way interaction terms, (AB, AC) and the three-way interaction term (ABC) is not statistically significant at the significance level of 0.05. The model equation was derived for the copper extraction process and the optimization of the process was performed using a multiple response method called desirability (D) function to optimize the extraction parameters by targeting maximum removal. The optimum extraction conditions of 99% of copper were found to be sulfuric acid concentration: 0.9 M, ratio of the volume of acid (mL) to the quantity of sludge (g) at 100:1 with an extraction time of 80 min. Experiments under the optimized conditions have been carried out to validate the accuracy of the Model.

Keywords: acid treatment, chemical extraction, sludge, waste management

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Authors: M. A. Moghaddas, M. Short, N. Wiley, A. Y. Yi, K. F. Graff

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The application of ultrasonic vibrations to machining processes has a long history, ranging from slurry-based systems able to drill brittle materials, to more recent developments involving low power ultrasonics for high precision machining, with many of these at the research and laboratory stages. The focus of this development is the application of high levels of ultrasonic power (1,000’s of watts) to standard, heavy duty machine tools – drilling being the immediate focus, with developments in milling in progress – with the objective of dramatically increasing system productivity through faster feed rates, this benefit arising from the thrust force reductions obtained by power ultrasonic vibrations. The presentation will describe development of an advanced drilling system based on a special, acoustically designed, rugged drill module capable of functioning under heavy duty production conditions, and making use of standard tool holder means, and able to obtain thrust force reductions while maintaining or improving surface finish and drilling accuracy. The characterization of the system performance will be described, and results obtained in drilling several materials (Aluminum, Stainless steel, Titanium) presented.

Keywords: dimensional accuracy, machine tool, productivity, surface roughness, thrust force, ultrasonic vibrations, ultrasonic-assisted drilling

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Authors: Ahmed Hossam ElMolla, Mohamed Hatem Saleh, Hamza Mostafa, Lara Mamdouh, Yassin Wael

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Artificial intelligence (AI) is reshaping industries, and its potential to revolutionize renewable energy and data center operations is immense. By harnessing AI's capabilities, we can optimize energy consumption, predict fluctuations in renewable energy generation, and improve the efficiency of data center infrastructure. This convergence of technologies promises a future where energy is managed more intelligently, sustainably, and cost-effectively. The integration of AI into renewable energy systems unlocks a wealth of opportunities. Machine learning algorithms can analyze vast amounts of data to forecast weather patterns, solar irradiance, and wind speeds, enabling more accurate energy production planning. AI-powered systems can optimize energy storage and grid management, ensuring a stable power supply even during intermittent renewable generation. Moreover, AI can identify maintenance needs for renewable energy infrastructure, preventing costly breakdowns and maximizing system lifespan. Data centers, which consume substantial amounts of energy, are prime candidates for AI-driven optimization. AI can analyze energy consumption patterns, identify inefficiencies, and recommend adjustments to cooling systems, server utilization, and power distribution. Predictive maintenance using AI can prevent equipment failures, reducing energy waste and downtime. Additionally, AI can optimize data placement and retrieval, minimizing energy consumption associated with data transfer. As AI transforms renewable energy and data center operations, modified Key Performance Indicators (KPIs) will emerge. Traditional metrics like energy efficiency and cost-per-megawatt-hour will continue to be relevant, but additional KPIs focused on AI's impact will be essential. These might include AI-driven cost savings, predictive accuracy of energy generation and consumption, and the reduction of carbon emissions attributed to AI-optimized operations. By tracking these KPIs, organizations can measure the success of their AI initiatives and identify areas for improvement. Ultimately, the synergy between AI, renewable energy, and data centers holds the potential to create a more sustainable and resilient future. By embracing these technologies, we can build smarter, greener, and more efficient systems that benefit both the environment and the economy.

