Search results for: resilient propagation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1155

Search results for: resilient propagation

465 Modeling the Saltatory Conduction in Myelinated Axons by Order Reduction

Authors: Ruxandra Barbulescu, Daniel Ioan, Gabriela Ciuprina

Abstract:

The saltatory conduction is the way the action potential is transmitted along a myelinated axon. The potential diffuses along the myelinated compartments and it is regenerated in the Ranvier nodes due to the ion channels allowing the flow across the membrane. For an efficient simulation of populations of neurons, it is important to use reduced order models both for myelinated compartments and for Ranvier nodes and to have control over their accuracy and inner parameters. The paper presents a reduced order model of this neural system which allows an efficient simulation method for the saltatory conduction in myelinated axons. This model is obtained by concatenating reduced order linear models of 1D myelinated compartments and nonlinear 0D models of Ranvier nodes. The models for the myelinated compartments are selected from a series of spatially distributed models developed and hierarchized according to their modeling errors. The extracted model described by a nonlinear PDE of hyperbolic type is able to reproduce the saltatory conduction with acceptable accuracy and takes into account the finite propagation speed of potential. Finally, this model is again reduced in order to make it suitable for the inclusion in large-scale neural circuits.

Keywords: action potential, myelinated segments, nonlinear models, Ranvier nodes, reduced order models, saltatory conduction

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464 Stochastic Richelieu River Flood Modeling and Comparison of Flood Propagation Models: WMS (1D) and SRH (2D)

Authors: Maryam Safrai, Tewfik Mahdi

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This article presents the stochastic modeling of the Richelieu River flood in Quebec, Canada, occurred in the spring of 2011. With the aid of the one-dimensional Watershed Modeling System (WMS (v.10.1) and HEC-RAS (v.4.1) as a flood simulator, the delineation of the probabilistic flooded areas was considered. Based on the Monte Carlo method, WMS (v.10.1) delineated the probabilistic flooded areas with corresponding occurrence percentages. Furthermore, results of this one-dimensional model were compared with the results of two-dimensional model (SRH-2D) for the evaluation of efficiency and precision of each applied model. Based on this comparison, computational process in two-dimensional model is longer and more complicated versus brief one-dimensional one. Although, two-dimensional models are more accurate than one-dimensional method, but according to existing modellers, delineation of probabilistic flooded areas based on Monte Carlo method is achievable via one-dimensional modeler. The applied software in this case study greatly responded to verify the research objectives. As a result, flood risk maps of the Richelieu River with the two applied models (1d, 2d) could elucidate the flood risk factors in hydrological, hydraulic, and managerial terms.

Keywords: flood modeling, HEC-RAS, model comparison, Monte Carlo simulation, probabilistic flooded area, SRH-2D, WMS

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463 Modeling the Elastic Mean Free Path of Electron Collision with Pyrimidine: The Screen Corrected Additivity Rule Method

Authors: Aouina Nabila Yasmina, Chaoui Zine El Abiddine

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This study presents a comprehensive investigation into the elastic mean free path (EMFP) of electrons colliding with pyrimidine, a precursor to the pyrimidine bases in DNA, employing the Screen Corrected Additivity Rule (SCAR) method. The SCAR method is introduced as a novel approach that combines classical and quantum mechanical principles to elucidate the interaction of electrons with pyrimidine. One of the most fundamental properties characterizing the propagation of a particle in the nuclear medium is its mean free path. Knowledge of the elastic mean free path is essential to accurately predict the effects of radiation on biological matter, as it contributes to the distances between collisions. Additionally, the mean free path plays a role in the interpretation of almost all experiments in which an excited electron moves through a solid. Pyrimidine, the precursor of the pyrimidine bases of DNA, has interesting physicochemical properties, which make it an interesting molecule to study from a fundamental point of view. These include a relatively large dipole polarizability and dipole moment and an electronic charge cloud with a significant spatial extension, which justifies its choice in this present study.

