Search results for: hybrid techniques

Authors: Shasha Lv, Zhengcao Li

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Due to the CMOS compatibility, silicon-based field emission (FE) devices as potential electron sources have attracted much attention. The geometrical arrangement and dimensional features of aligned silicon nanowires (SiNWs) have a determining influence on the FE properties. We discuss a multistep template replication process of Ag-assisted chemical etching combined with polystyrene (PS) spheres to fabricate highly periodic and well-aligned silicon nanowires, then their diameter, aspect ratio and density were further controlled via dry oxidation and post chemical treatment. The FE properties related to proximity and aspect ratio were systematically studied. A remarkable improvement of FE propertiy was observed with the average nanowires tip interspace increasing from 80 to 820 nm. On the basis of adjusting SiNWs dimensions and morphology, addition of a secondary material whose properties complement the SiNWs could yield a combined characteristic. Three different nanoheterostructures were fabricated to control the FE performance, they are: NiSi/Si core-shell structures, ZnO/Si nanotrees, and Graphene/SiNWs. We successfully fabricated the high-quality NiSi/Si heterostructured nanowires with excellent conformality. First, nickle nanoparticles were deposited onto SiNWs, then rapid thermal annealing process were utilized to form NiSi shell. In addition, we demonstrate a new and simple method for creating 3D nanotree-like ZnO/Si nanocomposites with a spatially branched hierarchical structure. Compared with the as-prepared SiNRs and ZnO NWs, the high-density ZnO NWs on SiNRs have exhibited predominant FE characteristics, and the FE enhancement factors were attributed to band bending effect and geometrical morphology. The FE efficiency from flat sheet structure of graphene is low. We discussed an effective approach towards full control over the diameter of uniform SiNWs to adjust the protrusions of large-scale graphene sheet deposited on SiNWs. The FE performance regarding the uniformity and dimensional control of graphene protrusions supported on SiNWs was systematically clarified. Therefore, the hybrid SiNWs/graphene structures with protrusions provide a promising class of field emission cathodes.

Keywords: field emission, silicon nanowires, heterostructures, controllable synthesis

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Authors: A. H. Paul, L. J. Gizaki, E. P. Ejimbi

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The study was carried out to determine the level of knowledge and adoption of agricultural biotechnology in Taraba state. Purposive and simple sampling techniques were used to select respondents. Questionnaires were administered to 90 respondents. Data were analyzed using descriptive and inferential statistics. The results showed that the majority (73.3%) of the respondents were small-scale farmers, whereas 24.4 percent were engaged in secondary occupations. The mean farm size was 1-5 ha. The majority (72.2%) had one form of formal education or another. About 84 percent (84.4%) had been farming for at least 10 years. There was a mean household size of 6-10 persons. Many (97.8%) of the respondents were knowledgeable about biotechnology, and about 70.0 percent (70.1%) reported that the biotechnology products which they had adopted were very good for animals and human consumption. The result of Pearson’s correlation (r = 0.699) was significant at the 0.01 alpha level. Therefore, the hypothesis that there is no significant relationship between knowledge and adoption of agricultural biotechnology was rejected. It was concluded that the agricultural biotechnologies that were adopted were very safe for animals, humans, and the environment. It was recommended that the government should employ more extension agents to help educate farmers about agricultural biotechnology.

Keywords: agricultural, adoption, biotechnology, knowledge

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Authors: Rami Rami Mahmoud Bakr

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The constant rate of strain (CRS) test is a rapid technique that effectively measures specific properties of cohesive soil, including the rate of consolidation, hydraulic conductivity, compressibility, and stress history. Its simple operation and frequent readings enable efficient definition, especially of the compression curve. However, its limitations include an inability to handle strain-rate-dependent soil behavior, initial transient conditions, and pore pressure evaluation errors. There are currently no effective techniques for interpreting CRS data. In this study, experiments were performed to evaluate the effects of different parameters on CRS results. Extensive tests were performed on two types of clay to analyze the soil behavior during strain consolidation at a constant rate. The results were used to evaluate the transient conditions and pore pressure system.