Keywords: data center, artificial intelligence, renewable energy, energy efficiency, sustainability, optimization, predictive analytics, energy consumption, energy storage, grid management, data center optimization, key performance indicators, carbon emissions, resiliency

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Authors: Arash Parehkar, S. Jamshid Mousavi, Shoubo Bayazidi, Vahid Karami, Laleh Shahidi, Arash Azaranfar, Ali Moridi, M. Shabakhti, Tayebeh Ariyan, Mitra Tofigh, Kaveh Masoumi, Alireza Motahari

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Water resource systems modelling have constantly been a challenge through history for human being. As the innovative methodological development is evolving alongside computer sciences on one hand, researches are likely to confront more complex and larger water resources systems due to new challenges regarding increased water demands, climate change and human interventions, socio-economic concerns, and environment protection and sustainability. In this research, an automatic calibration scheme has been applied on the Gilan’s large-scale water resource model using mathematical programming. The water resource model’s calibration is developed in order to attune unknown water return flows from demand sites in the complex Sefidroud irrigation network and other related areas. The calibration procedure is validated by comparing several gauged river outflows from the system in the past with model results. The calibration results are pleasantly reasonable presenting a rational insight of the system. Subsequently, the unknown optimized parameters were used in a basin-scale linear optimization model with the ability to evaluate the system’s performance against a reduced inflow scenario in future. Results showed an acceptable match between predicted and observed outflows from the system at selected hydrometric stations. Moreover, an efficient operating policy was determined for Sefidroud dam leading to a minimum water shortage in the reduced inflow scenario.

Keywords: auto-calibration, Gilan, large-scale water resources, simulation

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Authors: Sky Chou, Joseph C. Chen

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This paper focuses on using Six Sigma methodologies to improve the surface roughness of a manufactured part produced by the CNC milling machine. It presents a case study where the surface roughness of milled aluminum is required to reduce or eliminate defects and to improve the process capability index C_p and C_pk for a CNC milling process. The six sigma methodology, DMAIC (design, measure, analyze, improve, and control) approach, was applied in this study to improve the process, reduce defects, and ultimately reduce costs. The Taguchi-based six sigma approach was applied to identify the optimized processing parameters that led to the targeted surface roughness specified by our customer. A L₉ orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of feed rate, depth of cut, spindle speed, and surface roughness. The noise factor is the difference between the old cutting tool and the new cutting tool. The confirmation run with the optimal parameters confirmed that the new parameter settings are correct. The new settings also improved the process capability index. The purpose of this study is that the Taguchi–based six sigma approach can be efficiently used to phase out defects and improve the process capability index of the CNC milling process.

Keywords: CNC machining, six sigma, surface roughness, Taguchi methodology

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Authors: Sina Moradi, Christopher W. K. Chow, John Van Leeuwen, David Cook, Mary Drikas, Patrick Hayde, Rose Amal

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Chloramine is commonly used as a disinfectant in drinking water distribution systems (DWDSs), particularly in Australia and the USA. Maintaining a chloramine residual throughout the DWDS is important in ensuring microbiologically safe water is supplied at the customer’s tap. In order to simulate how chloramine behaves when it moves through the distribution system, a water quality network model (WQNM) can be applied. In this work, the WQNM was based on mono-chloramine decomposition reactions, which enabled prediction of mono-chloramine residual at different locations through a DWDS in Australia, using the Bentley commercial hydraulic package (Water GEMS). The accuracy of WQNM predictions is influenced by a number of water quality parameters. Optimization of these parameters in order to obtain the closest results in comparison with actual measured data in a real DWDS would result in both cost reduction as well as reduction in consumption of valuable resources such as energy and materials. In this work, the optimum operating conditions of water quality parameters (i.e. temperature, pH, and initial mono-chloramine concentration) to maximize the accuracy of mono-chloramine residual predictions for two water supply scenarios in an entire network were determined using response surface methodology (RSM). To obtain feasible and economical water quality parameters for highest model predictability, Design Expert 8.0 software (Stat-Ease, Inc.) was applied to conduct the optimization of three independent water quality parameters. High and low levels of the water quality parameters were considered, inevitably, as explicit constraints, in order to avoid extrapolation. The independent variables were pH, temperature and initial mono-chloramine concentration. The lower and upper limits of each variable for two water supply scenarios were defined and the experimental levels for each variable were selected based on the actual conditions in studied DWDS. It was found that at pH of 7.75, temperature of 34.16 ºC, and initial mono-chloramine concentration of 3.89 (mg/L) during peak water supply patterns, root mean square error (RMSE) of WQNM for the whole network would be minimized to 0.189, and the optimum conditions for averaged water supply occurred at pH of 7.71, temperature of 18.12 ºC, and initial mono-chloramine concentration of 4.60 (mg/L). The proposed methodology to predict mono-chloramine residual can have a great potential for water treatment plant operators in accurately estimating the mono-chloramine residual through a water distribution network. Additional studies from other water distribution systems are warranted to confirm the applicability of the proposed methodology for other water samples.