Keywords: elastic mean free path, elastic collision, pyrimidine, SCAR

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462 Designing and Analyzing Sensor and Actuator of a Nano/Micro-System for Fatigue and Fracture Characterization of Nanomaterials

Authors: Mohammad Reza Zamani Kouhpanji

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This paper presents a MEMS/NEMS device for fatigue and fracture characterization of nanomaterials. This device can apply static loads, cyclic loads, and their combinations in nanomechanical experiments. It is based on the electromagnetic force induced between paired parallel wires carrying electrical currents. Using this concept, the actuator and sensor parts of the device were designed and analyzed while considering the practical limitations. Since the PWCC device only uses two wires for actuation part and sensing part, its fabrication process is extremely easier than the available MEMS/NEMS devices. The total gain and phase shift of the MEMS/NEMS device were calculated and investigated. Furthermore, the maximum gain and sensitivity of the MEMS/NEMS device were studied to demonstrate the capability and usability of the device for wide range of nanomaterials samples. This device can be readily integrated into SEM/TEM instruments to provide real time study of the mechanical behaviors of nanomaterials as well as their fatigue and fracture properties, softening or hardening behaviors, and initiation and propagation of nanocracks.

Keywords: sensors and actuators, MEMS/NEMS devices, fatigue and fracture nanomechanical testing device, static and cyclic nanomechanical testing device

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461 Filler Elastomers Abrasion at Steady State: Optimal Use Conditions

Authors: Djeridi Rachid, Ould Ouali Mohand

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The search of a mechanism for the elastomer abrasive wear study is an open issue. The practice difficulties are complex due to the complexity of deformation mechanism, to the complex mechanism of the material tearing and to the marked interactions between the tribological parameters. In this work, we present an experimental technique to study the elastomers abrasive wear. The interaction 'elastomer/indenter' implicate dependant ant temporary of different tribological parameters. Consequently, the phenomenon that governs this interaction is not easy to explain. An optimal elastomers compounding and an adequate utilization conditions of these materials that define its resistance at the abrasion is discussed. The results are confronted to theoretical models: the weight loss variation in function of blade angle or in function of cycle number is in agreement with rupture models and with the mechanism of fissures propagation during the material tearing in abrasive wear of filler elastomers. The weight loss in function of the sliding velocity shows the existence of a critical velocity that corresponds to the maximal wear. The adding of silica or black carbon influences in a different manner on wear abrasive behavior of filler elastomers.

Keywords: abrasion wear, filler elastomer, tribology, hyperelastic

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460 Comfort Needs and Energy Practices in Low-Income, Tropical Housing from a Socio-Technical Perspective

Authors: Tania Sharmin

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Energy use, overheating and thermal discomfort in low-income tropical housing remains an under-researched area. This research attempts to explore these aspects in the Loving Community, a housing colony created for former leprosy patients and their families in Ahmedabad in India. The living conditions in these households and working practices of the inhabitants in terms of how the building and its internal and external spaces are used, will be explored through interviews and monitoring which will be based on a household survey and a focus group discussion (FGD). The findings from the study will provide a unique and in-depth account of how the relocation of the affected households to the new, flood-resistant and architecturally-designed buildings may have affected the dwellers’ household routines (health and well-being, comfort, satisfaction and working practices) and overall living conditions compared to those living in poorly-designed, existing low-income housings. The new houses were built under an innovative building project supported by De Montfort University Leicester (DMU)’s Square Mile India project. A comparison of newly-built and existing building typologies will reveal how building design can affect people’s use of space and energy use. The findings will be helpful to design healthier, energy efficient and socially acceptable low-income housing in future, thus addressing United Nation’s sustainable development goals on three aspects: 3 (health and well-being), 7 (energy) and 11 (safe, resilient and sustainable human settlements). This will further facilitate knowledge exchange between policy makers, developers, designers and occupants focused on strategies to increase stakeholders’ participation in the design process.

Keywords: thermal comfort, energy use, low-income housing, tropical climate

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459 A Comprehensive Approach to Sustainable Building Design: Bridging Design for Adaptability and Circular Economy with LCA

Authors: Saba Baienat, Ivanka Iordanova, Bechara Helal

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Incorporating the principles of Design for Adaptability (DfAd) and Circular Economy (CE) into the service life planning of buildings and construction engineering projects can significantly enhance sustainable development. By employing DfAd, both the service life and design process can be optimized, gradually postponing the building’s End of Life (EoL) and extending the service life of buildings, thereby closing material cycles and making them more circular. This paper presents a comprehensive framework that addresses adaptability strategies and considerations to objectively assess the role of DfAd in circularity. The framework aims to provide a streamlined approach for accessing DfAd strategies and identifying the most effective ones for enhancing a project's adaptability. Key strategies include anticipating changes in requirements, enabling adaptations and transformations of the building for better use and reuse, preparing for future lives of the building and its components, and contributing to the circular material life cycle. Furthermore, the framework seeks to enhance the awareness of stakeholders about the subject of Design for Adaptability through the lens of the Circular Economy. Additionally, this paper integrates Life Cycle Assessment (LCA) methodologies to evaluate the environmental impacts of implementing DfAd strategies within the context of the Circular Economy. By utilizing LCA, the framework provides a quantitative basis for assessing the sustainability benefits of adaptable building designs, offering insights into how these strategies can minimize resource consumption, reduce emissions, and enhance overall environmental performance. This holistic approach underscores the critical role of LCA in bridging DfAd and CE, ultimately fostering more resilient and sustainable construction practices.