Keywords: constant rate of strain (CRS), resedimented boston blue clay (RBBC), resedimented vicksburg buckshot clay (RVBC), compression index

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Authors: Fadwa Chtioui

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Vital Pulp Therapy (VPT) is nowadays challenging the deep-rooted dogma of root canal treatment, being the only therapeutic option for permanent teeth diagnosed with irreversible pulpitis or carious pulp exposure. Histologic and clinical research has shown that compromised dental pulp can be treated without the full removal or excavation of all healthy pulp, and the outcome of the partial or full pulpotomy followed by a Tricalcium-Silicate-based dressing seems to show promising results in maintaining pulp vitality and preserving affected teeth in the long term. By reviewing recent advances in the techniques of VPT and their clinical effectiveness and safety in permanent teeth with irreversible Pulpitis, this work provides a new understanding of pulp pathophysiology and defense mechanisms and will reform dental practitioners' decision-making in treating irreversible pulpits from root canal therapy to vital pulp therapy by taking advantage of the biological effects of Tricalcium Silicate materials.

Keywords: irreversible pulpitis, vital pulp therapy, pulpotomy, Tricalcium Silicate

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Authors: Gangmin Li, Fan Yang

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Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: personalized recommendation, generative user modelling, user intention identification, large language models, chain-of-thought prompting

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Authors: Muhammad Atif, M. Samsul Alam

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The purpose of this study is to investigate the effects of board room gender diversity on firm sustainable investment. We test the extent to which sustainable investment is affected by the presence of female directors on U.S. corporate boards. Using data of S&P 1500 indexed firms collected from Bloomberg covering the period 2004-2016, we estimate the baseline model to investigate the effects of board room gender diversity on firm sustainable investment. We find a positive relationship between board gender diversity and sustainable investment. We also find that boards with two or more women have a pronounced impact on sustainable investment, consistent with the critical mass theory. Female independent directors have a stronger impact on sustainable investment than female executive directors. Our findings are robust to different identification and estimation techniques. The study offers another perspective of the ongoing debate in the social responsibility literature about the accountability relationships between business and society.

Keywords: sustainable investment, gender diversity, environmental proctection, social responsibility

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Authors: M. R. Ebrahimi, B. Mahdaviani

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Conventional electric distribution systems are radial in nature, supplied at one end through a main source. These networks generally have a simple protection system usually implemented using fuses, re-closers, and over-current relays. Recently, great attention has been paid to applying Distributed energy resources (DERs) throughout electric distribution systems. Presence of such generation in a network leads to losing coordination of protection devices. Therefore, it is desired to develop an algorithm which is capable of protecting distribution systems that include DER. On the other hand smart grid brings opportunities to the power system. Fast advancement in communication and measurement techniques accelerates the development of multi agent system (MAS). So in this paper, a new approach for the protection of distribution networks in the presence of DERs is presented base on MAS. The proposed scheme has been implemented on a sample 27-bus distribution network.

Keywords: distributed energy resource, distribution network, protection, smart grid, multi agent system

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Natasha Petrovska, Mirjana Pavlovic, Maria M. Larrondo-Petrie

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Neural stem cells (NSCs) are multi-potent, self-renewing cells that generate new neurons. Three subtypes of NSCs can be separated regarding the stages of NSC lineage: quiescent neural stem cells (qNSCs), activated neural stem cells (aNSCs) and neural progenitor cells (NPCs), but their gene expression signatures are not utterly understood yet. Single-cell examinations have started to elucidate the complex structure of NSC populations. Nevertheless, there is a lack of thorough molecular interpretation of the NSC lineage heterogeneity and an increasing need for tools to analyze and improve the efficiency and correctness of single-cell sequencing data. Feature selection and ordering can identify and classify the gene expression signatures of these subtypes and can discover novel subpopulations during the NSCs activation and differentiation processes. The aim here is to review the implementation of the feature selection technique on NSC subtypes and the classification techniques that have been used for the identification of gene expression signatures.

