Search results for: route optimization

Authors: Antaram Sarve, Mahesh Varma, Shriram Sonawane

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Conventional route of producing biodiesel with alcohol produces glycerol as side product which leads to oversupply and devaluation in the world market. Supercritical methyl acetate (SCMA) has been proven to convert triglycerides into fatty acid methyl esters (FAMEs) and triacetin, which is a valuable biodiesel additive as side product rather than glycerol. However, due to the low reactivity of supercritical methyl acetate on triglycerides, high reaction conditions are required to obtained maximum yields. The present study describes the renewable approach for the production of biodiesel from low-cost, high acid value mahua oil under supercritical methyl acetate condition using carbon dioxide (CO2) as a co-solvent. CO2 was employed to decrease high reaction conditions required for supercritical methyl acetate transesterification. The influence of process parameters such as temperature, oil to methyl acetate molar ratio, reaction time, and the CO2 pressure was evaluated. The properties of biodiesel produced were found to be superior compared to conventional biodiesel method. Furthermore, SCMA has a high tolerance towards free fatty acids (FFAs) which is crucial to allow the utilization of inexpensive waste oils as a biodiesel feedstock.

Keywords: supercritical methyl acetate, CO2, biodiesel, fuel properties

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Authors: Sahithi Yarlagadda

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The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

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Authors: Richard Maguire

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This research evaluates the efficiency of using mobile HEPA filters to reduce localized Particulate Matter (PM), Total Volatile Organic Chemical (TVOC) and Formaldehyde (HCHO) Air Pollution. The research is being performed using a standard HEPA filter that is tube fitted and attached to a motor vehicle. The velocity of the vehicle is used to generate the pressure difference that allows the filter to remove PM, VOC and HCOC pollution from the localized atmosphere of a road transport traffic route. The testing has been performed on a sample of traffic routes in Non-Sparse and Sparse urban environments within the UK. Pre and Post filter measuring of the PM2.5 Air Quality has been carried out along with demographics of the climate environment, including live filming of the traffic conditions. This provides a base line for future national and international research. The effectiveness measurement is generated through evaluating the difference in PM2.5 Air Quality measured pre- and post- the mobile filter test equipment. A series of further research opportunities and future exploitation options are made based on the results of the research.

Keywords: high efficiency particulate air, HEPA filter, particulate matter, traffic pollution

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Authors: Lukman Andi Priyatna, Vivi Fauzia, Ferry Anggoro Ardy Nugroho

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Zinc oxide (ZnO) based nanostructures are ubiquitous in applications due to their favourable physicochemical properties and ease of fabrication. One widely accessible route to synthesize ZnO nanorods, which show promising performance in e.g. photoelectrochemical water splitting, is hydrothermal growth of ZnO seeds, obtained via an atomic nebulizer. Despite its popularity, study on the impact of the synthesis parameters in atomic nebulizer on the performance of the synthesized ZnO nanostructures is lacking. This study presents an investigation on the impact of the distance between substrates and atomic nebulizer nozzle on the photoelectrochemical water splitting performance of ZnO nanorods. Adjusting such a distance reveals an optimum separation which results in nanostructures with highest absorbance. Such high absorbance translates into improved photoelectrochemistry, as evaluated by higher photocurrent density, from 0.11 mA/cm² to 0.14 mA/cm² and higher Applied Bias Photon-to-Current Efficiency (ABPE) from 0.12% to 0.14%. These results underscore the importance of understanding and optimizing the experimental parameters during ZnO nanostructure synthesis. In a broader context, it advertises the need to carefully assess the corresponding fabrication parameters to optimize the performance of the obtained nanostructures.

Keywords: atomic nebulizer, photocurrent density, photoelectrochemical water splitting, ZnO nanorods

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Authors: Mahmoud B. Rokaya

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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

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Authors: Mariem Saied, Jens Gustedt, Gilles Muller

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We present Dido, a source-to-source auto-generation and optimization framework for multi-dimensional stencil computations. It enables a large programmer community to easily and safely implement stencil codes on distributed-memory parallel architectures with Ordered Read-Write Locks (ORWL) as an execution and communication back-end. ORWL provides inter-task synchronization for data-oriented parallel and distributed computations. It has been proven to guarantee equity, liveness, and efficiency for a wide range of applications, particularly for iterative computations. Dido consists mainly of an implicitly parallel domain-specific language (DSL) implemented as a source-level transformer. It captures domain semantics at a high level of abstraction and generates parallel stencil code that leverages all ORWL features. The generated code is well-structured and lends itself to different possible optimizations. In this paper, we enhance Dido to handle both Jacobi and Gauss-Seidel grid traversals. We integrate temporal blocking to the Dido code generator in order to reduce the communication overhead and minimize data transfers. To increase data locality and improve intra-node data reuse, we coupled the code generation technique with the polyhedral parallelizer Pluto. The accuracy and portability of the generated code are guaranteed thanks to a parametrized solution. The combination of ORWL features, the code generation pattern and the suggested optimizations, make of Dido a powerful code generation framework for stencil computations in general, and for distributed-memory architectures in particular. We present a wide range of experiments over a number of stencil benchmarks.