Keywords: circular economy (CE), design for adaptability (DfAd), life cycle assessment (LCA), sustainable development

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458 Conduction Accompanied With Transient Radiative Heat Transfer Using Finite Volume Method

Authors: A. Ashok, K.Satapathy, B. Prerana Nashine

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The objective of this research work is to investigate for one dimensional transient radiative transfer equations with conduction using finite volume method. Within the infrastructure of finite-volume, we obtain the conservative discretization of the terms in order to preserve the overall conservative property of finitevolume schemes. Coupling of conductive and radiative equation resulting in fluxes is governed by the magnitude of emissivity, extinction coefficient, and temperature of the medium as well as geometry of the problem. The problem under consideration has been solved, for a slab dominating radiation coupled with transient conduction based on finite volume method. The boundary conditions are also chosen so as to give a good model of the discretized form of radiation transfer equation. The important feature of the present method is flexibility in specifying the control angles in the FVM, while keeping the simplicity in the solution procedure. Effects of various model parameters are examined on the distributions of temperature, radiative and conductive heat fluxes and incident radiation energy etc. The finite volume method is considered to effectively evaluate the propagation of radiation intensity through a participating medium.

Keywords: participating media, finite volume method, radiation coupled with conduction, transient radiative heat transfer

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457 Neural Networks-based Acoustic Annoyance Model for Laptop Hard Disk Drive

Authors: Yichao Ma, Chengsiong Chin, Wailok Woo

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Since the last decade, there has been a rapid growth in digital multimedia, such as high-resolution media files and three-dimentional movies. Hence, there is a need for large digital storage such as Hard Disk Drive (HDD). As such, users expect to have a quieter HDD in their laptop. In this paper, a jury test has been conducted on a group of 34 people where 17 of them are students who is the potential consumer, and the remaining are engineers who know the HDD. A total 13 HDD sound samples have been selected from over hundred HDD noise recordings. These samples are selected based on an agreed subjective feeling. The samples are played to the participants using head acoustic playback system which enabled them to experience as similar as possible the same environment as have been recorded. Analysis has been conducted and the obtained results have indicated different group has different perception over the noises. Two neural network-based acoustic annoyance models are established based on back propagation neural network. Four psychoacoustic metrics, loudness, sharpness, roughness and fluctuation strength, are used as the input of the model, and the subjective evaluation results are taken as the output. The developed models are reasonably accurate in simulating both training and test samples.

Keywords: hdd noise, jury test, neural network model, psychoacoustic annoyance

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456 Hot-Dip Galvanizing as a Corrosion Protection System for Steel Hydraulic Structures

Authors: Farrokh Taherkhani, Thomas Pinger, Max Gündel

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Corrosion and suitable corrosion protection systems are a significant factor in the consideration of life cycle costs for steel hydraulic structures. In addition to classic coating systems (for example, epoxy resin or polyurethane), zinc and its alloys offer effective and very durable corrosion protection for steels. As a protective layer, hot-dip galvanizing prevents the corrosive media from penetrating into the steel matrix and acts as a sacrificial anode, which corrodes in preference to steel. However, hot-dip galvanizing as a corrosion protection system has not yet been approved by the relevant authority, the Federal Waterways Engineering and Research Institute (BAW) in Germany. In order to make hot-dip galvanizing usable as a corrosion protection system for steel hydraulic structures in the future, different factors must be considered. These factors are (i) corrosion protection type, (ii) resistance to mechanical stress (i.e., abrasion resistance), (iii) combinability with cathodic corrosion protection, (iv) environmental effects, and (v) the crack formation and propagation during hot-dip galvanizing. In this work, hot-dip galvanizing as a corrosion protection system for steel hydraulic steel structures, as well as open questions, are discussed. This paper is based on initial long-term exposure tests with corrosion protection systems consisting of hot-dip galvanizing and duplex systems.

