Search results for: green solution
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7568

Search results for: green solution

1718 Synthesis of Uio-66 Metal Organic Framework Impregnated Thin-Film Nanocomposite Membrane for the Desalination via Pressure Assisted Osmosis

Authors: Rajesha Kumar Alambi, Mansour Ahmed, Garudachari Bhadrachari, Safiyah Al-Muqahwi, Mansour Al-Rughaib, Jibu P. Thomas

Abstract:

Membrane-based pressure assisted osmosis (PAO) for seawater desalination has the potential to overcome the challenges of forward osmosis technology. PAO technology is gaining interest among the research community to ensure the sustainability of freshwater with a significant reduction in energy. The requirements of PAO membranes differ from the FO membrane; as it needs a slightly higher porous with sufficient mechanical strength to overcome the applied hydraulic pressure. The porous metal-organic framework (MOF) as a filler for the membrane synthesis has demonstrated a great potential to generate new channels for water transport, high selectivity, and reduced fouling propensity. Accordingly, this study is aimed at fabricating the UiO-66 MOF-based thin film nanocomposite membranes with specific characteristics for water desalination by PAO. A PAO test unit manufactured by Trevi System, USA, was used to determine the performance of the synthesized membranes. Further, the synthesized membranes were characterized in terms of morphological features, hydrophilicity, surface roughness, and mechanical properties. The 0.05 UiO-66 loaded membrane produced highest flux of 38L/m2h and with low reverse salt leakage of 2.1g/m²h for the DI water as feed solution and 2.0 M NaCl as draw solutions at the inlet feed pressure of 0.6 MPa. The new membranes showed a good tolerance toward the applied hydraulic pressure attributed to the fabric support used during the membrane synthesis.

Keywords: metal organic framework, composite membrane, desalination, salt rejection, flux

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1717 Devotional Informant and Diagenetic Alterations, Influences of Facies and Fine Kaolinite Formation Migration on Sandstone’ Reservoir Quality, Sarir Formation, Sirt

Authors: Faraj M. Elkhatri, Hana Ellafi

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In recent years, there has been a growing recognition of the potential of marine-based functional foods and combination therapies in promoting a healthy lifestyle and exploring their effectiveness in preventing or treating diseases. The combination of marine bioactive compounds or extracts offers synergistic or enhancement effects through various mechanisms, including multi-target actions, improved bioavailability, enhanced bioactivity, and mitigation of potential adverse effects. Both the green-lipped mussel (GLM) and fucoidan derived from brown seaweed are rich in bioactivities. These two, mussel and fucoidan, have not been previously formulated together. This study aims to combine GLM oil from Perna canaliculus with low molecular weight fucoidan (LMWF) extracted from Undaria pinnatifida to investigate the unique mixture’s anti-inflammatory and antioxidant properties. The cytotoxicity of individual compounds and combinations was assessed using the MTT assay in (THP-1 and RAW264.7) cell lines. The anti-inflammatory activity of mussel-fucoidan was evaluated by treating LPS-stimulated human monocyte and macrophage (THP1-1) cells. Subsequently, the inflammatory cytokines released into the supernatant of these cell lines were quantified via ELISA. Antioxidant activity was determined by using the free radical scavenging assay (DPPH). DPPH assay demonstrated that the radical scavenging activity of the combinations, particularly at concentrations exceeding 1 mg/ml, showed a significantly higher percentage of inhibition when compared to the individual component. This suggests an enhancement effect when the two compounds are combined, leading to increased antioxidant activity. In terms of immunomodulatory activity, the individual compounds exhibited distinct behaviors. GLM oil displayed a higher ability to suppress the cytokine TNF- compared to LMWF. Interestingly, the LMWF fraction, when used individually, did not demonstrate TNF- suppression. However, when combined with GLM, the TNF- suppression (anti-inflammatory) activity of the combination was better than GLM or LWMF alone. This observation underscores the potential for enhancement interactions between the two components in terms of anti-inflammatory properties. This study revealed that each individual compound, LMWF, and GLM, possesses unique and notable bioactivity. The combination of these two individual compounds results in an enhancement effect, where the bioactivity of each is enhanced, creating a superior combination. This suggests that the combination of LMWF and GLM has the potential to offer a more potent and multifaceted therapeutic effect, particularly in the context of antioxidant and anti-inflammatory activities. These findings hold promise for the development of novel therapeutic interventions or supplements that harness the enhancement effects.

Keywords: formation damage, porosity loses, pore throat, quartz cement

Procedia PDF Downloads 57
1716 Key Success Factors and Enterprise Resource Planning Implementation in Higher Education Institutions: Multiple Case Studies of Jordanian Universities

Authors: Abdallah Abu Madi, Dongmei Cao, Alexeis Garcia-Perez, Qile He

Abstract:

The failure of Enterprise Resource Planning (ERP) implementation in higher education institutions (HEIs) worldwide is much higher in comparison to other sectors, such as banking or manufacturing, to our knowledge limited research has been conducted on this issue. To date, prior literature has identified some key success factors (KSFs) mostly either in the domain of information and system (IS) or in the industrial context. However, evidence of ERP implementation in the higher education sector has had little attention in the extant literature. Hence, this paper identifies and categories KSFs of ERP implementation in HEIs. Semi-structured face-to-face interviews were conducted with technicians and managers from three Jordanian HEIs. From these case studies, three new sector- and context-specific KSFs were identified and categorized according to two dimensions: organizational and technical. The first new KSF is the selection of the ERP system, which is an influential factor in the organizational dimension. Results show that an ERP solution that is suitable to one context may be disastrous in another. The second new KSF, which falls under the technical dimension, is the relationship between vendors and HEIs. This must be fair and impartial to enable successful decision-making and thus the achievement of pre-defined goals. Also within the technical dimension is the third factor: in-house maintenance. Once an appropriate system is selected and a strong relationship is established, the ERP system requires continuous maintenance for effective operation. HEIs should ensure that qualified IT support is in place and in-house to avoid excessive running expenses.