Keywords: stencil computations, ordered read-write locks, domain-specific language, polyhedral model, experiments

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Authors: Catherine Kuforiji, Michel Nganbe

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The abrasive wear of composite materials is a major challenge in highly demanding wear applications. Therefore, this study focuses on fabricating, testing and assessing the properties of 50wt% SS316L stainless steel–50wt% Al2O3 particle composites. Composite samples were fabricated using the powder metallurgy route. The effects of the powder metallurgy processing parameters and hard particle reinforcement were studied. The microstructure, density, hardness and toughness were characterized. The wear behaviour was studied using pin-on-disc testing under dry sliding conditions. The highest hardness of 1085.2 HV, the highest theoretical density of 94.7% and the lowest wear rate of 0.00397 mm3/m were obtained at a milling speed of 720 rpm, a compaction pressure of 794.4 MPa and sintering at 1400 °C in an argon atmosphere. Compared to commercial SS316 and fabricated SS316L, the composites had 7.4 times and 11 times lower wear rate, respectively. However, the commercial 90WC-10Co showed 2.2 times lower wear rate compared to the fabricated SS316L-Al2O3 composites primarily due to the higher ceramic content of 90 wt.% in the reference WC-Co. However, eliminating the relatively high porosity of about 5 vol% using processes such as HIP and hot pressing can be expected to lead to further substantial improvements of the composites wear resistance.

Keywords: SS316L, Al2O3, powder metallurgy, wear characterization

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Authors: Dina Athariah, Desriani Desriani, Bugi Ratno Budiarto, Abinawanto Abinawanto, Dwi Wulandari

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Breast cancer is a regulated by many genes. Defect in PIK3CA gene especially at position of exon 9 (E542K and E545K), called hot spot mutation induce early transformation of breast cells. The early detection of breast cancer based on mutation profile of this hot spot region would be hampered by the existence of pseudogene, marked by its substitution mutation at base 1658 (E545A) and deletion at 1659 that have been previously proven in several cancers. To the best of the authors’ knowledge, until recently no studies have been reported about pseudogene phenomenon in breast cancer. Here, we reported PCR optimization to to obtain true exon 9 of PIK3CA gene from its pseudogene hence increasing the validity of data. Material and methods: two genomic DNA with Dev and En code were used in this experiment. Two pairs of primer were design for Standard PCR method. The size of PCR products for each primer is 200bp and 400bp. While other primer was designed for Nested-PCR followed with DNA sequencing method. For Nested-PCR, we optimized the annealing temperature in first and second run of PCR, and the PCR cycle for first run PCR (15x versus 25x). Result: standard PCR using both primer pairs designed is failed to detect the true PIK3CA gene, appearing a substitution mutation at 1658 and deletion at 1659 of PCR product in sequence chromatogram indicated pseudogene. Meanwhile, Nested-PCR with optimum condition (annealing temperature for the first round at 55oC, annealing temperatung for the second round at 60,7oC with 15x PCR cycles) and could detect the true PIK3CA gene. Dev sample were identified as WT while En sample contain one substitution mutation at position 545 of exon 9, indicating amino acid changing from E to K. For the conclusion, pseudogene also exists in breast cancer and the apllication of optimazed Nested-PCR in this study could detect the true exon 9 of PIK3CA gene.

Keywords: breast cancer, exon 9, hotspot mutation, PIK3CA, pseudogene

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Authors: Konstantinos Liagkouras, Konstantinos Metaxiotis

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In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a comparative study of the different technologies applied for efficient portfolio construction and we suggest potential paths for future work that lie at the intersection of the presented techniques.