Keywords: steel hydraulic structure, hot-dip galvanizing, corrosion resistance, zinc coating, organic coating and duplex systems

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455 Analytic Solutions of Solitary Waves in Three-Level Unbalanced Dense Media

Authors: Sofiane Grira, Hichem Eleuch

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We explore the analytical soliton-pair solutions for unbalanced coupling between the two coherent lights and the atomic transitions in a dissipative three-level system in lambda configuration. The two allowed atomic transitions are interacting resonantly with two laser fields. For unbalanced coupling, it is possible to derive an explicit solution for non-linear differential equations describing the soliton-pair propagation in this three-level system with the same velocity. We suppose that the spontaneous emission rates from the excited state to both ground states are the same. In this work, we focus on such case where we consider the coupling between the transitions and the optical fields are unbalanced. The existence conditions for the soliton-pair propagations are determined. We will show that there are four possible configurations of the soliton-pair pulses. Two of them can be interpreted as a couple of solitons with same directions of polarization and the other two as soliton-pair with opposite directions of polarization. Due to the fact that solitons have stable shapes while propagating in the considered media, they are insensitive to noise and dispersion. Our results have potential applications in data transfer with the soliton-pair pulses, where a dissipative three-level medium could be a realistic model for the optical communication media.

Keywords: non-linear differential equations, solitons, wave propagations, optical fiber

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454 Energy Storage in the Future of Ethiopia Renewable Electricity Grid System

Authors: Dawit Abay Tesfamariam

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Ethiopia’s Climate- Resilient Green Economy strategy focuses mainly on generating and utilization of Renewable Energy (RE). The data collected in 2016 by Ethiopian Electric Power (EEP) indicates that the intermittent RE sources on the grid from solar and wind energy were only 8 % of the total energy produced. On the other hand, the EEP electricity generation plan in 2030 indicates that 36 % of the energy generation share will be covered by solar and wind sources. Thus, a case study was initiated to model and compute the balance and consumption of electricity in three different scenarios: 2016, 2025, and 2030 using the Energy PLAN Model (EPM). Initially, the model was validated using the 2016 annual power-generated data to conduct the EPM analysis for two predictive scenarios. The EPM simulation analysis using EPM for 2016 showed that there was no significant excess power generated. Hence, the model’s results are in line with the actual 2016 output. Thus, the EPM was applied to analyze the role of energy storage in RE in Ethiopian grid systems. The results of the EPM simulation analysis showed there will be excess production of 402 /7963 MW average and maximum, respectively, in 2025. The excess power was dominant in all months except in the three rainy months of the year (June, July, and August). Consequently, based on the validated outcomes of EPM indicates, there is a good reason to think about other alternatives for the utilization of excess energy and storage of RE. Thus, from the scenarios and model results obtained, it is realistic to infer that; if the excess power is utilized with a storage mechanism that can stabilize the grid system; as a result, the extra RE generated can be exported to support the economy. Therefore, researchers must continue to upgrade the current and upcoming energy storage system to synchronize with RE potentials that can be generated from RE.

Keywords: renewable energy, storage, wind, energyplan

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453 Predictive Modeling of Bridge Conditions Using Random Forest

Authors: Miral Selim, May Haggag, Ibrahim Abotaleb

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The aging of transportation infrastructure presents significant challenges, particularly concerning the monitoring and maintenance of bridges. This study investigates the application of Random Forest algorithms for predictive modeling of bridge conditions, utilizing data from the US National Bridge Inventory (NBI). The research is significant as it aims to improve bridge management through data-driven insights that can enhance maintenance strategies and contribute to overall safety. Random Forest is chosen for its robustness, ability to handle complex, non-linear relationships among variables, and its effectiveness in feature importance evaluation. The study begins with comprehensive data collection and cleaning, followed by the identification of key variables influencing bridge condition ratings, including age, construction materials, environmental factors, and maintenance history. Random Forest is utilized to examine the relationships between these variables and the predicted bridge conditions. The dataset is divided into training and testing subsets to evaluate the model's performance. The findings demonstrate that the Random Forest model effectively enhances the understanding of factors affecting bridge conditions. By identifying bridges at greater risk of deterioration, the model facilitates proactive maintenance strategies, which can help avoid costly repairs and minimize service disruptions. Additionally, this research underscores the value of data-driven decision-making, enabling better resource allocation to prioritize maintenance efforts where they are most necessary. In summary, this study highlights the efficiency and applicability of Random Forest in predictive modeling for bridge management. Ultimately, these findings pave the way for more resilient and proactive management of bridge systems, ensuring their longevity and reliability for future use.

