Search results for: Coulombic efficiency

Authors: Muhlisin, Moh. Sofyan Budiarto

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Corporate social responsibility (CSR) initiatives based on charity and philanthropy have not alleviated many sustainable environmental issues, particularly in industrial towns. The collaborative governance strategy is seen to be an option for resolving difficulties of coordination and communication between businesses, the government, and the community so that the goals of urban environmental management can be met via collaborative efforts. The purpose of this research is to identify the different forms of environmental CSR implementation by corporate entities and to create a CSR collaborative governance model in environmental management. This qualitative investigation was carried out in 2020 in Cilegon City, one of Indonesia’s industrial cities. To investigate their support, a total of 20 informants from three stakeholder groups, namely the government, corporate entities, and the community, were questioned. According to the study’s findings, cleaner production, eco-office, energy and natural resource conservation, waste management, renewable energy, climate change adaptation, and environmental education are all examples of CSR application in the environmental sector. The environmental potential of CSR implementation is to create collaborative governance. The role of business entities in providing the beginning circumstances is critical, while the government offers facilitative leadership and the CSR forum launches institutional design. These three factors are crucial to the efficiency of collaborative governance in industrial cities' environmental management.

Keywords: collaborative governance, CSR forum, environmental CSR, industrial city

Procedia PDF Downloads 87

Authors: Babak Safaei, A. M. Fattahi

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In the present study we have investigated axial buckling characteristics of nanocomposite beams reinforced by single-walled carbon nanotubes (SWCNTs). Various types of beam theories including Euler-Bernoulli beam theory, Timoshenko beam theory and Reddy beam theory were used to analyze the buckling behavior of carbon nanotube-reinforced composite beams. Generalized differential quadrature (GDQ) method was utilized to discretize the governing differential equations along with four commonly used boundary conditions. The material properties of the nanocomposite beams were obtained using molecular dynamic (MD) simulation corresponding to both short-(10,10) SWCNT and long-(10,10) SWCNT composites which were embedded by amorphous polyethylene matrix. Then the results obtained directly from MD simulations were matched with those calculated by the mixture rule to extract appropriate values of carbon nanotube efficiency parameters accounting for the scale-dependent material properties. The selected numerical results were presented to indicate the influences of nanotube volume fractions and end supports on the critical axial buckling loads of nanocomposite beams relevant to long- and short-nanotube composites.

Keywords: nanocomposites, molecular dynamics simulation, axial buckling, generalized differential quadrature (GDQ)

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Authors: Dimassi Wissem

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In this work, we investigate the effect of combination between the porous silicon (PS) layer passivized with Lithium Bromide (LiBr) and grooving of grain boundaries (GB) in multi crystalline silicon. The grain boundaries were grooved in order to reduce the area of these highly recombining regions. Using optimized conditions, grooved GB's enable deep phosphorus diffusion and deep metallic contacts. We have evaluated the effects of LiBr on the surface properties of porous silicon on the performance of silicon solar cells. The results show a significant improvement of the internal quantum efficiency, which is strongly related to the photo-generated current. We have also shown a reduction of the surface recombination velocity and an improvement of the diffusion length after the LiBr process. As a result, the I–V characteristics under the dark and AM1.5 illumination were improved. It was also observed a reduction of the GB recombination velocity, which was deduced from light-beam-induced-current (LBIC) measurements. Such grooving in multi crystalline silicon enables passivization of GB-related defects. These results are discussed and compared to solar cells based on untreated multi crystalline silicon wafers.

Keywords: Multicrystalline silicon, LiBr, porous silicon, passivation

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Authors: Kwame B. O. Amoah

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This paper focuses on retrofitting an old existing office building to a net-zero energy building (NZEB). An existing small office building in Melbourne, Florida, was chosen as a case study to integrate state-of-the-art design strategies and energy-efficient building systems to improve building performance and reduce energy consumption. The study aimed to explore possible ways to maximize energy savings and renewable energy generation sources to cover the building's remaining energy needs necessary to achieve net-zero energy goals. A series of retrofit options were reviewed and adopted with some significant additional decision considerations. Detailed processes and considerations leading to zero energy are well documented in this study, with lessons learned adequately outlined. Based on building energy simulations, multiple design considerations were investigated, such as emerging state-of-the-art technologies, material selection, improvements to the building envelope, optimization of the HVAC, lighting systems, and occupancy loads analysis, as well as the application of renewable energy sources. The comparative analysis of simulation results was used to determine how specific techniques led to energy saving and cost reductions. The research results indicate this small office building can meet net-zero energy use after appropriate design manipulations and renewable energy sources.