Keywords: Enterprise Resource Planning (ERP)implementation, key success factors, higher education institutions, Jordanian higher education

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1715 Revisiting Dispute Resolution Mechanisms in the Southern African Development Community: A Proposal for Synchronization

Authors: Tapiwa Shumba, Nyaradzo D. T. Karubwa

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Dispute resolution is the plinth of regional integration initiatives anchored on the rule of law and compliance with obligations. Without effective and reliable despite resolution mechanisms, it may be difficult to foster deeper integration. Within the Southern African Development Community (SADC) legal and institutional framework exists an apparent recognition that dispute resolution is an integral part of the regional integration. Almost all legal instruments of SADC include some provision for dispute resolution. Institutionally, the somewhat now defunct SADC Tribunal is meant to be the fulcrum for resolving disputes that arise under SADC instruments. However, after a closer analysis of the substance of these legal provisions and the attendant procedural mechanisms for addressing disputes, an argument can be made that dispute resolution in SADC is somewhat scant, fragmented and neglected. In most instruments, the common provision on dispute resolution appears to be a ‘mid-night clause’. In other instruments which have specialised provisions and procedures, questions of practicality and genius cannot be avoided. Worse still there now appears to be a lack of magnanimity between the substantive provisions in various instruments and the role of the transformed Tribunal. This scant, fragmented and neglected dispute resolution system may have an impact on the observance of the rule of law and compliance with obligations in the rules-based SADC system. This all, in turn, has an effect on the common agenda for deeper regional integration. This article seeks to expose this scant, fragmented and neglected SADC dispute resolution system and to propose a harmonised system that addresses these challenges. A ‘one stop shop’ system under a strengthened SADC tribunal is proposed as a responsive solution.

Keywords: regional integration, harmonisation, SADC tribunal, dispute resolution

Procedia PDF Downloads 191
1714 ALEF: An Enhanced Approach to Arabic-English Bilingual Translation

Authors: Abdul Muqsit Abbasi, Ibrahim Chhipa, Asad Anwer, Saad Farooq, Hassan Berry, Sonu Kumar, Sundar Ali, Muhammad Owais Mahmood, Areeb Ur Rehman, Bahram Baloch

Abstract:

Accurate translation between structurally diverse languages, such as Arabic and English, presents a critical challenge in natural language processing due to significant linguistic and cultural differences. This paper investigates the effectiveness of Facebook’s mBART model, fine-tuned specifically for sequence-tosequence (seq2seq) translation tasks between Arabic and English, and enhanced through advanced refinement techniques. Our approach leverages the Alef Dataset, a meticulously curated parallel corpus spanning various domains to capture the linguistic richness, nuances, and contextual accuracy essential for high-quality translation. We further refine the model’s output using advanced language models such as GPT-3.5 and GPT-4, which improve fluency, coherence, and correct grammatical errors in translated texts. The fine-tuned model demonstrates substantial improvements, achieving a BLEU score of 38.97, METEOR score of 58.11, and TER score of 56.33, surpassing widely used systems such as Google Translate. These results underscore the potential of mBART, combined with refinement strategies, to bridge the translation gap between Arabic and English, providing a reliable, context-aware machine translation solution that is robust across diverse linguistic contexts.

Keywords: natural language processing, machine translation, fine-tuning, Arabic-English translation, transformer models, seq2seq translation, translation evaluation metrics, cross-linguistic communication

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1713 X-Ray Diffraction, Microstructure, and Mössbauer Studies of Nanostructured Materials Obtained by High-Energy Ball Milling

Authors: N. Boudinar, A. Djekoun, A. Otmani, B. Bouzabata, J. M. Greneche

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High-energy ball milling is a solid-state powder processing technique that allows synthesizing a variety of equilibrium and non-equilibrium alloy phases starting from elemental powders. The advantage of this process technology is that the powder can be produced in large quantities and the processing parameters can be easily controlled, thus it is a suitable method for commercial applications. It can also be used to produce amorphous and nanocrystalline materials in commercially relevant amounts and is also amenable to the production of a variety of alloy compositions. Mechanical alloying (high-energy ball milling) provides an inter-dispersion of elements through a repeated cold welding and fracture of free powder particles; the grain size decreases to nano metric scale and the element mix together. Progressively, the concentration gradients disappear and eventually the elements are mixed at the atomic scale. The end products depend on many parameters such as the milling conditions and the thermodynamic properties of the milled system. Here, the mechanical alloying technique has been used to prepare nano crystalline Fe_50 and Fe_64 wt.% Ni alloys from powder mixtures. Scanning electron microscopy (SEM) with energy-dispersive, X-ray analyses and Mössbauer spectroscopy were used to study the mixing at nanometric scale. The Mössbauer Spectroscopy confirmed the ferromagnetic ordering and was use to calculate the distribution of hyperfin field. The Mössbauer spectrum for both alloys shows the existence of a ferromagnetic phase attributed to γ-Fe-Ni solid solution.

Keywords: nanocrystalline, mechanical alloying, X-ray diffraction, Mössbauer spectroscopy, phase transformations

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1712 Wettability Properties of Pineapple Leaf Fibers and Banana Pseudostem Fibers Treated by Cold Plasma

Authors: Tatiana Franco, Hugo A. Estupinan

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Banana pseudostem fiber (BPF) and pineapple leaf fiber (PLF) for their excellent mechanical properties and biodegradability characteristics arouse interest in different areas of research. F In tropical regions, where the banana pseudostem and the pineapple leaf are transformed into hard-to-handle solid waste, they can be low-cost raw material and environmentally sustainable in research for composite materials. In terms of functionality of this type of fiber, an open structure would allow the adsorption and retention of organic, inorganic and metallic species. In general, natural fibers have closed structures on their surface with intricate internal arrangements that can be used for the solution of environmental problems and other technological uses, however it is not possible to access their internal structure and sublayers, exposing the fibers in the natural state. An alternative method to chemical and enzymatic treatment are the processes with the plasma treatments, which are known to be clean, economical and controlled. In this type of treatment, a gas contained in a reactor in the form of plasma acts on the fiber generating changes in its structure, morphology and topography. This work compares the effects on fibers of PLF and BPF treated with cold argon plasma, alternating time and current. These fibers are grown in the regions of Antioquia-Colombia. The morphological, compositional and wettability properties of the fibers were analyzed by Raman microscopy, contact angle measurements, scanning electron microscopy (SEM) and atomic force microscopy analysis (AFM). The treatment with cold plasma on PLF and BPF allowed increasing its wettability, the topography and the microstructural relationship between lignin and cellulose.