Keywords: data analysis, random forest, predictive modeling, bridge management

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452 Empirical Green’s Function Technique for Accelerogram Synthesis: The Problem of the Use for Marine Seismic Hazard Assessment

Authors: Artem A. Krylov

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Instrumental seismological researches in water areas are complicated and expensive, that leads to the lack of strong motion records in most offshore regions. In the same time the number of offshore industrial infrastructure objects, such as oil rigs, subsea pipelines, is constantly increasing. The empirical Green’s function technique proved to be very effective for accelerograms synthesis under the conditions of poorly described seismic wave propagation medium. But the selection of suitable small earthquake record in offshore regions as an empirical Green’s function is a problem because of short seafloor instrumental seismological investigation results usually with weak micro-earthquakes recordings. An approach based on moving average smoothing in the frequency domain is presented for preliminary processing of weak micro-earthquake records before using it as empirical Green’s function. The method results in significant waveform correction for modeled event. The case study for 2009 L’Aquila earthquake was used to demonstrate the suitability of the method. This work was supported by the Russian Foundation of Basic Research (project № 18-35-00474 mol_a).

Keywords: accelerogram synthesis, empirical Green's function, marine seismology, microearthquakes

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451 Challenges of Landscape Design with Tree Species Diversity

Authors: Henry Kuppen

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In the last decade, tree managers have faced many threats of pests and diseases and the effects of climate change. Managers will recognize that they have to put more energy and more money into tree management. By recognizing the cause behind this, the opportunity will arise to build sustainable tree populations for the future. More and more, unwanted larvae are sprayed, ash dieback infected trees are pruned or felled, and emerald ash borer is knocking at the door of West Europe. A lot of specific knowledge is needed to produce management plans and best practices. If pest and disease have a large impact, society loses complete tree species and need to start all over again building urban forest. But looking at the cause behind it, landscape design, and tree species selection, the sustainable solution does not present itself in managing these threats. Every pest or disease needs two important basic ingredients to be successful: climate and food. The changing climate is helping several invasive pathogens to survive. Food is often designed by the landscapers and managers of the urban forest. Monocultures promote the success of pathogens. By looking more closely at the basics, tree managers will realise very soon that the solution will not be the management of pathogens. The long-term solution for sustainable tree populations is a different design of our urban landscape. The use of tree species diversity can help to reduce the impact of climate change and pathogens. Therefore landscapers need to be supported. They are the specialists in designing the landscape using design values like canopy volume, ecosystem services, and seasonal experience. It’s up to the species specialist to show what the opportunities are for different species that meet the desired interpretation of the landscape. Based on landscapers' criteria, selections can be made, including tree species related requirements. Through this collaboration and formation of integral teams, sustainable plant design will be possible.

Keywords: climate change, landscape design, resilient landscape, tree species selection

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450 Corporate Governance Development in Mongolia: The Role of Professional Accountants

Authors: Ernest Nweke

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The work of Professional Accountants and Corporate governance are synonymous and cannot be divorced from each other. Organizations, profit and non-profit alike cannot implement sound corporate practices without inputs from Professional Accountants. In today’s dynamic corporate world, good corporate governance practice is a sine qua non. More so, following the corporate failures of the past decades like Enron and WorldCom, governments around the world, including Mongolia are becoming more proactive in ensuring sound corporate governance mechanisms. In the past fifteen years, the Mongolian government has taken several measures to establish and strengthen internal corporate governance structures in firms. This paper highlights the role of professional accountants and auditors play in ensuring that good corporate governance mechanisms are entrenched in listed companies in Mongolia. Both primary and secondary data are utilized in this research. In collection of primary data, Delphi method was used, securing responses from only knowledgeable senior employees, top managers, and some CEOs. Using this method, a total of 107 top-level company employees and executives randomly selected from 22 companies were surveyed; maximum of 5 and minimum of 4 from each company. These companies cut across several sectors. It was concluded that Professional Accountants play key roles in setting and maintaining firm governance. They do this by ensuring full compliance with all the requirements of good and sound corporate governance, establishing reporting, monitoring and evaluating standards, assisting in the setting up of proper controls, efficient and effective audit systems, sound fraud risk management and putting in place an overall vision for the enterprise. Companies with effective corporate governance mechanisms are usually strong and fraud-resilient. It was also discovered that companies with big 4 audit firms tend to have better governance structures in Mongolia.