Keywords: chloramine decay, modelling, response surface methodology, water quality parameters

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Authors: Paul Shize Li, Frank Alber

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A fundamental task of clinical genomics is to unravel the functions of genes and their associations with disorders. Although experimental biology has made efforts to discover and elucidate the molecular mechanisms of individual genes in the past decades, still about 40% of human genes have unknown functions, not to mention the diseases they may be related to. For those biologists who are interested in a particular gene with unknown functions, a powerful computational method tailored for inferring the functions and disease relevance of uncharacterized genes is strongly needed. Studies have shown that genes strongly linked to each other in multiple biological networks are more likely to have similar functions. This indicates that the densely connected subgraphs in multiple biological networks are useful in the functional and phenotypic annotation of uncharacterized genes. Therefore, in this work, we have developed an integrative network approach to identify the frequent local clusters, which are defined as those densely connected subgraphs that frequently occur in multiple biological networks and consist of the query gene that has few or no disease or function annotations. This is a local clustering algorithm that models multiple biological networks sharing the same gene set as a three-dimensional matrix, the so-called tensor, and employs the tensor-based optimization method to efficiently find the frequent local clusters. Specifically, massive public gene expression data sets that comprehensively cover dynamic, physiological, and environmental conditions are used to generate hundreds of gene co-expression networks. By integrating these gene co-expression networks, for a given uncharacterized gene that is of biologist’s interest, the proposed method can be applied to identify the frequent local clusters that consist of this uncharacterized gene. Finally, those frequent local clusters are used for function and disease annotation of this uncharacterized gene. This local tensor clustering algorithm outperformed the competing tensor-based algorithm in both module discovery and running time. We also demonstrated the use of the proposed method on real data of hundreds of gene co-expression data and showed that it can comprehensively characterize the query gene. Therefore, this study provides a new tool for annotating the uncharacterized genes and has great potential to assist clinical genomic diagnostics.

Keywords: local tensor clustering, query gene, gene co-expression network, gene annotation

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Authors: Louise Reyntjens

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Where criminal law used to be the traditional response to cope with the terrorist threat, European governments are increasingly relying on administrative paths. The reliance on immigration law fits into this trend. Terrorism is seen as a civilization menace emanating from abroad. In this context, the expulsion of dangerous aliens, immigration law’s core task, is put forward as a key security tool. Governments all over Europe are focusing on removing dangerous individuals from their territory rather than bringing them to justice. This research reflects on the consequences for the expelled individuals’ fundamental rights. For this, the author selected four European countries for a comparative study: Belgium, France, the United Kingdom and Sweden. All these countries face similar social and security issues, igniting the recourse to immigration law as a counterterrorism tool. Yet, they adopt a very different approach on this: the United Kingdom positions itself on the repressive side of the spectrum. Sweden on the other hand, also 'securitized' its immigration policy after the recent terrorist hit in Stockholm, but remains on the tolerant side of the spectrum. Belgium and France are situated in between. This paper addresses the situation in Belgium. In 2017, the Belgian parliament introduced several legislative changes by which it considerably expanded and facilitated the possibility to expel unwanted aliens. First, the expulsion measure was subjected to new and questionably definitions: a serious attack on the nation’s safety used to be required to expel certain categories of aliens. Presently, mere suspicions suffice to fulfil the new definition of a 'serious threat to national security'. A definition which fails to respond to the principle of legality; the law, nor the prepatory works clarify what is meant by 'a threat to national security'. This creates the risk of submitting this concept’s interpretation almost entirely to the discretion of the immigration authorities. Secondly, in name of intervening more quickly and efficiently, the automatic suspensive appeal for expulsions was abolished. The European Court of Human Rights nonetheless requires such an automatic suspensive appeal under Article 13 and 3 of the Convention. Whether this procedural reform will stand to endure, is thus questionable. This contribution also raises questions regarding expulsion’s efficacy as a key security tool. In a globalized and mobilized world, particularly in a European Union with no internal boundaries, questions can be raised about the usefulness of this measure. Even more so, by simply expelling a dangerous individual, States avoid their responsibility and shift the risk to another State. Criminal law might in these instances be more capable of providing a conclusive and long term response. This contribution explores the human rights consequences of expulsion as a security tool in Belgium. It also offers a critical view on its efficacy for protecting national security.