Keywords: cold plasma, contact angle, natural fibers, Raman, SEM, wettability

Procedia PDF Downloads 156
1711 Aseismic Stiffening of Architectural Buildings as Preventive Restoration Using Unconventional Materials

Authors: Jefto Terzovic, Ana Kontic, Isidora Ilic

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In the proposed design concept, laminated glass and laminated plexiglass, as ”unconventional materials”, are considered as a filling in a steel frame on which they overlap by the intermediate rubber layer, thereby forming a composite assembly. In this way vertical elements of stiffening are formed, capable for reception of seismic force and integrated into the structural system of the building. The applicability of such a system was verified by experiments in laboratory conditions where the experimental models based on laminated glass and laminated plexiglass had been exposed to the cyclic loads that simulate the seismic force. In this way the load capacity of composite assemblies was tested for the effects of dynamic load that was parallel to assembly plane. Thus, the stress intensity to which composite systems might be exposed was determined as well as the range of the structure stiffening referring to the expressed deformation along with the advantages of a particular type of filling compared to the other one. Using specialized software whose operation is based on the finite element method, a computer model of the structure was created and processed in the case study; the same computer model was used for analyzing the problem in the first phase of the design process. The stiffening system based on composite assemblies tested in laboratories is implemented in the computer model. The results of the modal analysis and seismic calculation from the computer model with stiffeners applied showed an efficacy of such a solution, thus rounding the design procedures for aseismic stiffening by using unconventional materials.

Keywords: laminated glass, laminated plexiglass, aseismic stiffening, experiment, laboratory testing, computer model, finite element method

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1710 Optimization of Biomass Production and Lipid Formation from Chlorococcum sp. Cultivation on Dairy and Paper-Pulp Wastewater

Authors: Emmanuel C. Ngerem

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The ever-increasing depletion of the dominant global form of energy (fossil fuels) calls for the development of sustainable and green alternative energy sources such as bioethanol, biohydrogen, and biodiesel. The production of the major biofuels relies on biomass feedstocks that are mainly derived from edible food crops and some inedible plants. One suitable feedstock with great potential as raw material for biofuel production is microalgal biomass. Despite the tremendous attributes of microalgae as a source of biofuel, their cultivation requires huge volumes of freshwater, thus posing a serious threat to commercial-scale production and utilization of algal biomass. In this study, a multi-media wastewater mixture for microalgae growth was formulated and optimized. Moreover, the obtained microalgae biomass was pre-treated to reduce sugar recovery and was compared with previous studies on microalgae biomass pre-treatment. The formulated and optimized mixed wastewater media for biomass and lipid accumulation was established using the simplex lattice mixture design. Based on the superposition approach of the potential results, numerical optimization was conducted, followed by the analysis of biomass concentration and lipid accumulation. The coefficients of regression (R²) of 0.91 and 0.98 were obtained for biomass concentration and lipid accumulation models, respectively. The developed optimization model predicted optimal biomass concentration and lipid accumulation of 1.17 g/L and 0.39 g/g, respectively. It suggested 64.69% dairy wastewater (DWW) and 35.31% paper and pulp wastewater (PWW) mixture for biomass concentration, 34.21% DWW, and 65.79% PWW for lipid accumulation. Experimental validation generated 0.94 g/L and 0.39 g/g of biomass concentration and lipid accumulation, respectively. The obtained microalgae biomass was pre-treated, enzymatically hydrolysed, and subsequently assessed for reducing sugars. The optimization of microwave pre-treatment of Chlorococcum sp. was achieved using response surface methodology (RSM). Microwave power (100 – 700 W), pre-treatment time (1 – 7 min), and acid-liquid ratio (1 – 5%) were selected as independent variables for RSM optimization. The optimum conditions were achieved at microwave power, pre-treatment time, and acid-liquid ratio of 700 W, 7 min, and 32.33:1, respectively. These conditions provided the highest amount of reducing sugars at 10.73 g/L. Process optimization predicted reducing sugar yields of 11.14 g/L on microwave-assisted pre-treatment of 2.52% HCl for 4.06 min at 700 watts. Experimental validation yielded reducing sugars of 15.67 g/L. These findings demonstrate that dairy wastewater and paper and pulp wastewater that could pose a serious environmental nuisance. They could be blended to form a suitable microalgae growth media, consolidating the potency of microalgae as a viable feedstock for fermentable sugars. Also, the outcome of this study supports the microalgal wastewater biorefinery concept, where wastewater remediation is coupled with bioenergy production.

Keywords: wastewater cultivation, mixture design, lipid, biomass, nutrient removal, microwave, Chlorococcum, raceway pond, fermentable sugar, modelling, optimization

Procedia PDF Downloads 41
1709 Nonlinear Finite Element Analysis of Optimally Designed Steel Angelina™ Beams

Authors: Ferhat Erdal, Osman Tunca, Serkan Tas, Serdar Carbas

Abstract:

Web-expanded steel beams provide an easy and economical solution for the systems having longer structural members. The main goal of manufacturing these beams is to increase the moment of inertia and section modulus, which results in greater strength and rigidity. Until recently, there were two common types of open web-expanded beams: with hexagonal openings, also called castellated beams, and beams with circular openings referred to as cellular beams, until the generation of sinusoidal web-expanded beams. In the present research, the optimum design of a new generation beams, namely sinusoidal web-expanded beams, will be carried out and the design results will be compared with castellated and cellular beam solutions. Thanks to a reduced fabrication process and substantial material savings, the web-expanded beam with sinusoidal holes (Angelina™ Beam) meets the economic requirements of steel design problems while ensuring optimum safety. The objective of this research is to carry out non-linear finite element analysis (FEA) of the web-expanded beam with sinusoidal holes. The FE method has been used to predict their entire response to increasing values of external loading until they lose their load carrying capacity. FE model of each specimen that is utilized in the experimental studies is carried out. These models are used to simulate the experimental work to verify of test results and to investigate the non-linear behavior of failure modes such as web-post buckling, shear buckling and vierendeel bending of beams.