Keywords: accountants, corporate disclosure, corporate failure, corporate governance

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449 On the Cluster of the Families of Hybrid Polynomial Kernels in Kernel Density Estimation

Authors: Benson Ade Eniola Afere

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Over the years, kernel density estimation has been extensively studied within the context of nonparametric density estimation. The fundamental components of kernel density estimation are the kernel function and the bandwidth. While the mathematical exploration of the kernel component has been relatively limited, its selection and development remain crucial. The Mean Integrated Squared Error (MISE), serving as a measure of discrepancy, provides a robust framework for assessing the effectiveness of any kernel function. A kernel function with a lower MISE is generally considered to perform better than one with a higher MISE. Hence, the primary aim of this article is to create kernels that exhibit significantly reduced MISE when compared to existing classical kernels. Consequently, this article introduces a cluster of hybrid polynomial kernel families. The construction of these proposed kernel functions is carried out heuristically by combining two kernels from the classical polynomial kernel family using probability axioms. We delve into the analysis of error propagation within these kernels. To assess their performance, simulation experiments, and real-life datasets are employed. The obtained results demonstrate that the proposed hybrid kernels surpass their classical kernel counterparts in terms of performance.

Keywords: classical polynomial kernels, cluster of families, global error, hybrid Kernels, Kernel density estimation, Monte Carlo simulation

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448 Hybrid Beam-Forming Techniques for 6G Terahertz Communication: Challenges

Authors: Mridula Korde

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The terahertz band is the main pillar of 6G wireless communication system. It is difficult to meet the high data rate of 1Tbps by millimeter frequency support systems. The terahertz band suffers huge propagation loss limiting wireless distance. Terahertz band imposes ultra massive multiple input multiple output antenna (UM-MIMO) systems which produce high array gain with narrow beamforming. The conventional methods for MIMO beamforming are Analog and Digital beamforming. The fully digital beamforming methods utilize dedicated structure of DAC/ADC and RF chains. These structures increase hardware complexity and are power hungry. The analog beamforming structures utilize ADC/DAC with phase shifters with less hardware complexity but support less data rates. As a result, a hybrid beamforming method can be adapted for UM-MIMO systems. This paper will investigate challenges in hybrid beamforming architecture which will address the low spatial degrees of freedom (SDoF) limitation in Terahertz (THz) Communication. The flexible hardware connections are proposed, in order to switch the system in an adaptive manner so as to minimize the power requirements.

Keywords: 6G, terahertz communication, beamforming, challenges

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447 Interfacial Investigation and Chemical Bonding in Graphene Reinforced Alumina Ceramic Nanocomposites

Authors: Iftikhar Ahmad, Mohammad Islam

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Thermally exfoliated graphene nanomaterial was reinforced into Al2O3 ceramic and the nanocomposites were consolidated using rapid high-frequency induction heat sintering route. The resulting nanocomposites demonstrated higher mechanical properties due to efficient GNS incorporation and chemical interaction with the Al2O3 matrix grains. The enhancement in mechanical properties is attributed to (i) uniformly-dispersed GNS in the consolidated structure (ii) ability of GNS to decorate Al2O3 nanoparticles and (iii) strong GNS/Al2O3 chemical interaction during colloidal mixing and pullout/crack bridging toughening mechanisms during mechanical testing. The GNS/Al2O3 interaction during different processing stages was thoroughly examined by thermal and structural investigation of the interfacial area. The formation of an intermediate aluminum oxycarbide phase (Al2OC) via a confined carbothermal reduction reaction at the GNS/Al2O3 interface was observed using advanced electron microscopes. The GNS surface roughness improves GNS/Al2O3 mechanical locking and chemical compatibility. The sturdy interface phase facilitates efficient load transfer and delayed failure through impediment of crack propagation. The resulting nanocomposites, therefore, offer superior toughness.