Keywords: Belgium, counter-terrorism and human rights, expulsion, immigration law

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper presents a Guidance and Control (G&C) strategy to address spacecraft maneuvering problem for future Rendezvous and Docking (RVD) missions. The proposed strategy allows safe and propellant efficient trajectories for space servicing missions including tasks such as approaching, inspecting and capturing. This work provides the validation test results of the G&C laws using a Hardware-In-the-Loop (HIL) setup with two robotic mockups representing the chaser and the target spacecraft. Through this paper, the challenges of the relative motion control in space are first summarized, and in particular, the constraints imposed by the mission, spacecraft and, onboard processing capabilities. Second, the proposed algorithm is introduced by presenting the formulation of constrained Model Predictive Control (MPC) to optimize the fuel consumption and explicitly handle the physical and geometric constraints in the system, e.g. thruster or Line-Of-Sight (LOS) constraints. Additionally, the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description and accordingly explained. The resulting convex optimization problem allows real-time implementation capability based on a detailed discussion on the computational time requirements and the obtained results with respect to the onboard computer and future trends of space processors capabilities. Finally, the performance of the algorithm is presented in the scope of a potential future mission and of the available equipment. The results also cover a comparison between the proposed algorithms with Linear–quadratic regulator (LQR) based control law to highlight the clear advantages of the MPC formulation.

Keywords: autonomous vehicles, embedded optimization, real-time experiment, rendezvous and docking, space robotics

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Authors: Hung-Chu Chen, Han Qi, Bauke de Vries

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Energy consumption in the urban environment has attracted numerous researches in recent decades. However, it is comparatively rare to find literary works which investigated 3D spatial analysis of urban energy demand modelling. In order to analyze the spatial correlation between urban morphology and energy demand comprehensively, this paper investigates their relation by using the spatial regression tool. In addition, the spatial regression tool which is applied in this paper is ordinary least squares regression (OLS) and geographically weighted regression (GWR) model. Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and building volume are explainers of urban morphology, which act as independent variables of Energy-land use (E-L) model. NDBI and NDVI are used as the index to describe five types of land use: urban area (U), open space (O), artificial green area (G), natural green area (V), and water body (W). Accordingly, annual electricity, gas demand and energy demand are dependent variables of the E-L model. Based on the analytical result of E-L model relation, it revealed that energy demand and urban morphology are closely connected and the possible causes and practical use are discussed. Besides, the spatial analysis methods of OLS and GWR are compared.

Keywords: energy demand model, geographically weighted regression, normalized difference built-up index, normalized difference vegetation index, spatial statistics

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Authors: Yuekun Chen, Yousef Sardahi, Salam Hajjar, Christopher Greer

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This paper presents a multi-objective optimal design of a cascade control system for an underactuated mechanical system. Cascade control structures usually include two control algorithms (inner and outer). To design such a control system properly, the following conflicting objectives should be considered at the same time: 1) the inner closed-loop control must be faster than the outer one, 2) the inner loop should fast reject any disturbance and prevent it from propagating to the outer loop, 3) the controlled system should be insensitive to measurement noise, and 4) the controlled system should be driven by optimal energy. Such a control problem can be formulated as a multi-objective optimization problem such that the optimal trade-offs among these design goals are found. To authors best knowledge, such a problem has not been studied in multi-objective settings so far. In this work, an underactuated mechanical system consisting of a rotary servo motor and a ball and beam is used for the computer simulations, the setup parameters of the inner and outer control systems are tuned by NSGA-II (Non-dominated Sorting Genetic Algorithm), and the dominancy concept is used to find the optimal design points. The solution of this problem is not a single optimal cascade control, but rather a set of optimal cascade controllers (called Pareto set) which represent the optimal trade-offs among the selected design criteria. The function evaluation of the Pareto set is called the Pareto front. The solution set is introduced to the decision-maker who can choose any point to implement. The simulation results in terms of Pareto front and time responses to external signals show the competing nature among the design objectives. The presented study may become the basis for multi-objective optimal design of multi-loop control systems.