Keywords: steel structures, web-expanded beams, angelina beam, optimum design, failure modes, finite element analysis

Procedia PDF Downloads 281
1708 Combining Diffusion Maps and Diffusion Models for Enhanced Data Analysis

Authors: Meng Su

Abstract:

High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

Procedia PDF Downloads 108
1707 Performance Investigation of Thermal Insulation Materials for Walls: A Case Study in Nicosia (Turkish Republic of North Cyprus)

Authors: L. Vafaei, McDominic Eze

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The performance of thermal energy in homes and buildings is a significant factor in terms of energy efficiency of a building. In a large sense, the performance of thermal energy is dependent on many factors of which the amount of thermal insulation is at one end a considerable factor, as likewise the essence of mass and the wall thickness and also the thermal resistance of wall material. This study is aimed at illustrating the different wall system in Turkish Republic of North Cyprus (TRNC), acknowledge the problem and suggest a solution through comparing the effect of thermal radiation two model rooms- L1 (Ytong wall) and L2 (heat insulated wall using stone wool) set up for experimentation. The model room has four face walls. The study consists of two stage, the first test is to access the effect of solar radiation for south facing wall and the second stage is to test the thermal performance of Ytong and heat insulated wall, the effects of climatic condition during winter. The heat insulated wall contains material hollow brick, stone wool, and gypsum while the Ytong wall contains cement concrete, for the outer surface and the inner surface and Ytong stone. The total heat of the wall was determined, 7T-Type thermocouple was used with a data logger system to record the data, temperature change recorded at an interval of 10 minutes. The result obtained was that Ytong wall save more energy than the heat insulated wall at night while heat insulated wall saves energy during the day when intensity is at maximum.

Keywords: heat insulation, hollow bricks, south facing, Ytong bricks wall

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1706 Unsupervised Echocardiogram View Detection via Autoencoder-Based Representation Learning

Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

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Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

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1705 Precoding-Assisted Frequency Division Multiple Access Transmission Scheme: A Cyclic Prefixes- Available Modulation-Based Filter Bank Multi-Carrier Technique

Authors: Ying Wang, Jianhong Xiang, Yu Zhong

Abstract:

The offset Quadrature Amplitude Modulation-based Filter Bank Multi-Carrier (FBMC) system provides superior spectral properties over Orthogonal Frequency Division Multiplexing. However, seriously affected by imaginary interference, its performances are hampered in many areas. In this paper, we propose a Precoding-Assisted Frequency Division Multiple Access (PA-FDMA) modulation scheme. By spreading FBMC symbols into the frequency domain and transmitting them with a precoding matrix, the impact of imaginary interference can be eliminated. Specifically, we first generate the coding pre-solution matrix with a nonuniform Fast Fourier Transform and pick the best columns by introducing auxiliary factors. Secondly, according to the column indexes, we obtain the precoding matrix for one symbol and impose scaling factors to ensure that the power is approximately constant throughout the transmission time. Finally, we map the precoding matrix of one symbol to multiple symbols and transmit multiple data frames, thus achieving frequency-division multiple access. Additionally, observing the interference between adjacent frames, we mitigate them by adding frequency Cyclic Prefixes (CP) and evaluating them with a signal-to-interference ratio. Note that PA-FDMA can be considered a CP-available FBMC technique because the underlying strategy is FBMC. Simulation results show that the proposed scheme has better performance compared to Single Carrier Frequency Division Multiple Access (SC-FDMA), etc.

Keywords: PA-FDMA, SC-FDMA, FBMC, non-uniform fast fourier transform

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1704 A Comparative Study: Influences of Polymerization Temperature on Phosphoric Acid Doped Polybenzimidazole Membranes

Authors: Cagla Gul Guldiken, Levent Akyalcin, Hasan Ferdi Gercel

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Fuel cells are electrochemical devices which convert the chemical energy of hydrogen into the electricity. Among the types of fuel cells, polymer electrolyte membrane fuel cells (PEMFCs) are attracting considerable attention as non-polluting power generators with high energy conversion efficiencies in mobile applications. Polymer electrolyte membrane (PEM) is one of the essential components of PEMFCs. Perfluorosulfonic acid based membranes known as Nafion® is widely used as PEMs. Nafion® membranes water dependent proton conductivity which limits the operating temperature below 100ᵒC. At higher temperatures, proton conductivity and mechanical stability of these membranes decrease because of dehydration. Polybenzimidazole (PBI), which has good anhydrous proton conductivity after doped with acids, as well as excellent thermal stability, shows great potential in the application of high temperature PEMFCs. In the present study, PBI polymers were synthesized by solution polycondensation at 190 and 210ᵒC. The synthesized polymers were characterized by FTIR, 1H NMR, and TGA. Phosphoric acid doped PBI membranes were prepared and tested in a PEMFC. The influences of reaction temperature on structural properties of synthesized polymers were investigated. Mechanical properties, acid-doping level, proton conductivity, and fuel cell performances of prepared phosphoric acid doped PBI membranes were evaluated. The maximum power density was found as 32.5 mW/cm² at 120ᵒC.

Keywords: fuel cell, high temperature polymer electrolyte membrane, polybenzimidazole, proton exchange membrane fuel cell

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1703 Suppressing Vibration in a Three-axis Flexible Satellite: An Approach with Composite Control

Authors: Jalal Eddine Benmansour, Khouane Boulanoir, Nacera Bekhadda, Elhassen Benfriha

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This paper introduces a novel composite control approach that addresses the challenge of stabilizing the three-axis attitude of a flexible satellite in the presence of vibrations caused by flexible appendages. The key contribution of this research lies in the development of a disturbance observer, which effectively observes and estimates the unwanted torques induced by the vibrations. By utilizing the estimated disturbance, the proposed approach enables efficient compensation for the detrimental effects of vibrations on the satellite system. To govern the attitude angles of the spacecraft, a proportional derivative controller (PD) is specifically designed and proposed. The PD controller ensures precise control over all attitude angles, facilitating stable and accurate spacecraft maneuvering. In order to demonstrate the global stability of the system, the Lyapunov method, a well-established technique in control theory, is employed. Through rigorous analysis, the Lyapunov method verifies the convergence of system dynamics, providing strong evidence of system stability. To evaluate the performance and efficacy of the proposed control algorithm, extensive simulations are conducted. The simulation results validate the effectiveness of the combined approach, showcasing significant improvements in the stabilization and control of the satellite's attitude, even in the presence of disruptive vibrations from flexible appendages. This novel composite control approach presented in this paper contributes to the advancement of satellite attitude control techniques, offering a promising solution for achieving enhanced stability and precision in challenging operational environments.