Keywords: energy consumption, building energy analysis, energy retrofits, energy-efficiency

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Authors: Cheng-Jhe Lee, Chiun-Chieh Hsu

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Due to the rapid development of the Internet and the increased availability of digital documents, the excessive information on the Internet has led to information overflow problem. In order to solve these problems for effective information retrieval, document clustering in text mining becomes a popular research topic. Clustering is the unsupervised classification of data items into groups without the need of training data. Many conventional document clustering methods perform inefficiently for large document collections because they were originally designed for relational database. Therefore they are impractical in real-world document clustering and require special handling for high dimensionality and high volume. We propose the FIHC (Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering, where the intuition of FIHC is that there exist some common words for each cluster. FIHC uses such words to cluster documents and builds hierarchical topic tree. In this paper, we combine FIHC algorithm with ontology to solve the semantic problem and mine the meaning behind the words in documents. Furthermore, we use the closed frequent itemsets instead of only use frequent itemsets, which increases efficiency and scalability. The experimental results show that our method is more accurate than those of well-known document clustering algorithms.

Keywords: FIHC, documents clustering, ontology, closed frequent itemset

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Authors: Artur Tyliszczak, Ewa Szymanek, Maciej Marek

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Flow through granular materials is important to a vast array of industries, for instance in construction industry where granular layers are used for bulkheads and isolators, in chemical engineering and catalytic reactors where large surfaces of packed granular beds intensify chemical reactions, or in energy production systems, where granulates are promising materials for heat storage and heat transfer media. Despite the common usage of granulates and extensive research performed in this field, phenomena occurring between granular solid elements or between solids and fluid are still not fully understood. In the present work we analyze the heat exchange process between the flowing medium (gas, liquid) and solid material inside the granular layers. We consider them as a composite of isolated solid elements and inter-granular spaces in which a gas or liquid can flow. The structure of the layer is controlled by shapes of particular granular elements (e.g., spheres, cylinders, cubes, Raschig rings), its spatial distribution or effective characteristic dimension (total volume or surface area). We will analyze to what extent alteration of these parameters influences on flow characteristics (turbulent intensity, mixing efficiency, heat transfer) inside the layer and behind it. Analysis of flow inside granular layers is very complicated because the use of classical experimental techniques (LDA, PIV, fibber probes) inside the layers is practically impossible, whereas the use of probes (e.g. thermocouples, Pitot tubes) requires drilling of holes inside the solid material. Hence, measurements of the flow inside granular layers are usually performed using for instance advanced X-ray tomography. In this respect, theoretical or numerical analyses of flow inside granulates seem crucial. Application of discrete element methods in combination with the classical finite volume/finite difference approaches is problematic as a mesh generation process for complex granular material can be very arduous. A good alternative for simulation of flow in complex domains is an immersed boundary-volume penalization (IB-VP) in which the computational meshes have simple Cartesian structure and impact of solid objects on the fluid is mimicked by source terms added to the Navier-Stokes and energy equations. The present paper focuses on application of the IB-VP method combined with large eddy simulation (LES). The flow solver used in this work is a high-order code (SAILOR), which was used previously in various studies, including laminar/turbulent transition in free flows and also for flows in wavy channels, wavy pipes and over various shape obstacles. In these cases a formal order of approximation turned out to be in between 1 and 2, depending on the test case. The current research concentrates on analyses of the flows in dense granular layers with elements distributed in a deterministic regular manner and validation of the results obtained using LES-IB method and body-fitted approach. The comparisons are very promising and show very good agreement. It is found that the size, number of elements and their distribution have huge impact on the obtained results. Ordering of the granular elements (or lack of it) affects both the pressure drop and efficiency of the heat transfer as it significantly changes mixing process.