Keywords: feature selection, feature similarity, neural stem cells, genes, feature selection methods

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Authors: Jingyi Li, Laurence Stamford, Alejandro Gallego-Schmid

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Renewable electricity has become an indispensable contributor to achieving net-zero by the mid-century to tackle climate change. Unlike solar, wind, or hydro, geothermal was stagnant in its electricity production development for decades. However, with the significant breakthrough made in recent years, especially the implementation of enhanced geothermal systems (EGS) in various regions globally, geothermal electricity could play a pivotal role in alleviating greenhouse gas emissions. Life cycle assessment has been applied to analyze specific geothermal power generation technologies, which proposed suggestions to optimize its environmental performance. For instance, selecting a high heat gradient region enables a higher flow rate from the production well and extends the technical lifespan. Although such process-level improvements have been made, the significance of geothermal power generation technologies so far has not explicitly displayed its competitiveness on a broader horizon. Therefore, this review-based study integrates a circular economy framework into life cycle assessment, clarifying the underlying added values for geothermal power plants to complete the sustainability profile. The derived results have provided an enlarged platform to discuss geothermal power generation technologies: (i) recover the heat and electricity from the process to reduce the fossil fuel requirements; (ii) recycle the construction materials, such as copper, steel, and aluminum for future projects; (iii) extract the lithium ions from geothermal brine and make geothermal reservoir become a potential supplier of the lithium battery industry; (iv) repurpose the abandoned oil and gas wells to build geothermal power plants; (v) integrate geothermal energy with other available renewable energies (e.g., solar and wind) to provide heat and electricity as a hybrid system at different weather; (vi) rethink the fluids used in stimulation process (EGS only), replace water with CO2 to achieve negative emissions from the system. These results provided a new perspective to the researchers, investors, and policymakers to rethink the role of geothermal in the energy supply network.

Keywords: climate, renewable energy, R strategies, sustainability

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Authors: J. M. de Luis Ruiz, P. M. Sierra García, R. P. García, R. P. Álvarez, F. P. García, E. C. López

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Given the evolution of viaducts, structural health monitoring requires more complex techniques to define their state. two alternatives can be distinguished: experimental and operational modal analysis. Although accelerometers or Global Positioning System (GPS) have been applied for the monitoring of structures under exploitation, the dynamic monitoring during the stage of construction is not common. This research analyzes whether GPS data can be applied to certain dynamic geometric controls of evolving structures. The fundamentals of this work were applied to the New Bridge of Cádiz (Spain), a worldwide milestone in bridge building. GPS data were recorded with an interval of 1 second during the erection of segments and turned to the frequency domain with Fourier transform. The vibration period and amplitude were contrasted with those provided by the finite element model, with differences of less than 10%, which is admissible. This process provides a vibration record of the structure with GPS, avoiding specific equipment.

Keywords: Fourier transform, global position system, operational modal analysis, structural health monitoring

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Authors: R. Farhoud, G. Hermand, S. Delepine-lesoille

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Future underground facility of French radioactive waste disposal, named Cigeo, is designed to store intermediate and high level - long-lived French radioactive waste. Intermediate level waste cells are tunnel-like, about 400m length and 65 m² section, equipped with several concrete layers, which can be grouted in situ or composed of tunnel elements pre-grouted. The operating space into cells, to allow putting or removing waste containers, should be monitored for several decades without any maintenance. To provide the required information, design was performed and tested in situ in Andra’s underground laboratory (URL) at 500m under the surface. Based on distributed optic fiber sensors (OFS) and backscattered Brillouin for strain and Raman for temperature interrogation technics, the design consists of 2 loops of OFS, at 2 different radiuses, around the monitored section (Orthoradiale strains) and longitudinally. Strains measured by distributed OFS cables were compared to classical vibrating wire extensometers (VWE) and platinum probes (Pt). The OFS cables were composed of 2 cables sensitive to strains and temperatures and one only for temperatures. All cables were connected, between sensitive part and instruments, to hybrid cables to reduce cost. The connection has been made according to 2 technics: splicing fibers in situ after installation or preparing each fiber with a connector and only plugging them together in situ. Another challenge was installing OFS cables along a tunnel mad in several parts, without interruption along several parts. First success consists of the survival rate of sensors after installation and quality of measurements. Indeed, 100% of OFS cables, intended for long-term monitoring, survived installation. Few new configurations were tested with relative success. Measurements obtained were very promising. Indeed, after 3 years of data, no difference was observed between cables and connection methods of OFS and strains fit well with VWE and Pt placed at the same location. Data, from Brillouin instrument sensitive to strains and temperatures, were compensated with data provided by Raman instrument only sensitive to temperature and into a separated fiber. These results provide confidence in the next steps of the qualification processes which consists of testing several data treatment approach for direct analyses.