Keywords: cascade control, multi-Loop control systems, multiobjective optimization, optimal control

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Authors: Vojtěch Gybas, Libor Klubal, Kateřina Kostolányová

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Nowadays, mobile touch technologies, such as tablets, are an integral part of teaching and learning in many special elementary schools. Many special education teachers tend to choose an iPad tablet with iOS. The reason is simple; the iPad has a function for pupils with special educational needs. If we decide to use tablets in teaching, in general, first we should try to stimulate the cognitive abilities of the pupil at the highest level, while holding the pupil’s attention on the task, when working with the device. This paper will describe how student attention can be increased by eliminating the working environment of selected applications, while using iPads with pupils in a special elementary school. Assisted function approach is highly effective at eliminating unwanted touching by a pupil when working on the desktop iPad, thus actively increasing the pupil´s attention while working on specific educational applications. During the various stages of the action, the research was conducted via data collection and interpretation. After a phase of gaining results and ideas for practice and actions, we carried out the check measurement, this time using the tool-assisted approach. In both cases, the pupils worked in the Math Board application and the resulting differences were evident.

Keywords: special elementary school, a mobile touch device, iPad, attention, Math Board

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Authors: Chaiwat Tantarangsee

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The purposes of this study are: 1) to study the frequent English writing errors of students registering the course: Reading and Writing English for Academic Purposes II, and 2) to find out the results of writing error correction by using coded indirect corrective feedback and writing error treatments. Samples include 28 2nd year English Major students, Faculty of Education, Suan Sunandha Rajabhat University. Tool for experimental study includes the lesson plan of the course; Reading and Writing English for Academic Purposes II, and tool for data collection includes 4 writing tests of short texts. The research findings disclose that frequent English writing errors found in this course comprise 7 types of grammatical errors, namely Fragment sentence, Subject-verb agreement, Wrong form of verb tense, Singular or plural noun endings, Run-ons sentence, Wrong form of verb pattern and Lack of parallel structure. Moreover, it is found that the results of writing error correction by using coded indirect corrective feedback and error treatment reveal the overall reduction of the frequent English writing errors and the increase of students’ achievement in the writing of short texts with the significance at .05.

Keywords: coded indirect corrective feedback, error correction, error treatment, frequent English writing errors

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Authors: M. Benghersallah, L. Boulanouar, G. List, G. Sutter

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The present work is an experimental study on the dry high speed turning of Ti-6Al-4V titanium alloy. The objective of this study is to see for high cutting speeds, how wear occurs on the face of insert and how to evolve cutting forces and chip formation. Cutting speeds tested is 600, 800, 1000 and 1200 m / min in orthogonal turning with a carbide insert tool H13A uncoated on a cylindrical titanium alloy part. Investigation on the wear inserts with 3D scanning microscope revered the crater formation is instantaneous and a chip adhesion (welded chip) causes detachment of carbide particles. In these experiments, the chip shape was systematically investigated at each cutting conditions using optical microscopy. The chips produced were collected and polished to measure the thicknesses t2max and t2min, dch the distance between each segments and ɸseg the inclination angle As described in the introduction part, the shear angle f and the inclination angle of a segment ɸseg are differentiated. The angle ɸseg is actually measured on the collected chips while the shear angle f cannot be. The angle ɸ represents the initial shear similar to the one that describes the formation of a continuous chip in the primary shear zone. Cutting forces increase and stabilize before removing the tool. The chip reaches a very high temperature.

Keywords: dry high speed, orthogonal turning, chip formation, cutting speed, cutting forces

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Authors: Mehtab Alam

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Sustainable tourism practices require to improve the decreased performance levels in phases of change management for image branding. This paper addresses the innovative approach of using sustainable tourism for image branding as a contemporary tool of foreign policy. The sustainable tourism-based foreign policy promotes cultural values, green tourism, economy, and image management for the avoidance of rising global conflict. The mixed-method approach (quantitative 382 surveys, qualitative 11 interviews at saturation point) implied for the data analysis. The research finding provides the potential of using sustainable tourism by implying skills and knowledge, capacity, and personal factors of change management in improving tourism-based performance levels. It includes the valuable tourism performance role for the success of a foreign policy through sustainable tourism. Change management in tourism-based foreign policy provides the destination readiness for international engagement and curbing of climate issues through green tourism. The research recommends the impact of change management in improving the tourism-based performance levels of image branding for a coercive foreign policy. The paper’s future direction for the immediate implementation of tourism-based foreign policy is to overcome the contemporary issues of travel marketing management, green infrastructure, and cross-border regulation.