Keywords: granular layers, heat transfer, immersed boundary method, numerical simulations

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Authors: Mengjie Zhou

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Under the rapid promotion of digital logistics, the old consumption space in cities is undergoing profound transformation and reconstruction. This article systematically analyzes the impact of digital logistics on existing consumer spaces in cities and how these spaces can adapt to and lead this change through distinct ‘spatial production’ models. The digital transformation of the logistics industry has significantly improved logistics efficiency and service quality while also putting forward new requirements for the form and function of consumer space. In this process, the old consumption space in cities not only faces the trend of material consumption transforming into spiritual consumption but also needs to face profound changes in consumer behavior patterns. Taking Fengying Xili in Changsha as an empirical case, this article explores in detail how it successfully transformed from a traditional consumption space to a modern cultural consumption space by introducing new business formats, optimizing spatial layout, and improving service quality while preserving its historical heritage. This case not only provides valuable practical experience for the transformation of old urban consumption spaces but also demonstrates the feasibility and potential of the new model of ‘spatial production’.

Keywords: digital logistics, urban consumption space, space production, urban renewal

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Authors: Olayinka Oduwole, Steve Sheard

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The magnetic separation of biological cells using super-magnetic beads has been used widely for various bioassays. These bioassays can further be integrated with other laboratory components to form a biosensor which can be used for cell sorting, mixing, purification, transport, manipulation etc. These bio-sensing applications have also been facilitated by the wide availability of magnetic beads which range in size and magnetic properties produced by different manufacturers. In order to improve the efficiency and separation capabilities of these biosensors, it is important to determine the magnetic force induced velocities and interaction of beads within the magnetic field; this will help biosensor users choose the desired magnetic bead for their specific application. This study presents for the first time the interaction between a pair of different sized super-paramagnetic beads suspended in a static fluid moving within a uniform magnetic field using a modified finite-time-finite-difference scheme. A captured video was used to record the trajectory pattern and a good agreement was obtained between the simulated trajectories and the video data. The model is, therefore, a good approximation for predicting the velocities as well as the interaction between various magnetic particles which differ in size and magnetic properties for bio-sensing applications requiring a low concentration of magnetic beads.

Keywords: biosensor, magnetic field, magnetic separation, super-paramagnetic bead

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Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Djaafar Fatiha, Ghalem Bachir, Hadri Bagdad

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We studied mainly the influence of temperature, thickness, molar fraction and the doping of the various layers (emitter, base, BSF and window) on the performances of a photovoltaic solar cell. In a first stage, we optimized the performances of the InGaP/GaAs dual-junction solar cell while varying its operation temperature from 275°K to 375 °K with an increment of 25°C using a virtual wafer fabrication TCAD Silvaco. The optimization at 300 °K led to the following result: Icc =14.22 mA/cm2, Voc =2.42V, FF=91.32 %, η= 22.76 % which is close with those found in the literature. In a second stage ,we have varied the molar fraction of different layers as well their thickness and the doping of both emitters and bases and we have registered the result of each variation until obtaining an optimal efficiency of the proposed solar cell at 300°K which was of Icc=14.35mA/cm2,Voc=2.47V,FF=91.34,and η=23.33% for In(1-x)Ga(x)P molar fraction( x=0.5).The elimination of a layer BSF on the back face of our cell, enabled us to make a remarkable improvement of the short-circuit current (Icc=14.70 mA/cm2) and a decrease in open circuit voltage Voc and output η which reached 1.46V and 11.97% respectively. Therefore, we could determine the critical parameters of the cell and optimize its various technological parameters to obtain the best performance for a dual junction solar cell .This work opens the way with new prospects in the field of the photovoltaic one. Such structures will thus simplify the manufacturing processes of the cells; will thus reduce the costs while producing high outputs of photovoltaic conversion.