Keywords: monitoring, fiber optic, sensor, data treatment

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Authors: Ani Thomas

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Every narrative is a temporal construct. Every narrative creates a qualitative experience of time for the viewer. The paper argues for the concept of a qualified time that emerges from the interaction between the narrative and the audience. The paper also challenges the conventional understanding of narrative time as either story time, real time or discourse time. Looking at narratives through the medium of Cinema, the study examines how narratives create and manipulate duration or durée, the qualitative experience of time as theorized by Henri Bergson. The paper further analyzes how Cinema and, by extension, narratives are nothing but Durée and the filmmaker, the artist of durée, who shape and manipulate the perception and emotions of the viewer through the manipulation and construction of durée. The paper draws on cinematic works to look at the techniques to demonstrate how filmmakers use, for example, editing, sound, compositional and production narratives etc., to create various modes of durée that challenge, amplify or unsettle the viewer’s sense of time. Bringing together the Viewer’s durée and exploring its interaction with the narrative construct, the paper explores the emergence of the new qualitative time, the narrative durée, that defines the audience experience.

Keywords: cinema, time, bergson, duree

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Authors: Zane Brough, Claudio Paoloni

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Modern low earth orbit (LEO) satellites that require multi-mission flexibility are highly likely to be repositioned between different operational orbits. While executing this process the satellite may experience high levels of vibration and environmental hazards, exposing the deployed solar panel to dangerous stress levels, fatigue and space debris, hence it is desirable to retract the solar array before satellite repositioning to avoid damage or failure. Furthermore, to accommodate for today's technological world, the power demand of a modern LEO satellite is rapidly increasing, which consequently provides pressure upon the design of the satellites solar array system to conform to the strict volume and mass limitations. A novel concept of deployable/retractable hybrid solar array system, aimed to provide a greater power to volume ratio while dramatically reducing the disadvantages of system mass and cost is proposed. Taking advantage of the new lightweight technology in solar panels, a mechanical system composed of both rigid and flexible solar panels arranged within a petal formation is proposed to yield a stowed to deployment area ratio up to at least 1:7, which improves the power density dramatically. The system consists of five subsystems, the outer ones based on a novel eight-petal configuration that provides a large surface and supports the flexible solar panels. A single cable and spool based hinge mechanism were designed to synchronously deploy/retract the panels in a safe, simple and efficient manner while the mass compared to the previous systems is considerably reduced. The relevant challenge to assure a smooth movement is resolved by a proper minimization of the gearing system and the use of a micro-controller system. A prototype was designed by 3D simulators and successfully constructed and tested. Further design works are in progress to implement an epicyclical gear hinge mechanism, which will further reduce the volume, mass and complexity of the system significantly. The proposed system due to an effective and reliable mechanism provides a large active surface, whilst being very compact. It could be extremely advantageous for use as ground portable solar panel system.

Keywords: mechatronic engineering, satellite, solar panel, deployable/retractable mechanism

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Authors: Omolola Ojetayo, Emmanuel Garuba, Obinna Ajunwa, Abiodun A. Onilude