Keywords: portfolio selection, optimization techniques, financial models, stochastic, heuristics

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Authors: Mercy Chepkirui, Paul Orina, Robin Abell, Leonard Akwany, Tonny Orina, Mercy Matuma, Rasowo Joseph

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Lake jipe, a shared water resource between Kenya and Tanzania located at the East African Coast, is under multiple pressures. The lake has receded from 30Km2 to 27.32Km2 due to prolonged dry spells and intensified water abstraction for irrigation and re-route to Mungu ya Nyumba Dam in Tanzania. Agricultural activities have significantly (90%) contributed to the lake levels decline and further affected the lakes’ aquatic biodiversity. Among the most affected are the commercially important endemic fish species of the lake, of which Oreochromis jipe has experienced the greatest decline. Overfishing, use of illegal unreported and unregulated fishing gears, intensified fishing along protected fish breeding areas as well as poor management and uncoordinated conservation efforts have significantly contributed to the decline of fish catches from 348 kg of O. jipe in 2016 to 90 kg daily catches in 2022. Therefore, the lake is on the verge of extinction if no action is taken. This calls for awareness of the significance of the L. Jipe ecosystems and its immediate and long-term benefits. Further, there is a need to revive alternative economic activities, including aquaculture and sustainable agriculture, to offer alternative livelihood to local communities.

Keywords: biodiversity, ecosystem, conservation, fisheries

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Authors: Nils Mueller, Gregor Herz, Erik Reichelt, Matthias Jahn

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In the context of climate change, the reduction of greenhouse gas emissions in all economic sectors is considered to be an important factor in order to meet the demands of a sustainable energy system. The steel industry as one of the large industrial CO₂ emitters is currently highly dependent on fossil resources. In order to reduce coke consumption and thereby CO₂ emissions while still being able to further utilize existing blast furnaces, the possibility of including a direct reduction process (DRP) into a fully integrated steel mill was investigated. Therefore, a blast furnace model, derived from literature data and implemented in Aspen Plus, was used to analyze the impact of DRI in the blast furnace process. Furthermore, a state-of-the-art DRP was modeled to investigate the possibility of substituting the reducing agent natural gas with hydrogen. A sensitivity analysis was carried out in order to find the boundary percentage of hydrogen as a reducing agent without penalty to the DRI quality. Lastly, the two modeled process steps were combined to form a route of producing pig iron. By varying boundary conditions of the DRP while recording the CO₂ emissions of the two process steps, the overall potential for the reduction of CO₂ emissions was estimated. Within the simulated range, a maximum reduction of CO₂ emissions of 23.5% relative to typical emissions of a blast furnace could be determined.

Keywords: blast furnace, CO₂ mitigation, DRI, hydrogen

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Authors: Ferdi Sönmez, Nihal Yorulmaz

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Decision making on the true planning of the public transportation systems to serve potential users is a must for metropolitan areas. To take attraction of travelers to projected modes of transport, adequately fair overall travel times should be provided. In this fashion, other benefits such as lower traffic congestion, road safety and lower noise and atmospheric pollution may be earned. The congestion which comes with increasing demand of public transportation is becoming a part of our lives and making residents’ life difficult. Hence, regulations should be done to reduce this congestion. To provide a constructive and balanced regulation in public transportation systems, right stations should be located in right places. In this study, it is aimed to design and implement a Decision Support System (DSS) Application to determine the optimal bus stop places for public transport in Istanbul which is one of the biggest and oldest cities in the world. Required information is gathered from IETT (Istanbul Electricity, Tram and Tunnel) Enterprises which manages all public transportation services in Istanbul Metropolitan Area. By using the most real-like values, cost assignments are made. The cost is calculated with the help of equations produced by bi-level optimization model. For this study, 300 buses, 300 drivers, 10 lines and 110 stops are used. The user cost of each station and the operator cost taken place in lines are calculated. Some components like cost, security and noise pollution are considered as significant factors affecting the solution of set covering problem which is mentioned for identifying and locating the minimum number of possible bus stops. Preliminary research and model development for this study refers to previously published article of the corresponding author. Model results are represented with the intent of decision support to the specialists on locating stops effectively.

Keywords: operator cost, bi-level optimization model, user cost, urban transportation

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Authors: Konja Knüppel, Gerrit Meyer, Peter Nyhuis

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The increasing interconnectedness and complexity of production processes raise the susceptibility of production systems to failure. Therefore, the ability to respond quickly to failures is increasingly becoming a competitive factor. The research project "Sustainable failure management in manufacturing SMEs" is developing a methodology to identify failures in the production and select preventive and reactive measures in order to correct failures and to establish sustainable failure management systems.