Keywords: modeling, simulation, multijunction, optimization, Silvaco ATLAS

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: Muhammad Awais, Wei Li, Anjum Munir

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Biomass gasification is a process of converting solid biomass ingredients into a combustible gas which can be used in electricity generation. Regardless of their applications in many fields, biomass gasification technology is still facing many cleaning issues of syngas. Tar production in biomass gasification process is one of the biggest challenges for this technology. The aimed of this study is to evaluate the tar contents in syngas produced from wood chips, corn cobs, coconut shells and mixture of corn cobs and wood chips as biomass fuel and tar removal efficiency of different cleaning units integrated with gassifier. Performance of different cleaning units, i.e., cyclone separator, wet scrubber, biomass filter, and auxiliary filter was tested under two biomass fuels. Results of this study indicate that wood chips produced less tar of 1736 mg/Nm³ as compared to corn cobs which produced tor 2489 mg/Nm³. It is also observed that coconut shells produced a high amount of tar. It was observed that when wood chips were used as a fuel, syngas tar contents were reduced from 6600 to 112 mg/Nm³ while in case of corn cob, they were reduced from 7500 mg/Nm³ to 220 mg/Nm³. Overall tar removal efficiencies of cyclone separator, wet scrubber, biomass filter, and auxiliary filter was 72%, 63%, 74%, 35% respectively.

Keywords: biomass, gasification, tar, cleaning system, biomass filter

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Authors: Arifa Batool, Ghulam Hussain Bhatti, Syed Mujtaba Shah

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Inorganic n-type (TiO2, CdO) and p-type (NiO, CuO) metal oxide nanoparticles were synthesized by a facile wet chemical method at room temperature. The morphological, compositional, structural and optical properties were investigated by scanning electron microscopy, energy dispersive X-ray spectroscopy, FT-IR, XRD analysis, UV/Visible and fluorescence spectroscopy. All semiconducting nanoparticles were photosensitized with Ru (II) based Z907 dye in ethanol solvent by grafting. Grafting of dye on the surface of nanoparticles was confirmed by UV/Visible and FT-IR spectroscopy. The synthesized photo-active nanohybrid was thoroughly blended with P3HT, a solid electrolyte and I-V measurements under solar stimulated radiations 1000 W/m2 (AM 1.5) were recorded. Maximum incident photon to current conversion efficiency (IPCE) of 0.9% was achieved with dye functionalized Z907-TiO2 hybrid, IPCE of 0.72% was achieved with bulk-heterojunction of TiO2-Z907-CuO and IPCE of 0.68% was attained with nanocomposite of TiO2-CdO. TiO2 based Solar cells have maximum Jscvalue i.e.4.63 mA/cm2. Dye-functionalized TiO2-based photovoltaic devices were found more efficient than the reference device but the morphology of the device was a major check in progress.

Keywords: solar cell, bulk heterojunction, nanocomposites, photosensitization, dye sensitized solar cell

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Authors: Polycarpe Feussi

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Globalization, technological and customer increasing changes, amongst other drivers, result in higher levels of uncertainty and unpredictability for organizations. In order for organizations to cope with the uncertain and fast-changing economic and business environment, these organizations need to innovate in order to achieve flexibility. In simple terms, the organizations must develop strategies leading to the ability of these organizations to provide horizontal information connections across the supply chain to create and deliver products that meet customer needs by synchronization of customer demands with product creation. The generated information will create efficiency and effectiveness throughout the whole supply chain regarding production, storage, and distribution, as well as eliminating redundant activities and reduction in response time. In an integrated supply chain, spanning activities include coordination with distributors and suppliers. This paper explains how through postponement strategies, flexibility can be achieved in an organization. In order to achieve the above, a thorough literature review was conducted via the search of online websites that contains material from scientific journal data-bases, articles, and textbooks on the subject of postponement and flexibility. The findings of the research are found in the last part of the paper. The first part introduces the concept of postponement and its importance in supply chain management. The second part of the paper provides the methodology used in the process of writing the paper.

Keywords: postponement strategies, supply chain management, flexibility, logistics

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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: Han Longxiang

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In the process of treating industrial oily wastewater with complex components, the traditional treatment methods (flotation, coagulation, microwave heating, etc.) often produce high operating costs, secondary pollution, and other problems. In order to solve these problems, the materials with high flux and stability applied to surfactant-stabilized emulsions separation have gained huge attention in the treatment of oily wastewater. Nevertheless, four stable oil-in-water emulsions can be formed due to different surfactants (surfactant-free, anionic surfactant, cationic surfactant, and non-ionic surfactant), and the previous advanced materials can only separate one or several of them, cannot effectively separate in one step. Herein, a facile synthesis method of graphene-based multilevel filter materials (GMFM) which can efficiently separate the oil-in-water emulsions stabilized with different surfactants only through its gravity. The prepared materials with high stability of 20 cycles show a high flux of ~ 5000 L m-2 h-1 with a high separation efficiency of > 99.9 %. GMFM can effectively separate the emulsion stabilized by mixed surfactants and oily wastewater from factories. The results indicate that the GMFM have a wide range of applications in oil-in-water emulsions separation in industry and environmental science.