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Introduction: Biofilm is a functional community of microorganisms that are associated with a surface or an interface. These adherent cells become embedded within an extracellular matrix composed of polymeric substances, i.e., biofilms refer to biological deposits consisting of both microbes and their extracellular products on biotic and abiotic surfaces. Despite their detrimental effects in medicine, biofilms as natural cell immobilization have found several applications in biotechnology, such as in the treatment of wastewater, bioremediation and biodegradation, desulfurization of gas, and conversion of agro-derived materials into alcohols and organic acids. The means of enhancing immobilized cells have been chemical-inductive, and this affects the medium composition and final product. Physical factors including electrical, magnetic, and electromagnetic flux have shown potential for enhancing biofilms depending on the bacterial species, nature, and intensity of emitted signals, the duration of exposure, and substratum used. However, the concept of cell immobilisation by electrical and magnetic induction is still underexplored. Methods: To assess the effects of physical factors on biofilm formation, six American typed culture collection (Acetobacter aceti ATCC15973, Pseudomonas aeruginosa ATCC9027, Serratia marcescens ATCC14756, Gluconobacter oxydans ATCC19357, Rhodobacter sphaeroides ATCC17023, and Bacillus subtilis ATCC6633) were used. Standard culture techniques for bacterial cells were adopted. Natural autoimmobilisation potentials of test bacteria were carried out by simple biofilms ring formation on tubes, while crystal violet binding assay techniques were adopted in the characterisation of biofilm quantity. Electroinduction of bacterial cells by direct current (DC) application in cell broth, static magnetic field exposure, and electromagnetic flux were carried out, and autoimmobilisation of cells in a biofilm pattern was determined on various substrata tested, including wood, glass, steel, polyvinylchloride (PVC) and polyethylene terephthalate. Biot Savart law was used in quantifying magnetic field intensity, and statistical analyses of data obtained were carried out using the analyses of variance (ANOVA) as well as other statistical tools. Results: Biofilm formation by the selected test bacteria was enhanced by the physical factors applied. Electromagnetic induction had the greatest effect on biofilm formation, with magnetic induction producing the least effect across all substrata used. Microbial cell-cell communication could be a possible means via which physical signals affected the cells in a polarisable manner. Conclusion: The enhancement of biofilm formation by bacteria using physical factors has shown that their inherent capability as a cell immobilization method can be further optimised for industrial applications. A possible relationship between the presence of voltage-dependent channels, mechanosensitive channels, and bacterial biofilms could shed more light on this phenomenon.

Keywords: bacteria, biofilm, cell immobilization, electromagnetic induction, substrata

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Authors: Yakup Sahin, Naim Suleyman Ting, Ismail Aksoy

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In this paper, an improved active snubber cell is proposed on account of soft switching (SS) family of pulse width modulation (PWM) DC-DC converters. The improved snubber cell provides zero-voltage transition (ZVT) turn on and zero-current transition (ZCT) turn off for main switch. The snubber cell decreases EMI noise and operates with SS in a wide range of line and load voltages. Besides, all of the semiconductor devices in the converter operate with SS. There is no additional voltage and current stress on the main devices. Additionally, extra voltage stress does not occur on the auxiliary switch and its current stress is acceptable value. The improved converter has a low cost and simple structure. The theoretical analysis of converter is clarified and the operating states are given in detail. The experimental results of converter are obtained by prototype of 500 W and 100 kHz. It is observed that the experimental results and theoretical analysis of converter are suitable with each other perfectly.

Keywords: active snubber cells, DC-DC converters, zero-voltage transition, zero-current transition

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Authors: Oveis Abedinia, Noradin Ghadimi, Nasser Mikaeilvand, Roza Poursoleiman, Asghar Poorfaraj

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In this paper a robust Fuzzy Proportional Integral Differential (PID) controller is applied to multi-machine power system based on Modified Shuffled Frog Leaping (MSFL) algorithm. This newly proposed controller is more efficient because it copes with oscillations and different operating points. In this strategy the gains of the PID controller is optimized using the proposed technique. The nonlinear problem is formulated as an optimization problem for wide ranges of operating conditions using the MSFL algorithm. The simulation results demonstrate the effectiveness, good robustness and validity of the proposed method through some performance indices such as ITAE and FD under wide ranges operating conditions in comparison with TS and GSA techniques. The single-machine infinite bus system and New England 10-unit 39-bus standard power system are employed to illustrate the performance of the proposed method.

Keywords: fuzzy PID, MSFL, multi-machine, low frequency oscillation

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Authors: Rodrigo Arnaldo Scarpel

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Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

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Authors: Fengmei Li, Li Xu, Guoliang Xia

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Whey acidic proteins (WAP) domain-containing proteins in crustacean are involved in innate immune response against microbial invasion. In the present study, a novel double WAP domain (DWD)-containing protein gene 3 was identified from Chinese mitten crab Eriocheir sinensis (designated EsDWD3) by expressed sequence tag (EST) analysis and PCR techniques. The full-length cDNA of EsDWD3 was of 1223 bp, consisting of a 5′-terminal untranslated region (UTR) of 74 bp, a 3′ UTR of 727 bp with a polyadenylation signal sequence AATAAA and a polyA tail, and an open reading frame (ORF) of 423 bp. The ORF encoded a polypeptide of 140 amino acids with a signal peptide of 22 amino acids. The deduced protein sequence EsDWD3 showed 96.4 % amino acid similar to other reported EsDWD1 from E. sinensis, and phylogenetic tree analysis revealed that EsDWD3 had closer relationships with the reported two double WAP domain-containing proteins of E. sinensis species.