Keywords: attitude control, flexible satellite, vibration control, disturbance observer

Procedia PDF Downloads 86
1702 Devulcanization of Waste Rubber Using Thermomechanical Method Combined with Supercritical CO₂

Authors: L. Asaro, M. Gratton, S. Seghar, N. Poirot, N. Ait Hocine

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Rubber waste disposal is an environmental problem. Particularly, many researches are centered in the management of discarded tires. In spite of all different ways of handling used tires, the most common is to deposit them in a landfill, creating a stock of tires. These stocks can cause fire danger and provide ambient for rodents, mosquitoes and other pests, causing health hazards and environmental problems. Because of the three-dimensional structure of the rubbers and their specific composition that include several additives, their recycling is a current technological challenge. The technique which can break down the crosslink bonds in the rubber is called devulcanization. Strictly, devulcanization can be defined as a process where poly-, di-, and mono-sulfidic bonds, formed during vulcanization, are totally or partially broken. In the recent years, super critical carbon dioxide (scCO₂) was proposed as a green devulcanization atmosphere. This is because it is chemically inactive, nontoxic, nonflammable and inexpensive. Its critical point can be easily reached (31.1 °C and 7.38 MPa), and residual scCO₂ in the devulcanized rubber can be easily and rapidly removed by releasing pressure. In this study thermomechanical devulcanization of ground tire rubber (GTR) was performed in a twin screw extruder under diverse operation conditions. Supercritical CO₂ was added in different quantities to promote the devulcanization. Temperature, screw speed and quantity of CO₂ were the parameters that were varied during the process. The devulcanized rubber was characterized by its devulcanization percent and crosslink density by swelling in toluene. Infrared spectroscopy (FTIR) and Gel permeation chromatography (GPC) were also done, and the results were related with the Mooney viscosity. The results showed that the crosslink density decreases as the extruder temperature and speed increases, and, as expected, the soluble fraction increase with both parameters. The Mooney viscosity of the devulcanized rubber decreases as the extruder temperature increases. The reached values were in good correlation (R= 0.96) with de the soluble fraction. In order to analyze if the devulcanization was caused by main chains or crosslink scission, the Horikx's theory was used. Results showed that all tests fall in the curve that corresponds to the sulfur bond scission, which indicates that the devulcanization has successfully happened without degradation of the rubber. In the spectra obtained by FTIR, it was observed that none of the characteristic peaks of the GTR were modified by the different devulcanization conditions. This was expected, because due to the low sulfur content (~1.4 phr) and the multiphasic composition of the GTR, it is very difficult to evaluate the devulcanization by this technique. The lowest crosslink density was reached with 1 cm³/min of CO₂, and the power consumed in that process was also near to the minimum. These results encourage us to do further analyses to better understand the effect of the different conditions on the devulcanization process. The analysis is currently extended to monophasic rubbers as ethylene propylene diene monomer rubber (EPDM) and natural rubber (NR).

Keywords: devulcanization, recycling, rubber, waste

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1701 The Weavability of Waste Plants and Their Application in Fashion and Textile Design

Authors: Jichi Wu

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The dwindling of resources requires a more sustainable design. New technology could bring new materials and processing techniques to the fashion industry and push it to a more sustainable future. Thus this paper explores cutting-edge researches on the life-cycle of closed-loop products and aims to find innovative ways to recycle and upcycle. For such a goal, the author investigated how low utilization plants and leftover fiber could be turned into ecological textiles in fashion. Through examining the physical and chemical properties (cellulose content/ fiber form) of ecological textiles to explore their wearability, this paper analyzed the prospect of bio-fabrics (weavable plants) in body-oriented fashion design and their potential in sustainable fashion and textile design. By extracting cellulose from 9 different types or sections of plants, the author intends to find an appropriate method (such as ion solution extraction) to mostly increase the weavability of plants, so raw materials could be more effectively changed into fabrics. All first-hand experiment data were carefully collected and then analyzed under the guidance of related theories. The result of the analysis was recorded in detail and presented in an understandable way. Various research methods are adopted through this project, including field trip and experiments to make comparisons and recycle materials. Cross-discipline cooperation is also conducted for related knowledge and theories. From this, experiment data will be collected, analyzed, and interpreted into a description and visualization results. Based on the above conclusions, it is possible to apply weavable plant fibres to develop new textile and fashion.

Keywords: wearable bio-textile, sustainability, economy, ecology, technology, weavability, fashion design

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1700 Intelligent Control of Bioprocesses: A Software Application

Authors: Mihai Caramihai, Dan Vasilescu

Abstract:

The main research objective of the experimental bioprocess analyzed in this paper was to obtain large biomass quantities. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The reactor was equipped with pH, temperature, dissolved oxygen, and agitation controllers. The operating parameters were 37 oC, 1.2 atm, 250 rpm and air flow rate of 15 L/min. The main objective of this paper is to present a case study to demonstrate that intelligent control, describing the complexity of the biological process in a qualitative and subjective manner as perceived by human operator, is an efficient control strategy for this kind of bioprocesses. In order to simulate the bioprocess evolution, an intelligent control structure, based on fuzzy logic has been designed. The specific objective is to present a fuzzy control approach, based on human expert’ rules vs. a modeling approach of the cells growth based on bioprocess experimental data. The kinetic modeling may represent only a small number of bioprocesses for overall biosystem behavior while fuzzy control system (FCS) can manipulate incomplete and uncertain information about the process assuring high control performance and provides an alternative solution to non-linear control as it is closer to the real world. Due to the high degree of non-linearity and time variance of bioprocesses, the need of control mechanism arises. BIOSIM, an original developed software package, implements such a control structure. The simulation study has showed that the fuzzy technique is quite appropriate for this non-linear, time-varying system vs. the classical control method based on a priori model.