Keywords: ceramics, nanocomposites, interfaces, nanostructures, electron microscopy, Al2O3

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446 Analytical Solution of Non–Autonomous Discrete Non-Linear Schrodinger Equation With Saturable Non-Linearity

Authors: Mishu Gupta, Rama Gupta

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It has been elucidated here that non- autonomous discrete non-linear Schrödinger equation is associated with saturable non-linearity through photo-refractive media. We have investigated the localized solution of non-autonomous saturable discrete non-linear Schrödinger equations. The similarity transformation has been involved in converting non-autonomous saturable discrete non-linear Schrödinger equation to constant-coefficient saturable discrete non-linear Schrödinger equation (SDNLSE), whose exact solution is already known. By back substitution, the solution of the non-autonomous version has been obtained. We have analysed our solution for the hyperbolic and periodic form of gain/loss term, and interesting results have been obtained. The most important characteristic role is that it helps us to analyse the propagation of electromagnetic waves in glass fibres and other optical wave mediums. Also, the usage of SDNLSE has been seen in tight binding for Bose-Einstein condensates in optical mediums. Even the solutions are interrelated, and its properties are prominently used in various physical aspects like optical waveguides, Bose-Einstein (B-E) condensates in optical mediums, Non-linear optics in photonic crystals, and non-linear kerr–type non-linearity effect and photo refracting medium.

Keywords: B-E-Bose-Einstein, DNLSE-Discrete non linear schrodinger equation, NLSE-non linear schrodinger equation, SDNLSE - saturable discrete non linear Schrodinger equation

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445 Adaptive Energy-Aware Routing (AEAR) for Optimized Performance in Resource-Constrained Wireless Sensor Networks

Authors: Innocent Uzougbo Onwuegbuzie

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Wireless Sensor Networks (WSNs) are crucial for numerous applications, yet they face significant challenges due to resource constraints such as limited power and memory. Traditional routing algorithms like Dijkstra, Ad hoc On-Demand Distance Vector (AODV), and Bellman-Ford, while effective in path establishment and discovery, are not optimized for the unique demands of WSNs due to their large memory footprint and power consumption. This paper introduces the Adaptive Energy-Aware Routing (AEAR) model, a solution designed to address these limitations. AEAR integrates reactive route discovery, localized decision-making using geographic information, energy-aware metrics, and dynamic adaptation to provide a robust and efficient routing strategy. We present a detailed comparative analysis using a dataset of 50 sensor nodes, evaluating power consumption, memory footprint, and path cost across AEAR, Dijkstra, AODV, and Bellman-Ford algorithms. Our results demonstrate that AEAR significantly reduces power consumption and memory usage while optimizing path weight. This improvement is achieved through adaptive mechanisms that balance energy efficiency and link quality, ensuring prolonged network lifespan and reliable communication. The AEAR model's superior performance underlines its potential as a viable routing solution for energy-constrained WSN environments, paving the way for more sustainable and resilient sensor network deployments.

Keywords: wireless sensor networks (WSNs), adaptive energy-aware routing (AEAR), routing algorithms, energy, efficiency, network lifespan

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444 Rational Approach to the Design of a Sustainable Drainage System for Permanent Site of Federal Polytechnic Oko: A Case Study for Flood Mitigation and Environmental Management

Authors: Fortune Chibuike Onyia, Femi Ogundeji Ayodele

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The design of a drainage system at the permanent site of Federal Polytechnic Oko in Anambra State is critical for mitigating flooding, managing surface runoff, and ensuring environmental sustainability. The design process employed a comprehensive analysis involving topographical surveys, hydraulic modeling, and the assessment of local soil types to ensure stability and efficient water conveyance. Proper slope gradients were considered to maintain adequate flow velocities and avoid sediment deposition, which could hinder long-term performance. From the result, the channel size estimated was 0.199m by 0.0199m and 0.0199m². This study proposed a channel size of 1.4m depth by 0.5m width and 0.7m², optimized to accommodate the anticipated peak flow resulting from heavy rainfall and storm-water events. This sizing is based on hydrological data, which takes into account rainfall intensity, runoff coefficients, and catchment area characteristics. The objective is to effectively convey storm-water while preventing overflow, erosion, and subsequent damage to infrastructure and properties. This sustainable approach incorporates provisions for maintenance and aligns with urban drainage standards to enhance durability and reliability. Implementing this drainage system will mitigate flood risks, safeguard campus facilities, improve overall water management, and contribute to the development of resilient infrastructure at Federal Polytechnic Oko.