Keywords: Chinese mitten crab, Eriocheir sinensis, cloning, double WAP domain-containing protein

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Authors: Thierry Pauporté, Sana Koussi, Fabrice Odobel

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The preparation of semiconductor oxide layers and structures by soft techniques is an important field of research. Higher performances are expected from the optimizing of the oxide films and then use of new methods of preparation for a better control of their chemical, morphological, electrical and optical properties. We present the preparation of NiO by electrodeposition from pure polar aprotic medium and mixtures with water. The effect of the solvent, of the electrochemical deposition parameters and post-deposition annealing treatment on the structural, morphological and optical properties of the films is investigated. We remarkably show that the solvent is inserted in the deposited layer and act as a blowing agent, giving rise to mesoporous films after elimination by thermal annealing. These layers of p-type oxide have been successfully used, after sensitization by a dye, in p-type dye-sensitized solar cells. The effects of the solvent on the layer properties and the application of these layers in p-type dye-sensitized solar cells are described.

Keywords: NiO, layer, p-type sensitized solar cells, electrodeposition

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Authors: Rajkumar Ghosh

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Water scarcity is a significant challenge in urban areas, even in smart cities (Lucknow, Bangalore, Jaipur, etc.) where efficient resource management is prioritized. The depletion of groundwater resources in Gomti Nagar, Lucknow, Uttar Pradesh, India is particularly severe, posing a significant challenge for sustainable development in the region. This study focuses on addressing the water shortage by investigating the effectiveness of rooftop rainwater harvesting systems (RTRWHs) as a sustainable approach to bridge the gap between groundwater recharge and extraction. The aim of this study is to assess the effectiveness of RTRWHs in reducing aquifer depletion and addressing the water scarcity issue in the Gomti Nagar region. The research methodology involves the utilization of RTRWHs as the primary method for collecting rainwater. RTRWHs will be implemented in residential and commercial buildings to maximize the collection of rainwater. Data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. Statistical analysis and modelling techniques were employed to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. The study reveals that the installation of RTRWHs in the Gomti Nagar region has a positive impact on addressing the water scarcity issue. Currently, RTRWHs cover only a small percentage of the total rainfall collected in the region. However, when RTRWHs are installed in all buildings, their influence on increasing water availability and reducing aquifer depletion will be significantly greater. The study also highlights the significant water imbalance in the region, emphasizing the urgent need for sustainable water management practices. This research contributes to the theoretical understanding of sustainable water management systems in smart cities. By highlighting the effectiveness of RTRWHs in reducing aquifer depletion, it emphasizes the importance of implementing such systems in urban areas. Data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. The collected data were then analysed using statistical analysis and modelling techniques to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. The findings of this study demonstrate that the implementation of RTRWHs can effectively mitigate the water scarcity crisis in Gomti Nagar. By reducing aquifer depletion and bridging the gap between groundwater recharge and extraction, RTRWHs offer a sustainable solution to the region's water scarcity challenges. Widespread adoption of RTRWHs in all buildings and integration into urban planning and development processes are crucial for efficient water management in smart cities like Gomti Nagar. These findings can serve as a basis for policymakers, urban planners, and developers to prioritize and incentivize the installation of RTRWHs as a potential solution to the water shortage crisis.

Keywords: water scarcity, urban areas, smart cities, resource management, groundwater depletion, rooftop rainwater harvesting systems, sustainable development, sustainable water management, mitigating water scarcity

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Authors: Athena Nguyen, Rojin Belganeh

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Detecting and identifying differences in like polymer materials are key factors in failure and deformulation analysis, and reverse engineering. Pyrolysis-GC/MS is an easy solid sample introduction technique which expands the application areas of gas chromatography and mass spectrometry. The Micro furnace pyrolyzer is directly interfaced with the GC injector preventing any potential of cold spot, carryover, and cross contamination. In this presentation, the analysis of the differences in three polystyrene samples is demonstrated. Although the three samples look very similar by Evolve gas analysis (EGA) and Flash pyrolysis, there are indications of small levels of other materials. By performing Thermal desorption-GC/MS, the additive compounds between samples show the differences. EGA, flash pyrolysis, and thermal desorption analysis are the different modes of operations of the micro-furnace pyrolyzer enabling users to perform multiple analytical techniques.