Keywords: failure categorization, failure management, logistic performance, production optimization

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Authors: Ayman Hassouna

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Gaza was famous in the history of trade, because it lies at the end of overland trade route, then the goods transferred by Gazzian merchants to different places around the Mediterranean, so it is described as ‘Mediterranean port of Arabs’, but Gaza is not located directly at the sea shore, so it is fortified by two ports: the first is Anthedon, and second is Maiomas. It is possible to dig in Anthedon but it is too difficult to do that in Maiomas because the site is full of modern buildings. Archaeological excavations at Anthedon's port provided us much archaeological and historical information about cooperation between Anthedon's port and different places at the Mediterranean basin. This research speaks about the roots of Anthedon's name, and it is related with other names in Greek land, by use different dictionaries language, and produce historical introduction were covering the ages beginning from the Iron Age to Greek, Roman and Byzantine periods. Then the study reviewed the most important architectural discoveries in the site, and highlighted the relationship with the civilizations' ports of the Mediterranean basin by studying number of artefacts pottery were imported from different places as Cyprus, Greece, Italy, North Africa, Carthage and Tripoli workshops. On the other hand, the archaeologists discovered some of local pottery made in Gaza at different sites on the Mediterranean basin which confirms the relationship of Gaza merchants with those areas. At the end of this study, there are some conclusions and recommendations about the site.

Keywords: ancient port of Gaza, pottery typology, Mediterranean basin ports, Palestine archaeology

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Authors: Umair Ahmed, Muhammad Bin Irfan

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This study focuses on designing and optimization of an alkaline water electrolyser for the production of green hydrogen. The aim is to enhance the durability and efficiency of this technology while simultaneously reducing the cost associated with the production of green hydrogen. The experimental results obtained from the alkaline water electrolyser are compared with simulated results using Aspen Plus software, allowing a comprehensive analysis and evaluation. To achieve the aforementioned goals, several design and operational parameters are investigated. The electrode material, electrolyte concentration, and operating conditions are carefully selected to maximize the efficiency and durability of the electrolyser. Additionally, cost-effective materials and manufacturing techniques are explored to decrease the overall production cost of green hydrogen. The experimental setup includes a carefully designed alkaline water electrolyser, where various performance parameters (such as hydrogen production rate, current density, and voltage) are measured. These experimental results are then compared with simulated data obtained using Aspen Plus software. The simulation model is developed based on fundamental principles and validated against the experimental data. The comparison between experimental and simulated results provides valuable insight into the performance of an alkaline water electrolyser. It helps to identify the areas where improvements can be made, both in terms of design and operation, to enhance the durability and efficiency of the system. Furthermore, the simulation results allow cost analysis providing an estimate of the overall production cost of green hydrogen. This study aims to develop a comprehensive understanding of alkaline water electrolysis technology. The findings of this research can contribute to the development of more efficient and durable electrolyser technology while reducing the cost associated with this technology. Ultimately, these advancements can pave the way for a more sustainable and economically viable hydrogen economy.

Keywords: sustainable development, green energy, green hydrogen, electrolysis technology

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Authors: F. Z. Benabid, S. Kridi, F. Zouai, D. Benachour

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The aim of present work is to characterize the PVDF/TiO2 blends as nanocomposites, and study the effect of TiO2 on properties of different compositions and the evaluation of the effectiveness of the method used for filler treatment. Nanocomposite samples were synthesized by molten route in an internal mixer. The TiO2 nanoparticles were treated with stearic acid in order to obtain a good dispersion, and the demonstration of the effectiveness of the treatment on the morphology and roughness of the nanofiller was established by microstructural analysis by FTIR and AFM. The various developed nanocomposite compositions were characterized by different methods; i.e. FTIR, XRD, SEM and optical microscopy. Rheological, dielectric and mechanical studies were also performed. The results showed a remarkable increase in the crystallinity of the PVDF/neat TiO2 nanocomposite containing 1 wt% loading of filler, due to the nucleation effect of TiO2 nanoparticles. A good dispersion was obtained in PVDF/treated TiO2 nanocomposites. The rheological study showed an increase in the fluidity in all developed nanocomposite compositions, involved by the orientation of TiO2 nanoparticles in the flow direction. The dielectric study revealed an increase in electrical conductivity in PVDF/neat TiO2 nanocomposites. However, in PVDF/ treated TiO2 nanocomposites, the electrical conductivity was decreased by the addition of 0.5 and 2 wt% loading of filler.

Keywords: nanocomposites, PVDF, TiO2, comixing, mechanical treatment

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Authors: Tahir Ahmad, M. Kamran, R. Ahmad, M. T. Z. Butt

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Hybrid aluminum metal matrix composites with 1, 2, 3 and 4 wt. % of silica sand nanoparticles and electro-less nickel coated carbon fibers were successfully developed using sand casting technique. Epoxy coating of carbon fibers was removed and phosphorous-nickel coating was successfully applied via electro-less route. The developed hybrid composites were characterized using micro hardness tester, tensile testing, and optical microscopy. The gradual increase of reinforcing phases yielded improved mechanical properties such as hardness and tensile strength. The increase in hardness was attributed to the presence of silica sand nanoparticles whereas electro-less nickel coated carbon fibers enhanced the tensile properties of developed hybrid composites. The microstructure of the developed hybrid composites revealed the homogeneous distribution of both carbon fibers and silica sand nanoparticles in aluminum based hybrid composites. The formation of dendrite microstructure is the main cause of improving mechanical properties.