Keywords: intelligent, control, fuzzy model, bioprocess optimization

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1699 Lithium Ion Supported on TiO2 Mixed Metal Oxides as a Heterogeneous Catalyst for Biodiesel Production from Canola Oil

Authors: Mariam Alsharifi, Hussein Znad, Ming Ang

Abstract:

Considering the environmental issues and the shortage in the conventional fossil fuel sources, biodiesel has gained a promising solution to shift away from fossil based fuel as one of the sustainable and renewable energy. It is synthesized by transesterification of vegetable oils or animal fats with alcohol (methanol or ethanol) in the presence of a catalyst. This study focuses on synthesizing a high efficient Li/TiO2 heterogeneous catalyst for biodiesel production from canola oil. In this work, lithium immobilized onto TiO2 by the simple impregnation method. The catalyst was evaluated by transesterification reaction in a batch reactor under moderate reaction conditions. To study the effect of Li concentrations, a series of LiNO3 concentrations (20, 30, 40 wt. %) at different calcination temperatures (450, 600, 750 ºC) were evaluated. The Li/TiO2 catalysts are characterized by several spectroscopic and analytical techniques such as XRD, FT-IR, BET, TG-DSC and FESEM. The optimum values of impregnated Lithium nitrate on TiO2 and calcination temperature are 30 wt. % and 600 ºC, respectively, along with a high conversion to be 98 %. The XRD study revealed that the insertion of Li improved the catalyst efficiency without any alteration in structure of TiO2 The best performance of the catalyst was achieved when using a methanol to oil ratio of 24:1, 5 wt. % of catalyst loading, at 65◦C reaction temperature for 3 hours of reaction time. Moreover, the experimental kinetic data were compatible with the pseudo-first order model and the activation energy was (39.366) kJ/mol. The synthesized catalyst Li/TiO2 was applied to trans- esterify used cooking oil and exhibited a 91.73% conversion. The prepared catalyst has shown a high catalytic activity to produce biodiesel from fresh and used oil within mild reaction conditions.

Keywords: biodiesel, canola oil, environment, heterogeneous catalyst, impregnation method, renewable energy, transesterification

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1698 Expansion of Cord Blood Cells Using a Mix of Neurotrophic Factors

Authors: Francisco Dos Santos, Diogo Fonseca-Pereira, Sílvia Arroz-Madeira, Henrique Veiga-Fernandes

Abstract:

Haematopoiesis is a developmental process that generates all blood cell lineages in health and disease. This relies on quiescent haematopoietic stem cells (HSCs) that are able to differentiate, self renew and expand upon physiological demand. HSCs have great interest in regenerative medicine, including haematological malignancies, immunodeficiencies and metabolic disorders. However, the limited yield from existing HSC sources drives the global need for reliable techniques to expand harvested HSCs at high quality and sufficient quantities. With the extensive use of cord blood progenitors for clinical applications, there is a demand for a safe and efficient expansion protocol that is able to overcome the limitations of the cord blood as a source of HSC. StemCell2MAXTM developed a technology that enhances the survival, proliferation and transplantation efficiency of HSC, leading the way to a more widespread use of HSC for research and clinical purposes. StemCell2MAXTM MIX is a solution that improves HSC expansion up to 20x, while preserving stemness, when compared to state-of-the-art. In a recent study by a leading cord blood bank, StemCell2MAX MIX was shown to support a selective 100-fold expansion of CD34+ Hematopoietic Stem and Progenitor Cells (when compared to a 10-fold expansion of Total Nucleated Cells), while maintaining their multipotent differentiative potential as assessed by CFU assays. The technology developed by StemCell2MAXTM opens new horizons for the usage of expanded hematopoietic progenitors for both research purposes (including quality and functional assays in Cord Blood Banks) and clinical applications.

Keywords: cord blood, expansion, hematopoietic stem cell, transplantation

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1697 A Chemical-Free Colouration Technique for Regenerated Fibres Using Waste Alpaca Fibres

Authors: M. Abdullah Al Faruque, Rechana Remadevi, Abu Naser M. Ahsanul Haque, Joselito Razal, Xungai Wang, Maryam Naebe

Abstract:

Generally, the colouration of textile fibres is performed by using synthetic colourants in dope dyeing or conventional dyeing methods. However, the toxic effect of some synthetic colorants due to long-term exposure can cause several health threats including cancer, asthma and skin diseases. Moreover, in colouration process, these colourants not only consume a massive amount of water but also generates huge proportion of wastewater to the environment. Despite having the environmentally friendly characteristics, current natural colourants have downsides in their yield and need chemical extraction processes which are water consuming as well. In view of this, the present work focuses to develop a chemical-free biocompatible and natural pigment based colouration technique to colour regenerated fibres. Waste alpaca fibre was used as a colourant and the colour properties, as well as the mechanical properties, of the regenerated fibres were investigated. The colourant from waste alpaca was fabricated through mechanical milling process and it was directly applied to the polyacrylonitrile (PAN) dope solution in different ratios of alpaca: PAN (10:90, 20:80, 30:70). The results obtained from the chemical structure characterization suggested that all the coloured regenerated fibres exhibited chemical functional groups of both PAN and alpaca. Furthermore, the color strength was increased gradually with the increment of alpaca content and showed excellent washing fastness properties. These results reveal a potential new pathway for chemical-free dyeing technique for fibres with improved properties.