Keywords: Gas chromatography/Mass spectrometry, pyrolysis, pyrolyzer, thermal desorption-GC/MS

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Authors: Burcu Oralhan, Zeki Oralhan, Nilsun Sariyer, Kumru Uyar

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Data mining has been becoming more and more important and a wide range of applications in recent years. Data mining is the process of find hidden and unknown patterns in big data. One of the applied fields of data mining is Customer Relationship Management. Understanding the relationships between products and customers is crucial for every business. Customer Relationship Management is an approach to focus on customer relationship development, retention and increase on customer satisfaction. In this study, we made an application of a data mining methods in telecommunication customer relationship management side. This study aims to determine the customers profile who likely to leave the system, develop marketing strategies, and customized campaigns for customers. Data are clustered by applying classification techniques for used to determine the churners. As a result of this study, we will obtain knowledge from international telecommunication industry. We will contribute to the understanding and development of this subject in Customer Relationship Management.

Keywords: customer churn analysis, customer relationship management, data mining, telecommunication industry

Procedia PDF Downloads 321

Authors: Farid Habibi Tanha, Mojtaba Jahanbazi, Morteza Foroutan, Rasidah Mohd Rashid

Abstract:

This paper depicts the effects of asymmetric information in determining capital inflows to be captured through stock market microstructure. The model can explain several stylized facts regarding the capital immobility. The first phase of the research involves in collecting and refining 150,000,000 daily data of 11 stock markets over a period of one decade in an effort to minimize the impact of survivorship bias. Three micro techniques were used to measure information asymmetries. The final phase analyzes the model through panel data approach. As a unique contribution, this research will provide valuable information regarding negative effects of information asymmetries in stock markets on attracting foreign investments. The results of this study can be directly considered by policy makers to monitor and control changes of capital flow in order to keep market conditions in a healthy manner, by preventing and managing possible shocks to avoid sudden reversals and market failures.

Keywords: asymmetric information, capital inflow, market microstructure, investment

Procedia PDF Downloads 323

Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

Abstract:

Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

Procedia PDF Downloads 277

Authors: F. Allag, S. Bouharati, M. Belmahdi, R. Zegadi

Abstract:

The rapid expansion of deserts in recent decades as a result of human actions combined with climatic changes has highlighted the necessity to understand biological processes in arid environments. Whereas physical processes and the biology of flora and fauna have been relatively well studied in marginally used arid areas, knowledge of desert soil micro-organisms remains fragmentary. The objective of this study is to conduct a diversity analysis of bacterial communities in unvegetated arid soils. Several biological phenomena in hot deserts related to microbial populations and the potential use of micro-organisms for restoring hot desert environments. Dry land ecosystems have a highly heterogeneous distribution of resources, with greater nutrient concentrations and microbial densities occurring in vegetated than in bare soils. In this work, we found it useful to use techniques of artificial intelligence in their treatment especially artificial neural networks (ANN). The use of the ANN model, demonstrate his capability for addressing the complex problems of uncertainty data.

Keywords: desert soil, climatic changes, bacteria, vegetation, artificial neural networks

Procedia PDF Downloads 401

Authors: Sujay Kotwale, Ramasubba Reddy M.

Abstract:

Electrocardiogram (ECG) is a non-invasive technique used to study and analyze various heart diseases. Cardiac arrhythmia is a serious heart disease which leads to death of the patients, when left untreated. An early-time detection of cardiac arrhythmia would help the doctors to do proper treatment of the heart. In the past, various algorithms and machine learning (ML) models were used to early-time detection of cardiac arrhythmia, but few of them have achieved better results. In order to improve the performance, this paper implements principal component analysis (PCA) along with XGBoost model. The PCA was implemented to the raw ECG signals which suppress redundancy information and extracted significant features. The obtained significant ECG features were fed into XGBoost model and the performance of the model was evaluated. In order to valid the proposed technique, raw ECG signals obtained from standard MIT-BIH database were employed for the analysis. The result shows that the performance of proposed method is superior to the several state-of-the-arts techniques.