Keywords: decrease performance levels, change management, sustainable tourism, image branding, foreign policy

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Authors: Leo Paul Vaurs, Sonia Heaven, Charles Banks

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Municipal solid waste (MSW) is a virtually unlimited source of lignocellulosic material in the form of a waste paper/cardboard mixture which can be converted into fermentable sugars via cellulolytic enzyme hydrolysis in a biorefinery. The extraction of the lignocellulosic fraction and its preparation, however, are energy and water demanding processes. The waste water generated is a rich organic liquor with a high Chemical Oxygen Demand that can be partially cleaned while generating biogas in an Upflow Anaerobic Sludge Blanket bioreactor and be further re-used in the process. In this work, an experiment was designed to determine the critical contaminant concentrations in water affecting either anaerobic digestion or enzymatic hydrolysis by simulating multiple water re-circulations. It was found that re-using more than 16.5 times the same water could decrease the hydrolysis yield by up to 65 % and led to a complete granules desegregation. Due to the complexity of the water stream, the contaminant(s) responsible for the performance decrease could not be identified but it was suspected to be caused by sodium, potassium, lipid accumulation for the anaerobic digestion (AD) process and heavy metal build-up for enzymatic hydrolysis. The experimental data were incorporated into a Water Pinch technology based model that was used to optimize the water re-utilization in the modelled system to reduce fresh water requirement and wastewater generation while ensuring all processes performed at optimal level. Multiple scenarios were modelled in which sub-process requirements were evaluated in term of importance, operational costs and impact on the CAPEX. The best compromise between water usage, AD and enzymatic hydrolysis yield was determined for each assumed contaminant degradations by anaerobic granules. Results from the model will be used to build the first MSW based biorefinery in the USA.

Keywords: anaerobic digestion, enzymatic hydrolysis, municipal solid waste, water optimization

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Authors: Latif Yanar, Muammer Kaçan

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Decision support systems are getting more important in many fields of science and technology and used effectively especially when the problems to be solved are complicated with many criteria. In this kind of problems one of the main challenges for the decision makers are that sometimes they cannot produce a countable data for evaluating the criteria but the knowledge and sense of experts. In recent years, fuzzy set theory and fuzzy logic based decision models gaining more place in literature. In this study, a decision support model to determine a country to build naval base is proposed and the application of the model is performed, considering Turkish Navy by the evaluations of Turkish Navy officers and academicians of international relations departments of various Universities located in Istanbul. The results achieved from the evaluations made by the experts in our model are calculated by a decision support tool named DESTEC 1.0, which is developed by the authors using C Sharp programming language. The tool gives advices to the decision maker using Analytic Hierarchy Process, Analytic Network Process, Fuzzy Analytic Hierarchy Process and Fuzzy Analytic Network Process all at once. The calculated results for five foreign countries are shown in the conclusion.

Keywords: decision support system, analytic hierarchy process, fuzzy analytic hierarchy process, analytic network process, fuzzy analytic network process, naval base, country selection, international relations