Keywords: aluminum based hybrid composites, mechanical properties, microstructure, microstructure and mechanical properties relationship

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Authors: Yujie Zhao, Jiantao Weng

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In the past decade, with the rapid development of China's economy, the purchasing power and physical demand of residents have been improved, which results in the vast emergence of public buildings like large shopping malls. However, the architects usually focus on the internal functions and streamlines of these buildings, ignoring the impact of the environment on the subjective feelings of building users. Only in Zhejiang province, the infiltration of cold air in winter frequently occurs at the entrance of sizeable commercial complex buildings that have been in operation, which will affect the environmental comfort of the building lobby and internal public spaces. At present, to reduce these adverse effects, it is usually adopted to add active equipment, such as setting air curtains to block air exchange or adding heating air conditioners. From the perspective of energy consumption, the infiltration of cold air into the entrance will increase the heat consumption of indoor heating equipment, which will indirectly cause considerable economic losses during the whole winter heating stage. Therefore, it is of considerable significance to explore the suitable entrance forms for improving the environmental comfort of commercial buildings and saving energy. In this paper, a commercial complex with apparent cold air infiltration problem in Hangzhou is selected as the research object to establish a model. The environmental parameters of the building entrance, including temperature, wind speed, and infiltration air volume, are obtained by Computational Fluid Dynamics (CFD) simulation, from which the heat consumption caused by the natural air infiltration in the winter and its potential economic loss is estimated as the objective metric. This study finally obtains the optimization direction of the building entrance form of the commercial complex by comparing the simulation results of other local commercial complex projects with different entrance forms. The conclusions will guide the entrance design of the same type of commercial complex in this area.

Keywords: air infiltration, commercial complex, heat consumption, CFD simulation

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Authors: Chandan Deep Singh, Jaimal Singh Khamba, Harleen Kaur

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Eminence, charge, deliverance, modernism, and awareness underlie most manufacturing strategic plan today. Firms have traditionally pursued the above tasks through the implementation of advanced technologies and manufacturing practices, such as Reverse Engineering, Value Engineering, worker empowerment, etc. Recent developments in industry suggest the materialization of another route to manufacturing brilliance, that is, there is an increasing focus by industry regulators and professional bodies on the need to stimulate innovation in a broad range of manufacturing competencies. By ‘competencies’ we mean the methods, equipment and expertise that can be developed as a leading capability in one market sector or application and have real potential to be applied successfully across other sectors or applications as well. Further, competencies are the ability to apply or use a set of related knowledge, skills, and abilities to perform 'critical work functions' or tasks in a defined work setting. Competencies often serve as the basis for skill standards that specify the level of knowledge, skills, and abilities required for success in the workplace as well as potential measurement criteria for assessing competency attainment. The present research is so designed to come up to the level of the expectations of the industrialists, policy makers, designers of the competencies, specially, the manufacturing competencies upon which the whole strategic success of the industry depends.

Keywords: manufacturing competency, strategic success, manufacturing excellence, competitive strategy

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Authors: Reem Al-Shidhani, Isabelle S. R. Storer, Michael J. Bromley, Lydia Tabernero

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Invasive fungal diseases are an increasing global health concern that contributes to the high mortality rates in immunocompromised patients. The rising of antifungal resistance severely lowers the efficacy of the limited antifungal agents available. New antifungal drugs that target new mechanisms are necessary to tackle the current shortfalls. Amongst post- modifications, phosphorylation is a predominant and an outstanding protein alteration in all eukaryotes. In fungi, protein phosphorylation plays a vital role in many signal transduction pathways, including cell cycle, cell growth, metabolism, transcription, differentiation, proliferation, and virulence. The investigation of Aspergillus fumigatus phosphatases revealed seven genes essential for viability. Inhibiting one of these phosphatases is a new interesting route to develop novel antifungal drugs. In this study, we carried out an early drug discovery process targeting oneessential phosphatase, GlcA. Here, we report the identification of new GlcA inhibitors that show antifungal activity. These important finding open a new avenue to the development of novel antifungals to expand the current narrow arsenal of clinical candidates.