Keywords: alpaca, chemical-free coloration, natural colorant, polyacrylonitrile, water consumption, wet spinning

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1696 Petrology, Geochemistry and Formation Conditions of Metaophiolites of the Loki Crystalline Massif (the Caucasus)

Authors: Irakli Gamkrelidze, David Shengelia, Tamara Tsutsunava, Giorgi Chichinadze, Giorgi Beridze, Ketevan Tedliashvili, Tamara Tsamalashvili

Abstract:

The Loki crystalline massif crops out in the Caucasian region and the geological retrospective represent the northern marginal part of the Baiburt-Sevanian terrain (island arc), bordering with the Paleotethys oceanic basin in the north. The pre-Alpine basement of the massif is built up of Lower-Middle Paleozoic metamorphic complex (metasedimentary and metabasite rocks), Upper Devonian quartz-diorites and Late Variscan granites. Earlier metamorphic complex was considered as an indivisible set including suites with different degree of metamorphism. Systematic geologic, petrologic and geochemical investigations of the massif’s rocks suggest the different conception on composition, structure and formation conditions of the massif. In particular, there are two main rock types in the Loki massif: the oldest autochthonous series of gneissic quartz-diorites and cutting them granites. The massif is flanked on its western side by a volcano-sedimentary sequence, metamorphosed to low-T facies. Petrologic, metamorphic and structural differences in this sequence prove the existence of a number of discrete units (overthrust sheets). One of them, the metabasic sheet represents the fragment of ophiolite complex. It comprises transition types of the second and third layers of the Paleooceanic crust: the upper noncumulated part of the third layer gabbro component and the following lowest part of the parallel diabase dykes of the second layer. The ophiolites are represented by metagabbros, metagabbro-diabases, metadiabases and amphibolite schists. According to the content of petrogenic components and additive elements in metabasites is stated that the protolith of metabasites belongs to petrochemical type of tholeiitic series of basalts. The parental magma of metaophiolites is of E-MORB composition, and by petrochemical parameters, it is very close to the composition of intraplate basalts. The dykes of hypabissal leucocratic siliceous and medium magmatic rocks associated with the metaophiolite sheet form the separate complex. They are granitoids with the extremely low content of CaO and quartz-diorite porphyries. According to various petrochemical parameters, these rocks have mixed characteristics. Their formation took place in spreading conditions or in the areas of manifestation of plumes most likely of island arc type. The metamorphism degree of the metaophiolites corresponds to a very low stage of green schist facies. The rocks of the metaophiolite complex are obducted from the Paleotethys Ocean. Geological and paleomagnetic data show that the primary location of the ocean is supposed to be to the north of the Loki crystalline massif.

Keywords: the Caucasus, crystalline massif, ophiolites, tectonic sheet

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1695 Using Dynamic Glazing to Eliminate Mechanical Cooling in Multi-family Highrise Buildings

Authors: Ranojoy Dutta, Adam Barker

Abstract:

Multifamily residential buildings are increasingly being built with large glazed areas to provide tenants with greater daylight and outdoor views. However, traditional double-glazed window assemblies can lead to significant thermal discomfort from high radiant temperatures as well as increased cooling energy use to address solar gains. Dynamic glazing provides an effective solution by actively controlling solar transmission to maintain indoor thermal comfort, without compromising the visual connection to outdoors. This study uses thermal simulations across three Canadian cities (Toronto, Vancouver and Montreal) to verify if dynamic glazing along with operable windows and ceiling fans can maintain the indoor operative temperature of a prototype southwest facing high-rise apartment unit within the ASHRAE 55 adaptive comfort range for a majority of the year, without any mechanical cooling. Since this study proposes the use of natural ventilation for cooling and the typical building life cycle is 30-40 years, the typical weather files have been modified based on accepted global warming projections for increased air temperatures by 2050. Results for the prototype apartment confirm that thermal discomfort with dynamic glazing occurs only for less than 0.7% of the year. However, in the baseline scenario with low-E glass there are up to 7% annual hours of discomfort despite natural ventilation with operable windows and improved air movement with ceiling fans.

Keywords: electrochromic glazing, multi-family housing, passive cooling, thermal comfort, natural ventilation

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1694 Estimation Model for Concrete Slump Recovery by Using Superplasticizer

Authors: Chaiyakrit Raoupatham, Ram Hari Dhakal, Chalermchai Wanichlamlert

Abstract:

This paper is aimed to introduce the solution of concrete slump recovery using chemical admixture type-F (superplasticizer, naphthalene base) to the practice, in order to solve unusable concrete problem due to concrete loss its slump, especially for those tropical countries that have faster slump loss rate. In the other hand, randomly adding superplasticizer into concrete can cause concrete to segregate. Therefore, this paper also develops the estimation model used to calculate amount of second dose of superplasticizer need for concrete slump recovery. Fresh properties of ordinary Portland cement concrete with volumetric ratio of paste to void between aggregate (paste content) of 1.1-1.3 with water-cement ratio zone of 0.30 to 0.67 and initial superplasticizer (naphthalene base) of 0.25%- 1.6% were tested for initial slump and slump loss for every 30 minutes for one and half hour by slump cone test. Those concretes with slump loss range from 10% to 90% were re-dosed and successfully recovered back to its initial slump. Slump after re-dosed was tested by slump cone test. From the result, it has been concluded that, slump loss was slower for those mix with high initial dose of superplasticizer due to addition of superplasticizer will disturb cement hydration. The required second dose of superplasticizer was affected by two major parameter, which were water-cement ratio and paste content, where lower water-cement ratio and paste content cause an increase in require second dose of superplasticizer. The amount of second dose of superplasticizer is higher as the solid content within the system is increase, solid can be either from cement particles or aggregate. The data was analyzed to form an equation use to estimate the amount of second dosage requirement of superplasticizer to recovery slump to its original.

Keywords: estimation model, second superplasticizer dosage, slump loss, slump recovery

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1693 Near Optimal Closed-Loop Guidance Gains Determination for Vector Guidance Law, from Impact Angle Errors and Miss Distance Considerations

Authors: Karthikeyan Kalirajan, Ashok Joshi

Abstract:

An optimization problem is to setup to maximize the terminal kinetic energy of a maneuverable reentry vehicle (MaRV). The target location, the impact angle is given as constraints. The MaRV uses an explicit guidance law called Vector guidance. This law has two gains which are taken as decision variables. The problem is to find the optimal value of these gains which will result in minimum miss distance and impact angle error. Using a simple 3DOF non-rotating flat earth model and Lockheed martin HP-MARV as the reentry vehicle, the nature of solutions of the optimization problem is studied. This is achieved by carrying out a parametric study for a range of closed loop gain values and the corresponding impact angle error and the miss distance values are generated. The results show that there are well defined lower and upper bounds on the gains that result in near optimal terminal guidance solution. It is found from this study, that there exist common permissible regions (values of gains) where all constraints are met. Moreover, the permissible region lies between flat regions and hence the optimization algorithm has to be chosen carefully. It is also found that, only one of the gain values is independent and that the other dependent gain value is related through a simple straight-line expression. Moreover, to reduce the computational burden of finding the optimal value of two gains, a guidance law called Diveline guidance is discussed, which uses single gain. The derivation of the Diveline guidance law from Vector guidance law is discussed in this paper.