Keywords: emulsion, filtration, graphene, one-step

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Authors: M. Merabet-Khelassi, Z. Houiene, L. Aribi-Zouioueche, O. Riant

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Lipases (EC.3.1.1.3) are efficient biotools widely used for their remarkable chemo-, regio- and enantio-selectivity, especially, in kinetic resolution of racemates. They offer access to a large panel of enantiopure building blocks, such as secondary benzylic alcohols, commonly used as synthetic intermediates in pharmaceutical and agrochemical industries. Due to the stability of lipases in both water and organic solvents poor in water, they are able to catalyze both transesterifications of arylalkylcarbinols and hydrolysis of their corresponding acetates. The use of enzymatic hydrolysis in aqueous media still limited. In this presentation, we expose a practical methodology for the preparation of optically enriched acetates using a Candida antarctica lipase B-catalyzed hydrolysis in non-aqueous media in the presence of alkaline carbonate salts. The influence of several parameters which can intervene on the enzymatic efficiency such as the impact of the introduction of the carbonates salts, its amount and the nature of the alkaline earth metal are discussed. The obtained results show that the use of sodium carbonate with CAL-B enhances drastically both reactivity and selectivity of this immobilized lipase. In all cases, the resulting alcohols and remaining acetates are obtained in high ee values (up to > 99 %), and the selectivities reach (E > 500).

Keywords: alkaline-hydrolysis, enzymatic kinetic resolution, lipases, arylalkylcarbinol, non-aqueous media

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Authors: Awatef Chniguir, Tarek Farah, Zouhair Ben Jemaa, Safya Belguith

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Optimal routing allows minimizing energy consumption in wireless sensor networks (WSN). Clustering has proven its effectiveness in organizing WSN by reducing channel contention and packet collision and enhancing network throughput under heavy load. Therefore, nowadays, with the emergence of the Internet of Things, heterogeneity is essential. Stable election protocol (SEP) that has increased the network stability period and lifetime is the first clustering protocol for heterogeneous WSN. SEP and its descendants, namely SEP, Threshold Sensitive SEP (TSEP), Enhanced TSEP (ETSSEP) and Current Energy Allotted TSEP (CEATSEP), were studied. These algorithms’ performance was evaluated based on different metrics, especially first node death (FND), to compare their stability. Simulations were conducted on the MATLAB tool considering two scenarios: The first one demonstrates the fraction variation of advanced nodes by setting the number of total nodes. The second considers the interpretation of the number of nodes while keeping the number of advanced nodes permanent. CEATSEP outperforms its antecedents by increasing stability and, at the same time, keeping a low throughput. It also operates very well in a large-scale network. Consequently, CEATSEP has a useful lifespan and energy efficiency compared to the other routing protocol for heterogeneous WSN.

Keywords: clustering, heterogeneous, stability, scalability, IoT, WSN

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Authors: M. Zake, I. Barmina, R. Valdmanis, A. Kolmickovs

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Experimental investigations of the DC electric field effect on thermal decomposition of biomass, formation of the axial flow of volatiles (CO, H2, CxHy), mixing of volatiles with swirling airflow at low swirl intensity (S ≈ 0.2-0.35), their ignition and on formation of combustion dynamics are carried out with the aim to understand the mechanism of electric field influence on biomass gasification, combustion of volatiles and heat energy production. The DC electric field effect on combustion dynamics was studied by varying the positive bias voltage of the central electrode from 0.6 kV to 3 kV, whereas the ion current was limited to 2 mA. The results of experimental investigations confirm the field-enhanced biomass gasification with enhanced release of volatiles and the development of endothermic processes at the primary stage of thermochemical conversion of biomass determining the field-enhanced heat energy consumption with the correlating decrease of the flame temperature and heat energy production at this stage of flame formation. Further, the field-enhanced radial expansion of the flame reaction zone correlates with a more complete combustion of volatiles increasing the combustion efficiency by 3 % and decreasing the mass fraction of CO, H2 and CxHy in the products, whereas by 10 % increases the average volume fraction of CO2 and the heat energy production downstream the combustor increases by 5-10 %