Keywords: invasive fungal diseases, phosphatases, GlcA, competitive inhibitors

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Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Alejandro Tellez-Jurado, Juan C. Seck-Tuoh-Mora, Eva S. Hernandez-Gress, Norberto Hernandez-Romero, Iaina P. Medina-Serna

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Trichoderma harzianum is a fungus that has been utilized as a low-cost fungicide for biological control of pests, and it is important to determine the optimal conditions to produce the highest amount of conidiospores of Trichoderma harzianum. In this work, the conidiospore production of Trichoderma harzianum is modeled and optimized by using Artificial Neural Networks (AANs). In order to gather data of this process, 30 experiments were carried out taking into account the number of hours of culture (10 distributed values from 48 to 136 hours) and the culture humidity (70, 75 and 80 percent), obtained as a response the number of conidiospores per gram of dry mass. The experimental results were used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers, and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The ANN with the best performance was chosen in order to simulate the process and be able to maximize the conidiospores production. The obtained ANN with the highest performance has 2 inputs and 1 output, three hidden layers with 3, 10 and 10 neurons in each layer, respectively. The ANN performance shows an R2 value of 0.9900, and the Root Mean Squared Error is 1.2020. This ANN predicted that 644175467 conidiospores per gram of dry mass are the maximum amount obtained in 117 hours of culture and 77% of culture humidity. In summary, the ANN approach is suitable to represent the conidiospores production of Trichoderma harzianum because the R2 value denotes a good fitting of experimental results, and the obtained ANN model was used to find the parameters to produce the biggest amount of conidiospores per gram of dry mass.

Keywords: Trichoderma harzianum, modeling, optimization, artificial neural network

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Authors: Christina Kirsch, Adam Hatzigiannis

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Rail operators and maintainers worldwide are increasingly replacing walking patrols in the rail corridor with mechanized track patrols -essentially data capture on trains- and on-screen reviews of track infrastructure in centralized review facilities. The benefit is that infrastructure workers are less exposed to the dangers of the rail corridor. The impact is a significant change in work design from walking track sections and direct observation in the real world to sedentary jobs in the review facility reviewing captured data on screens. Defects in rail infrastructure can have catastrophic consequences. Reviewer performance regarding accuracy and efficiency of reviews within the available time frame is essential to ensure safety and operational performance. Rail operators must optimize workload and resource loading to transition to on-screen reviews successfully. Therefore, they need to know what workload assessment methodologies will provide reliable and valid data to optimize resourcing for on-screen reviews. This paper compares objective workload measures, including track difficulty ratings and review distance covered per hour, and subjective workload assessments (NASA TLX) and analyses the link between workload and reviewer performance, including sensitivity, precision, and overall accuracy. An experimental study was completed with eight on-screen reviewers, including infrastructure workers and engineers, reviewing track sections with different levels of track difficulty over nine days. Each day the reviewers completed four 90-minute sessions of on-screen inspection of the track infrastructure. Data regarding the speed of review (km/ hour), detected defects, false negatives, and false positives were collected. Additionally, all reviewers completed a subjective workload assessment (NASA TLX) after each 90-minute session and a short employee engagement survey at the end of the study period that captured impacts on job satisfaction and motivation. The results showed that objective measures for tracking difficulty align with subjective mental demand, temporal demand, effort, and frustration in the NASA TLX. Interestingly, review speed correlated with subjective assessments of physical and temporal demand, but to mental demand. Subjective performance ratings correlated with all accuracy measures and review speed. The results showed that subjective NASA TLX workload assessments accurately reflect objective workload. The analysis of the impact of workload on performance showed that subjective mental demand correlated with high precision -accurately detected defects, not false positives. Conversely, high temporal demand was negatively correlated with sensitivity and the percentage of detected existing defects. Review speed was significantly correlated with false negatives. With an increase in review speed, accuracy declined. On the other hand, review speed correlated with subjective performance assessments. Reviewers thought their performance was higher when they reviewed the track sections faster, despite the decline in accuracy. The study results were used to optimize resourcing and ensure that reviewers had enough time to review the allocated track sections to improve defect detection rates in accordance with the efficiency-thoroughness trade-off. Overall, the study showed the importance of a multi-method approach to workload assessment and optimization, combining subjective workload assessments with objective workload and performance measures to ensure that recommendations for work system optimization are evidence-based and reliable.