Keywords: Marv guidance, reentry trajectory, trajectory optimization, guidance gain selection

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1692 Using Convolutional Neural Networks to Distinguish Different Sign Language Alphanumerics

Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

Abstract:

Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

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1691 Software-Defined Architecture and Front-End Optimization for DO-178B Compliant Distance Measuring Equipment

Authors: Farzan Farhangian, Behnam Shakibafar, Bobda Cedric, Rene Jr. Landry

Abstract:

Among the air navigation technologies, many of them are capable of increasing aviation sustainability as well as accuracy improvement in Alternative Positioning, Navigation, and Timing (APNT), especially avionics Distance Measuring Equipment (DME), Very high-frequency Omni-directional Range (VOR), etc. The integration of these air navigation solutions could make a robust and efficient accuracy in air mobility, air traffic management and autonomous operations. Designing a proper RF front-end, power amplifier and software-defined transponder could pave the way for reaching an optimized avionics navigation solution. In this article, the possibility of reaching an optimum front-end to be used with single low-cost Software-Defined Radio (SDR) has been investigated in order to reach a software-defined DME architecture. Our software-defined approach uses the firmware possibilities to design a real-time software architecture compatible with a Multi Input Multi Output (MIMO) BladeRF to estimate an accurate time delay between a Transmission (Tx) and the reception (Rx) channels using the synchronous scheduled communication. We could design a novel power amplifier for the transmission channel of the DME to pass the minimum transmission power. This article also investigates designing proper pair pulses based on the DO-178B avionics standard. Various guidelines have been tested, and the possibility of passing the certification process for each standard term has been analyzed. Finally, the performance of the DME was tested in the laboratory environment using an IFR6000, which showed that the proposed architecture reached an accuracy of less than 0.23 Nautical mile (Nmi) with 98% probability.

Keywords: avionics, DME, software defined radio, navigation

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1690 Flooring Solution for Sports Courts Such as Ecological Mortar

Authors: Helida T. G. Soares, Antonio J. P. da Silva

Abstract:

As the society develops, the accumulation of solid waste in landfills, in the environment, and the depletion of the raw material increases. In this way, there is relevance in researching the interaction between the environmental management and civil construction; therefore, this project has for scope the analysis and the effects of the rubber microparticles use as a small aggregate added to the sand, producing an ecological mortar for the pavement constitution, from the mixture of a paste, composed of Portland cement and water, and its application in sports courts. It was used the detailed reutilization of micro rubber in its most primordial, micro form, highlighting the powder pattern as the additional balancing of the mortar, analyzing the evolution of the mechanical properties. Percentages of 5, 10 and 15% rubber were used based on the total mass of the trace, where there is no removal of aggregates or cement, only increment of the rubber. The results obtained through the mechanical test of simple compression showed that the rubber, added to the mortar, presents low mechanical resistance compared to the reference trait, the study of this subject is vast of possibilities to be explored. In this sense, we seek sustainability and innovation from the use of an ecological material, thus adding value and reducing the impact of this material on the environment. The manufacturing process takes place from the direct mixing of cement paste and rubber, whether manually, mechanically or industrially. It results in the production of a low-cost mortar, through the use of recycled rubber, with high efficiency in general properties, such as compressive strength and friction coefficient, allowing its use for the construction of floors for sports courts with high durability. Thus, it is possible to reuse this micro rubber residue in other applications in simple concrete artifacts.

Keywords: civil construction, ecological mortar, high efficiency, rubber

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1689 Business Intelligent to a Decision Support Tool for Green Entrepreneurship: Meso and Macro Regions

Authors: Anishur Rahman, Maria Areias, Diogo Simões, Ana Figeuiredo, Filipa Figueiredo, João Nunes

Abstract:

The circular economy (CE) has gained increased awareness among academics, businesses, and decision-makers as it stimulates resource circularity in the production and consumption systems. A large epistemological study has explored the principles of CE, but scant attention eagerly focused on analysing how CE is evaluated, consented to, and enforced using economic metabolism data and business intelligent framework. Economic metabolism involves the ongoing exchange of materials and energy within and across socio-economic systems and requires the assessment of vast amounts of data to provide quantitative analysis related to effective resource management. Limited concern, the present work has focused on the regional flows pilot region from Portugal. By addressing this gap, this study aims to promote eco-innovation and sustainability in the regions of Intermunicipal Communities Região de Coimbra, Viseu Dão Lafões and Beiras e Serra da Estrela, using this data to find precise synergies in terms of material flows and give companies a competitive advantage in form of valuable waste destinations, access to new resources and new markets, cost reduction and risk sharing benefits. In our work, emphasis on applying artificial intelligence (AI) and, more specifically, on implementing state-of-the-art deep learning algorithms is placed, contributing to construction a business intelligent approach. With the emergence of new approaches generally highlighted under the sub-heading of AI and machine learning (ML), the methods for statistical analysis of complex and uncertain production systems are facing significant changes. Therefore, various definitions of AI and its differences from traditional statistics are presented, and furthermore, ML is introduced to identify its place in data science and the differences in topics such as big data analytics and in production problems that using AI and ML are identified. A lifecycle-based approach is then taken to analyse the use of different methods in each phase to identify the most useful technologies and unifying attributes of AI in manufacturing. Most of macroeconomic metabolisms models are mainly direct to contexts of large metropolis, neglecting rural territories, so within this project, a dynamic decision support model coupled with artificial intelligence tools and information platforms will be developed, focused on the reality of these transition zones between the rural and urban. Thus, a real decision support tool is under development, which will surpass the scientific developments carried out to date and will allow to overcome imitations related to the availability and reliability of data.

Keywords: circular economy, artificial intelligence, economic metabolisms, machine learning

Procedia PDF Downloads 73