Keywords: biomass, combustion, electrodynamic control, gasification

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Authors: Mahdi Motahari, Mojtaba Farzaneh, Ebrahim Sepidbar

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Tracking of moving and flying targets is one of the most important issues in image processing topic. Estimating of trajectory of desired object in short-term and long-term scale is more important than tracking of moving and flying targets. In this paper, a new way of identifying and estimating of future trajectory of a moving ball in long-term scale is estimated by using synthesis and interaction of image processing algorithms including noise removal and image segmentation, Kalman filter algorithm in order to estimating of trajectory of ball in football game in short-term scale and intelligent adaptive neuro-fuzzy algorithm based on time series of traverse distance. The proposed system attain more than 96% identify accuracy by using aforesaid methods and relaying on aforesaid algorithms and data base video in format of synthesis and interaction. Although the present method has high precision, it is time consuming. By comparing this method with other methods we realize the accuracy and efficiency of that.

Keywords: tracking, signal processing, moving targets and flying, artificial intelligent systems, estimating of trajectory, Kalman filter

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Authors: Andrew R. Winters, Gregor J. Gassner

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A high-order numerical magentohydrodynamics (MHD) solver built upon a non-linear entropy stable numerical flux function that supports eight traveling wave solutions will be described. The method is designed to treat the divergence-free constraint on the magnetic field in a similar fashion to a hyperbolic divergence cleaning technique. The solver is especially well-suited for flows involving strong discontinuities due to its strong stability without the need to enforce artificial low density or energy limits. Furthermore, a new formulation of the numerical algorithm to guarantee positivity of the pressure during the simulation is described and presented. By construction, the solver conserves mass, momentum, and energy and is entropy stable. High spatial order is obtained through the use of a third order limiting technique. High temporal order is achieved by utilizing the family of strong stability preserving (SSP) Runge-Kutta methods. Main attributes of the solver are presented as well as details on an implementation of the new solver into the multi-physics, multi-scale simulation code FLASH. The accuracy, robustness, and computational efficiency is demonstrated with a variety of numerical tests. Comparisons are also made between the new solver and existing methods already present in FLASH framework.

Keywords: entropy stability, finite volume scheme, magnetohydrodynamics, pressure positivity

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Authors: Wu Defu, Kiefer Chiam, Yang Kin Seng

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The planning of geological survey works is an iterative process which involves planner, geologist, civil engineer and other stakeholders, who perform different roles and have different points of view. Traditionally, the team used paper maps or CAD drawings to present the proposal which is not an efficient way to present and share idea on the site investigation proposal such as sitting of borehole location or seismic survey lines. This paper focuses on how a GIS approach can be utilised to develop a web-based system to support decision making process in the planning of geological survey works and also to plan site activities carried out by Singapore Geological Office (SGO). The authors design a framework of building an interactive web-based GIS system, and develop a prototype, which enables the users to obtain rapidly existing geological information and also to plan interactively borehole locations and seismic survey lines via a web browser. This prototype system is used daily by SGO and has shown to be effective in increasing efficiency and productivity as the time taken in the planning of geological survey works is shortened. The prototype system has been developed using the ESRI ArcGIS API 3.7 for Flex which is based on the ArcGIS 10.2.1 platform.