Procedia PDF Downloads 581

Authors: F. Bellali, M. Kharroubi, Y. Rady, N. Bourhim

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In Morocco, fish processing industry is an important source income for a large amount of by-products including skins, bones, heads, guts, and scales. Those underutilized resources particularly scales contain a large amount of proteins and calcium. Sardina plichardus scales from resulting from the transformation operation have the potential to be used as raw material for the collagen production. Taking into account this strong expectation of the regional fish industry, scales sardine upgrading is well justified. In addition, political and societal demands for sustainability and environment-friendly industrial production systems, coupled with the depletion of fish resources, drive this trend forward. Therefore, fish scale used as a potential source to isolate collagen has a wide large of applications in food, cosmetic, and biomedical industry. The main aim of this study is to isolate and characterize the acid solubilize collagen from sardine fish scale, Sardina pilchardus. Experimental design methodology was adopted in collagen processing for extracting optimization. The first stage of this work is to investigate the optimization conditions of the sardine scale deproteinization on using response surface methodology (RSM). The second part focus on the demineralization with HCl solution or EDTA. And the last one is to establish the optimum condition for the isolation of collagen from fish scale by solvent extraction. The advancement from lab scale to pilot scale is a critical stage in the technological development. In this study, the optimal condition for the deproteinization which was validated at laboratory scale was employed in the pilot scale procedure. The deproteinization of fish scale was then demonstrated on a pilot scale (2Kg scales, 20l NaOH), resulting in protein content (0,2mg/ml) and hydroxyproline content (2,11mg/l). These results indicated that the pilot-scale showed similar performances to those of lab-scale one.

Keywords: deproteinization, pilot scale, scale, sardine pilchardus

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Authors: Precious Ehiomogue, Ifechukwude Israel Ahuchaogu, Isiguzo Edwin Ahaneku

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Vermicompost is the product of the decomposition process using various species of worms, to create a mixture of decomposing vegetable or food waste, bedding materials, and vemicast. This process is called vermicomposting, while the rearing of worms for this purpose is called vermiculture. Several works have verified the adsorption of toxic metals using vermicompost but the application is still scarce for the retention of organic compounds. This research brings to knowledge the effectiveness of earthworm waste (vermicompost) for the remediation of crude oil contaminated soils. The remediation methods adopted in this study were two soil washing methods namely, batch and column process which represent laboratory and in-situ remediation. Characterization of the vermicompost and crude oil contaminated soil were performed before and after the soil washing using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray fluorescence (XRF), X-ray diffraction (XRD) and Atomic adsorption spectrometry (AAS). The optimization of washing parameters, using response surface methodology (RSM) based on Box-Behnken Design was performed on the response from the laboratory experimental results. This study also investigated the application of machine learning models [Artificial neural network (ANN), Adaptive neuro fuzzy inference system (ANFIS). ANN and ANFIS were evaluated using the coefficient of determination (R²) and mean square error (MSE)]. Removal efficiency obtained from the Box-Behnken design experiment ranged from 29% to 98.9% for batch process remediation. Optimization of the experimental factors carried out using numerical optimization techniques by applying desirability function method of the response surface methodology (RSM) produce the highest removal efficiency of 98.9% at absorbent dosage of 34.53 grams, adsorbate concentration of 69.11 (g/ml), contact time of 25.96 (min), and pH value of 7.71, respectively. Removal efficiency obtained from the multilevel general factorial design experiment ranged from 56% to 92% for column process remediation. The coefficient of determination (R²) for ANN was (0.9974) and (0.9852) for batch and column process, respectively, showing the agreement between experimental and predicted results. For batch and column precess, respectively, the coefficient of determination (R²) for RSM was (0.9712) and (0.9614), which also demonstrates agreement between experimental and projected findings. For the batch and column processes, the ANFIS coefficient of determination was (0.7115) and (0.9978), respectively. It can be concluded that machine learning models can predict the removal of crude oil from polluted soil using vermicompost. Therefore, it is recommended to use machines learning models to predict the removal of crude oil from contaminated soil using vermicompost.