Keywords: cardiac arrhythmia, electrocardiogram, principal component analysis, XGBoost

Procedia PDF Downloads 125

Authors: Akanksha Singh, Mahesh Kumar, Shailesh N. Sharma

Abstract:

Semiconductor quantum dots (QDs) such as CdSe, CdS, InP, etc. have gained significant interest in the recent years due to its application in various fields such as LEDs, solar cells, lasers, biological markers, etc. The interesting feature of the QDs is their tunable band gap. The size of the QDs can be easily varied by varying the synthesis parameters which change the band gap. One of the limitations with II-VI semiconductor QDs is their biological application. The use of cadmium makes them unsuitable for biological applications. III-V QD such as InP overcomes this problem as they are structurally robust because of the covalent bonds which do not allow the ions to leak. Also, InP QDs has large Bohr radii which increase the window for the quantum confinement effect. The synthesis of InP QDs is difficult and time consuming. Authors have synthesized InP using a novel, quick synthesis method which utilizes trioctylphosphine as a source of phosphorus. In this work, authors have made InP composites with P3HT(Poly(3-hexylthiophene-2,5-diyl))polymer(organic-inorganic hybrid material) and gold nanoparticles(metal-semiconductor composites). InP-P3HT shows FRET phenomenon whereas InP-Au shows charge transfer mechanism. The synthesized InP QDs has an absorption band at 397 nm and PL peak position at 491 nm. The band gap of the InP QDs is 2.46 eV as compared to the bulk band gap of InP i.e. 1.35 eV. The average size of the QDs is around 3-4 nm. In order to protect the InP core, a shell of wide band gap material i.e. ZnS is coated on the top of InP core. InP-P3HT composites were made in order to study the charge transfer/energy transfer phenomenon between them. On adding aliquots of P3HT to InP QDs solution, the P3HT PL increases which can be attributed to the dominance of Förster energy transfer between InP QDs (donor) P3HT polymer (acceptor). There is a significant spectral overlap between the PL spectra of InP QDs and absorbance spectra of P3HT. But in the case of InP-Au nanocomposites, significant charge transfer was seen from InP QDs to Au NPs. When aliquots of Au NPs were added to InP QDs, a decrease in the PL of the InP QDs was observed. This is due to the charge transfer from the InP QDs to the Au NPs. In the case of metal semiconductor composites, the enhancement and quenching of QDs depend on the size of the QD and the distance between the QD and the metal NP. These two composites have different phenomenon between donor and acceptor and hence can be utilized for two different applications. The InP-P3HT composite can be utilized for LED devices due to enhancement in the PL emission (FRET). The InP-Au can be utilized efficiently for photovoltaic application owing to the successful charge transfer between InP-Au NPs.

Keywords: charge transfer, FRET, gold nanoparticles, InP quantum dots

Procedia PDF Downloads 152

Authors: Hyun-Woo Cho

Abstract:

The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

Procedia PDF Downloads 562

Authors: Burak Kaplan, Ünver Kaynak

Abstract:

Gas turbine engines, crucial for modern aviation and power generation, rely on the efficient operation of turbine blades. However, extreme temperatures and pressures can lead to material degradation and failure. Film cooling, a widely employed technique, injects a coolant onto the blade surface to mitigate the effects of hot gas exposure. This research investigates the impact of film cooling on gas turbine engine performance, focusing on its influence on efficiency, longevity, and overall engine performance. Through a comprehensive literature review, computational fluid dynamics simulations, and thermal performance analysis, this study aims to provide insights into optimizing film cooling configurations for enhanced engine performance. The research explores the thermal performance characteristics of turbine blades with and without film cooling, the influence of various film cooling techniques on engine efficiency, and the design factors that optimize film cooling effectiveness. The findings of this study have the potential to contribute to the development of more efficient and reliable gas turbine engines, ultimately advancing the field of gas turbine technology.

Keywords: gas turbine, engine, cooling, blade, optimization

Procedia PDF Downloads 17