Keywords: automation, efficiency-thoroughness trade-off, human factors, job design, NASA TLX, performance optimization, subjective workload assessment, workload analysis

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Authors: Stela Papa, Klementina Puto, Migena Pllaha

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HCV is a hepatotropic RNA virus, transmitted primarily via the blood route, which causes progressive disease such as chronic hepatitis, liver cirrhosis, or hepatocellular carcinoma. HCV nowadays is a global healthcare problem. A variety of immunoassays including old and new technologies are being applied to detect HCV in our country. These methods include Immunochromatography assays (ICA), Fluorescence immunoassay (FIA), Enzyme linked fluorescent assay (ELFA), and Enzyme linked immunosorbent assay (ELISA) to detect HCV antibodies in blood serum, which lately is being slowly replaced by more sensitive methods such as rapid automated analyzer chemiluminescence immunoassay (CLIA). The aim of this study is to estimate HCV infection in carriers and chronic acute patients and to evaluate the use of new diagnostic methods. This study was realized from September 2016 to May 2018. During this study period, 2913 patients were analyzed for the presence of HCV by taking samples from their blood serum. The immunoassays performed were ICA, FIA, ELFA, ELISA, and CLIA assays. Concluding, 82% of patients taken in this study, resulted infected with HCV. Diagnostic methods in clinical laboratories are crucial in the early stages of infection, in the management of chronic hepatitis and in the treatment of patients during their disease.

Keywords: CLIA, ELISA, Hepatitis C virus, immunoassay

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Authors: Boris G. German, Edward Jiménez, Sebastián Espinoza, Andrés G. Chico, Ricardo A. Narváez

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The unique flora and fauna of The Galapagos Islands has leveraged a tourism-driven growth in the islands. Nonetheless, such development is energy-intensive and requires thousands of gallons of diesel each year for thermoelectric electricity generation. The needed transport of fossil fuels from the continent has generated oil spillages and affectations to the fragile ecosystem of the islands. The Zero Fossil Fuels initiative for The Galapagos proposed by the Ecuadorian government as an alternative to reduce the use of fossil fuels in the islands, considers the replacement of diesel in thermoelectric generators, by Jatropha curcas vegetable oil. However, the Jatropha oil supply cannot entirely cover yet the demand for electricity generation in Galapagos. Within this context, the present work aims to provide an optimization model that can be used as a selection criterion for approving new Jatropha Curcas collection points in rural areas of Manabi-Ecuador. For this purpose, existing Jatropha collection points in Manabi were grouped under three regions: north (7 collection points), center (4 collection points) and south (9 collection points). Field work was carried out in every region in order to characterize the collection points, to establish local Jatropha supply and to determine transportation costs. Data collection was complemented using GIS software and an objective function was defined in order to determine the profit associated to Jatropha oil production. The market price of both Jatropha oil and residual cake, were considered for the total revenue; whereas Jatropha price, transportation and oil extraction costs were considered for the total cost. The tonnes of Jatropha fruit and seed, transported from collection points to the extraction plant, were considered as variables. The maximum and minimum amount of the collected Jatropha from each region constrained the optimization problem. The supply chain was optimized using linear programming in order to maximize the profits. Finally, a sensitivity analysis was performed in order to find a profit-based criterion for the acceptance of future collection points in Manabi. The maximum profit reached a value of $ 4,616.93 per year, which represented a total Jatropha collection of 62.3 tonnes Jatropha per year. The northern region of Manabi had the biggest collection share (69%), followed by the southern region (17%). The criteria for accepting new Jatropha collection points in the rural areas of Manabi can be defined by the current maximum profit of the zone and by the variation in the profit when collection points are removed one at a time. The definition of new feasible collection points plays a key role in the supply chain associated to Jatropha oil production. Therefore, a mathematical model that assists decision makers in establishing new collection points while assuring profitability, contributes to guarantee a continued Jatropha oil supply for Galapagos and a sustained economic growth in the rural areas of Ecuador.

Keywords: collection points, Jatropha curcas, linear programming, supply chain

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Authors: Yasser Gaber, Mohamed Ismail, Serena Bisagni, Mohamad Takwa, Rajni Hatti-Kaul

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Enzymes are safe and selective catalysts. They skillfully catalyze chemical reactions; however, the native form is not usually suitable for industrial applications. Enzymes are therefore engineered by several techniques to meet the required catalytic task. Clopidogrel is recorded among the five best selling pharmaceutical in 2010 under the brand name Plavix. The commonly used route for production of the drug on an industrial scale is the synthesis of the racemic mixture followed by diastereomeric resolution to obtain the pure S isomer. The process consumes a lot of solvents and chemicals. We have evaluated a biocatalytic cleaner approach for asymmetric hydrolysis of racemic clopidogrel. Initial screening of a selected number of hydrolases showed only one enzyme EST to exhibit activity and selectivity towards the desired stereoisomer. As the crude EST is a mixture of several isoenzymes, a homology model of EST-1 was used in molecular dynamic simulations to study the interaction of the enzyme with R and S isomers of clopidogrel. Analysis of the geometric hindrances of the tetrahedral intermediates revealed a potential site for mutagenesis in order to improve the activity and the selectivity. Single point mutation showed dramatic increase in activity and inversion of the enantioselectivity (400 fold change in E value).