Keywords: ANFIS, ANN, crude-oil, contaminated soil, remediation and vermicompost

Procedia PDF Downloads 101

Authors: Esraa Mohamed El-Fawal

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A facile solvothermal procedure was applied to fabricate zinc ferrite nanoparticles (ZnFe₂O₄ NPs). Activated carbon (AC) derived from peanut shells is synthesized using a microwave through the chemical activation method. The ZnFe₂O₄-AC composite is then mixed with a cerium-based metal-organic framework (CeMOF) by solid-state adding to formulate ZnFe₂O₄-AC/CeMOF composite. The synthesized photo materials were tested by scanning/transmission electron microscope (SEM/TEM), Photoluminescence (PL), (XRD) X-Ray diffraction, (FTIR) Fourier transform infrared, (UV-Vis/DRS) ultraviolet-visible/diffuse reflectance spectroscopy. The prepared ZnFe₂O₄-AC/CeMOFphotomaterial shows significantly boosted efficiency for photodegradation of methyl orange /methylene blue (MO/MB) compared with the pristine ZnFe₂O₄ and ZnFe₂O₄-AC composite under the irradiation of visible-light. The favorable ZnFe₂O₄-AC/CeMOFphotocatalyst displays the highest photocatalytic degradation efficiency of MB/MO (R: 91.5-88.6%, consecutively) compared with the other as-prepared materials after 30 min of visible-light irradiation. The apparent reaction rate K: 1.94-1.31 min-1 is also calculated. The boosted photocatalytic proficiency is ascribed to the heterojunction at the interface of prepared photo material that assists the separation of the charge carriers. To reach optimization, statistical analysis using response surface methodology was applied. The effect of independent parameters (such as A (pH), B (irradiation time), and (c) initial pollutants concentration on the response function (%)photodegradation of MB/MO dyes (as examples of azodyes) was investigated via using central composite design. At the optimum condition, the photodegradation efficiency (%) of the MB/MO is 99.8-97.8%, respectively. ZnFe2O₄-AC/CeMOF hybrid reveals good stability over four consecutive cycles.

Keywords: azo-dyes, photo-catalysis, zinc ferrite, response surface methodology

Procedia PDF Downloads 157

Authors: Martha Wilson

Abstract:

With the peak of Computer-Assisted Language Learning slowly coming to pass and Mobile-Assisted Language Learning, at times, a bit lacking in the communicative department, we are now faced with a challenging question: How can we engage the interest of our digital native students and, most importantly, sustain it? As previously mentioned, our classrooms are now experiencing an influx of “digital natives” – people who have grown up using and having unlimited access to technology. While modernizing our curriculum and digitalizing our classrooms are necessary in order to accommodate this new learning style, it is a huge financial burden and a massive undertaking for language institutes. Instead, opting for a more compact, simple, yet multidimensional pedagogical tool may be the solution to the issue at hand. This paper aims to give a brief overview into an existing device referred to as Student Response Systems (SRS) and to expand on this notion to include a new prototype of response system that will be designed as a mobile application to eliminate the need for costly hardware and software. Additionally, an analysis into recent attempts by other institutes to develop the Mobile Response System (MRS) and customer reviews of the existing MRSs will be provided, as well as the lessons learned from those projects. Finally, while the new model of MRS is still in its infancy stage, this paper will discuss the implications of incorporating such an application as a tool to support and to enrich traditional techniques and also offer practical classroom applications with the existing response systems that are immediately available on the market.

Keywords: app, clickers, mobile app, mobile response system, student response system

Procedia PDF Downloads 366

Authors: Oluwatoyin Joseph Gbadeyan, Sarp Adali, Bright Glen, Bruce Sithole

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Sodium lauryl surfactant concentration optimization, for nanoparticle production, provided the platform for advanced research studies. Different concentrations (0.05 %, 0.1 %, and 0.2 %) of sodium lauryl surfactant was added to snail shells powder during milling processes for producing CaCO3 at smaller particle size. Epoxy nanocomposites prepared at filler content 2 wt.% synthesized with different volumes of sodium lauryl surfactant were fabricated using a conventional resin casting method. Mechanical properties such as tensile strength, stiffness, and hardness of prepared nanocomposites was investigated to determine the effect of sodium lauryl surfactant concentration on nanocomposite properties. It was observed that the loading of the synthesized nano-calcium carbonate improved the mechanical properties of neat epoxy at lower concentrations of sodium lauryl surfactant 0.05 %. Meaningfully, loading of achatina fulica snail shell nanoparticles manufactures, with small concentrations of sodium lauryl surfactant 0.05 %, increased the neat epoxy tensile strength by 26%, stiffness by 55%, and hardness by 38%. Homogeneous dispersion facilitated, by the addition of sodium lauryl surfactant during milling processes, improved mechanical properties. Research evidence suggests that nano-CaCO3, synthesized from achatina fulica snail shell, possesses suitable reinforcement properties that can be used for nanocomposite fabrication. The evidence showed that adding small concentrations of sodium lauryl surfactant 0.05 %, improved dispersion of nanoparticles in polymetrix material that provided mechanical properties improvement.

Keywords: sodium lauryl surfactant, mechanical properties , achatina fulica snail shel, calcium carbonate nanopowder

Procedia PDF Downloads 137