Keywords: engineering geology, flex, geological survey planning, geoscience, GIS, site investigation, WebGIS

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Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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Authors: Hee Soo Kim, Ha Young Kyung

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Happiness and pleasure are a result of dopamine, oxytocin, serotonin, and endorphin levels in the body. In order to increase the four neurochemical levels, it is important to associate daily activities with its corresponding neurochemical releases. This includes setting goals, maintaining social relationships, laughing frequently, and exercising regularly. The likelihood of experiencing happiness increases when all four neurochemicals are released at the optimal level. The achievement of happiness is important because it increases healthiness, productivity, and the ability to overcome adversity. To process emotions, electrical brain waves, brain structure, and neurochemicals must be analyzed. This research uses Chemcraft and Avogadro to determine the theoretical and chemical properties of the four neurochemical molecules. Each neurochemical molecule’s thermodynamic stability is calculated to observe the efficiency of the molecules. The study found that among dopamine, oxytocin, serotonin, alpha-, beta-, and gamma-endorphin, beta-endorphin has the lowest optimized energy of 388.510 kJ/mol. Beta-endorphin, a neurotransmitter involved in mitigating pain and stress, is the most thermodynamically stable and efficient molecule that is involved in the process of happiness. Through examining such properties of happiness neurotransmitters, the science of happiness is better understood.

Keywords: happiness, neurotransmitters, positive psychology, dopamine, oxytocin, serotonin, endorphins

Procedia PDF Downloads 154

Authors: Farid Benkaci-Alia, Abdelhamid Neggada, Sophie Laurentb

Abstract:

A new extraction method of polyphenols from honey using a biodegradable resin was developed and compared with the common commercial resin amberlite XAD2. For this purpose, three honey samples of Algerian origin were selected for the different physico-chemical and biochemical parameters study. After extraction of the target compounds by both resins, the polyphenol content was determined, the antioxidant activity was tested, and LC-MS analyses were performed for identification and quantification. The results showed that physico-chemical and biochemical parameters meet the norms of the International Honey commission, and the H1 sample seemed to be of high quality. The optimal conditions of extraction by biodegradable resin were a pH of 3, an adsorption dose of 40 g/L, a contact time of 50 min, an extraction temperature of 60°C and no stirring. The regeneration and reuse number of both resins was three cycles. The polyphenol contents demonstrated a higher extraction efficiency of biosorbent than of XAD2, especially in H1. LC-MS analyses allowed for the identification and quantification of fifteen compounds in the different honey samples extracted using both resins and the most abundant compound was 3,4,5-trimethoxybenzoic acid. In addition, the biosorbent extracts showed stronger antioxidant activities than the XAD2 extracts.

Keywords: extraction, polyphénols, biosorbent, resin amberlite, HPLC-MS

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Authors: Mohammadreza Heydariazad

Abstract:

Productivity growth of wind energy as a clean source needed to achieve improved strategy in production and transmission and management of wind resources in order to increase quality of power and reduce costs. New technologies based on power converters that cause changing turbine speed to suit the wind speed blowing turbine improve extraction efficiency power from wind. This article introduces variable speed wind turbines and optimization of power, and presented methods to use superconducting inductor in the composition of power converter and is proposed the dc measurement for the wind farm and especially is considered techniques available to them. In fact, this article reviews mechanisms and function, changes of wind speed turbine according to speed control strategies of various types of wind turbines and examines power possible transmission and ac from producing location to suitable location for a strong connection integrating wind farm generators, without additional cost or equipment. It also covers main objectives of the dynamic control of wind turbines, and the methods of exploitation and the ways of using it that includes the unique process of these components. Effective algorithm is presented for power control in order to extract maximum active power and maintains power factor at the desired value.

Keywords: wind energy, generator, superconducting inductor, wind turbine power

Procedia PDF Downloads 327

Authors: Reynaldo Esquivel, Pedro Hernandez, Aaron Martinez-Higareda, Sergio Tena-Cano, Enrique Alvarez-Ramos, Armando Lucero-Acuna

Abstract:

Stimuli-responsive nanomaterials play an essential role in loading, transporting and well-distribution of anti-cancer compounds in the cellular surroundings. The outstanding properties as the Lower Critical Solution Temperature (LCST), hydrolytic cleavage and protonation/deprotonation cycle, govern the release and delivery mechanisms of payloads. In this contribution, we experimentally determine the load efficiency and release of antineoplastic Vincristine Sulfate into PNIPAM-Interpenetrated-Chitosan (PIntC) nanoparticles. Structural analysis was performed by Fourier Transform Infrared Spectroscopy (FT-IR) and Proton Nuclear Magnetic Resonance (1HNMR). ζ-Potential (ζ) and Hydrodynamic diameter (DH) measurements were monitored by Electrophoretic Mobility (EM) and Dynamic Light scattering (DLS) respectively. Mathematical analysis of the release pharmacokinetics reveals a three-phase model above LCST, while a monophasic of Vincristine release model was observed at 32 °C. Cytotoxic essays reveal a noticeable enhancement of Vincristine effectiveness at low drug concentration on HeLa cervix cancer and MDA-MB-231 breast cancer.