Keywords: biocatalysis, biotechnology, enzyme, protein engineering, molecular modeling

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Authors: Sakshi Tomar, Renu Chadha

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Cocrystallization comprises a selective route to the intensive design of pharmaceutical products with desired physiochemical and pharmacokinetic properties. The present study is focused on the preparation, characterization, and evaluation of etodolac (ET) co-crystals with coformers nicotinamide (ETNI) and Glutaric acid (ETGA), using cocrystallization approach. Preliminarily examination of the prepared co-crystal was done by differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FT-IR), powder X-ray diffraction (PXRD). DSC thermographs of ETNI and ETGA cocrystals showed single sharp melting endotherms at 144°C and 135°C, respectively, which were different from the melting of drugs and coformers. FT-IR study points towards carbonyl-acid interaction sandwiched between the involving molecules. The emergence of new peaks in the PXRD pattern confirms the formation of new crystalline solid forms. Both the cocrystals exhibited better apparent solubility, and 3.8-5.0 folds increase in IDR were established, as compared to pure etodolac. Evaluations of these solid forms were done using anti-osteoarthritic activities. All the results indicate that etodolac cocrystals possess better anti-osteoarthritic efficacy than free drug. Thus loom of cocrystallization has been found to be a viable approach to resolve the solubility and bioavailability issues that circumvent the use of potential antiosteoarthritic molecules.

Keywords: bioavailability, etodolac, nicotinamide, osteoarthritis

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Authors: Mrinal Jana, Geetanjali Panda

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In this paper a methodology is developed to solve a nonlinear fractional programming problem in which the coefficients of the objective function and constraints are interval parameters. This model is transformed into a general optimization problem and relation between the original problem and the transformed problem is established. Finally the proposed methodology is illustrated through a numerical example.

Keywords: fractional programming, interval valued function, interval inequalities, partial order relation

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Authors: Nahian Salsabeel, Faria Leera

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—“Whoever controls the Indian Ocean, dominates Asia. This ocean is the key to the seven seas. In the 21st century, the destiny of the world will be decided on its waters” -Alfred Mahan South Asia is increasingly becoming a hub for international politics. Numerous ventures are taking place in the strategic region. Of them, the most prominent is the Belt and Road Initiative (BRI). Originating from the concept of ancient Silk Route, the Chinese Xi Jin Ping regime looks to reestablish the vast connectivity project to connect the world through infrastructure and trade. On the other hand, the US, teamed up with India, Australia and Japan, thereby forming the Quad, have launched their own foreign policy, the Indo-Pacific Strategy. The ambitious 21st century initiative for the development of maritime trade, security and governance focuses critical importance to the Indo-Pacific region, especially to South Asia. Against the backdrop of contemporary political scenario, both the Quad and China airs to establish their own footprint across the region through respective mega projects, the Indo-Pacific Strategy and the BRI. This research employs a comparative case study research method, using a secondary research design. The paper looks at the variety of opportunities and challenges posed by the BRI and the Indo Pacific, and gives the comparative study on both ends.

Keywords: BRI, Foreign Policy, Indo-Pacific, South Asia

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Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Oriol Gomis Bellmunt, Vinicius Albernaz Lacerda Freitas

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The use of distributed and renewable sources in power systems has grown significantly, recently. One the most popular sources are wind farms which have grown massively. However, ¬wind farms are connected to the grid, this can cause problems such as reduced voltage stability, frequency fluctuations and reduced dynamic stability. Variable speed generators (asynchronous) are used due to the uncontrollability of wind speed specially Doubley Fed Induction Generators (DFIG). The most important disadvantage of DFIGs is its sensitivity to voltage drop. In the case of faults, a large volume of reactive power is induced therefore, use of FACTS devices such as SVC and STATCOM are suitable for improving system output performance. They increase the capacity of lines and also passes network fault conditions. In this paper, in addition to modeling the reactive power control system in a DFIG with converter, FACTS devices have been used in a DFIG wind turbine to improve the stability of the power system containing two synchronous sources. In the following paper, recent optimal control systems have been designed to minimize fluctuations caused by system disturbances, for FACTS devices employed. For this purpose, a suitable method for the selection of nine parameters for MPSH-phase-post-phase compensators of reactive power compensators is proposed. The design algorithm is formulated ¬¬as an optimization problem searching for optimal parameters in the controller. Simulation results show that the proposed controller Improves the stability of the network and the fluctuations are at desired speed.

Keywords: renewable energy sources, optimization wind power plant, stability, reactive power compensator, double-feed induction generator, optimal control, genetic algorithm

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

Procedia PDF Downloads 455