Keywords: nanoparticles, vincristine, drug delivery, PNIPAM

Procedia PDF Downloads 156

Authors: Nayden Chivarov, Denis Chikurtev, Kaloyan Yovchev, Nedko Shivarov

Abstract:

This paper represents methods for improving the efficiency and precision of service mobile robot. This robot is used for increasing the quality of life of elderly and disabled people. The key concept of the proposed Intelligent Service Mobile Robot is its easier adaptability to achieve services for a wide range of Elderly or Disabled Person’s needs, by performing different tasks for supporting Elderly or Disabled Persons care. We developed robot autonomous navigation and computer vision systems in order to recognize different objects and bring them to the people. Web based user interface is developed to provide easy access and tele-control of the robot by any device through the internet. In this study algorithms for object recognition and localization are proposed for providing successful object recognition and accuracy in the positioning. Different methods for sending movement commands to the mobile robot system are proposed and evaluated. After executing some experiments to show the results of the research, we can summarize that these systems and algorithms provide good control of the service mobile robot and it will be more useful to help the elderly and disabled persons.

Keywords: service robot, mobile robot, autonomous navigation, computer vision, web user interface, ROS

Procedia PDF Downloads 339

Authors: Muhammad Raqib Rasul, Tavga Sulaiman Rashid

Abstract:

Fertilization increases efficiency and obtains better quality of product recovery in agricultural activities. However, fertilizer consumption increased exponentially throughout the world, causing severe environmental problems. Biofertilizers can be a practical approach to minimize chemical fertilizer sources and ultimately develop soil fertility. This study was carried out to isolate, identify and characterize bacteria from medicinal plant (Rumex tuberosus L. and Verbascum sp.) rhizosphere for in vivo screening. 25 bacterial isolates were isolated and several biochemical tests were performed. Two isolates that were positive for most biochemical tests were chosen for the field experiment. The isolates were identified as Go1 Alcaligenes faecalis (Accession No. OP001725) and T11 (Bacillus sp.) based on the 16S rRNA sequence analysis that was compared with related bacteria in GenBank database using MEGA 6.1. For the field trial isolate GO1 and T11 (separately and mixed), NPK as a positive control was used. Both isolates increased plant height, chlorophyll content, number of tubers, and tuber’s weight. The results demonstrated that these two isolates of bacteria can potentially replace with chemical fertilizers for potato production.

Keywords: biofertilizer, Bacillus subtilis, Alcaligenes faecalis, potato tubers, in vivo screening

Procedia PDF Downloads 103

Authors: Madhujit Deb, G. R. K. Sastry, R. S. Panua, Rahul Banerjee, P. K. Bose

Abstract:

The present work attempts to investigate the combustion, performance and emission characteristics of an existing single-cylinder four-stroke compression-ignition engine operated in dual-fuel mode with hydrogen as an alternative fuel. Environmental concerns and limited amount of petroleum fuels have caused interests in the development of alternative fuels like hydrogen for internal combustion (IC) engines. In this experimental investigation, a diesel engine is made to run using hydrogen in dual fuel mode with diesel, where hydrogen is introduced into the intake manifold using an LPG-CNG injector and pilot diesel is injected using diesel injectors. A Timed Manifold Injection (TMI) system has been developed to vary the injection strategies. The optimized timing for the injection of hydrogen was 100 CA after top dead center (ATDC). From the study it was observed that with increasing hydrogen rate, enhancement in brake thermal efficiency (BTHE) of the engine has been observed with reduction in brake specific energy consumption (BSEC). Furthermore, Soot contents decrease with an increase in indicated specific NOx emissions with the enhancement of hydrogen flow rate.

Keywords: diesel engine, hydrogen, BTHE, BSEC, soot, NOx

Procedia PDF Downloads 538