Keywords: flood mitigation, drainage system, sustainable design, environmental management

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443 Methaheuristic Bat Algorithm in Training of Feed-Forward Neural Network for Stock Price Prediction

Authors: Marjan Golmaryami, Marzieh Behzadi

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Recent developments in stock exchange highlight the need for an efficient and accurate method that helps stockholders make better decision. Since stock markets have lots of fluctuations during the time and different effective parameters, it is difficult to make good decisions. The purpose of this study is to employ artificial neural network (ANN) which can deal with time series data and nonlinear relation among variables to forecast next day stock price. Unlike other evolutionary algorithms which were utilized in stock exchange prediction, we trained our proposed neural network with metaheuristic bat algorithm, with fast and powerful convergence and applied it in stock price prediction for the first time. In order to prove the performance of the proposed method, this research selected a 7 year dataset from Parsian Bank stocks and after imposing data preprocessing, used 3 types of ANN (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) to predict the closed price of stocks. Afterwards, this study engaged MATLAB to simulate 3 types of ANN, with the scoring target of mean absolute percentage error (MAPE). The results may be adapted to other companies stocks too.

Keywords: artificial neural network (ANN), bat algorithm, particle swarm optimization algorithm (PSO), stock exchange

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442 Implementing Teacher Students’ Coaching in Practical Periods of University Teacher Education: The Significance of Training Cultures

Authors: Rahm Sibylle

Abstract:

The core element in most European teacher training concepts consists in practical periods where teacher students may review the chosen profession before going on to their theoretical studies. In Germany, teacher students learn in practical studies about everyday teaching and learning in schools. Teacher students appreciate opportunities to explore school practice and to feel responsible for students’ learning. In practical studies, teacher students often idealize their teacher mentors (and consequently tend to imitate their teaching style) or contrarily feel disappointed about school practice. Concepts of empowerment through practical experience in school-based academic teacher training have to be developed. Our Swiss-German research project COPRA (Coaching in practical periods; funded by the Swiss National Science Foundation (SNF) and the German Research Foundation (DFG), aims at gaining resilient results about the effectiveness of (peer) coaching in practical school periods. To explore innovative ways of accompanying novice teachers in practical periods we consider different cultures of teacher training institutions. School cultures, including teachers’ beliefs and teaching traditions involve different training cultures as starting positions for our intervention study. In our qualitative study, we describe typologies of teacher training institutions by analyzing group discussions with teacher students, mentor teachers and university lecturers concerning participation, cooperation, and relationships. In our paper, we present the design of our intervention study, our coaching concept as well as typologies of teacher training cultures. We discuss opportunities for teacher students to learn through domain-specific (peer) coaching on the background of these typologies.

Keywords: teacher training (practical periods), teacher students' coaching, training cultures (typologies), COPRA (coaching in practical periods)

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441 Genomics Approach for Excavation of NAS Genes from Nutri Rich Minor Millet Crops: Transforming Perspective from Orphan Plants to Future Food Crops

Authors: Mahima Dubey, Girish Chandel

Abstract:

Minor millets are highly nutritious and climate resilient cereal crops. These features make them ideal candidates to excavate the physiology of the underlying mechanism. In an attempt to understand the basis of mineral nutrition in minor millets, a set of five Barnyard millet genotypes were analyzed for grain Fe and Zn content under contrasting Fe-Zn supply to identify genotypes proficient in tolerating mineral deficiency. This resulted in the identification of Melghat-1 genotype to be nutritionally superior with better ability to withstand deficiency. Expression analysis of several Nicotianamine synthase (NAS) genes showed that HvNAS1 and OsNAS2 genes were prominent in positively mediating mineral deficiency response in Barnyard millet. Further, strategic efforts were employed for fast-track identification of more effective orthologous NAS genes from Barnyard millet. This resulted in the identification of two genes namely EfNAS1 (orthologous to HvNAS1 of barley) and EfNAS2 (orthologous to OsNAS2 gene of rice). Sequencing and thorough characterization of these sequences revealed the presence of intact NAS domain and signature tyrosine and di-leucine motifs in their predicted proteins and thus established their candidature as functional NAS genes in Barnyard millet. Moreover, EfNAS1 showed structural superiority over previously known NAS genes and is anticipated to have role in more efficient metal transport. Findings of the study provide insight into Fe-Zn deficiency response and mineral nutrition in millets. This provides millets with a physiological edge over micronutrient deficient staple cereals such as rice in withstanding Fe-Zn deficiency and subsequently accumulating higher levels of Fe and Zn in millet grains.

Keywords: gene expression, micronutrient, millet, ortholog

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440 Analytical Modelling of Surface Roughness during Compacted Graphite Iron Milling Using Ceramic Inserts

Authors: Ş. Karabulut, A. Güllü, A. Güldaş, R. Gürbüz

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This study investigates the effects of the lead angle and chip thickness variation on surface roughness during the machining of compacted graphite iron using ceramic cutting tools under dry cutting conditions. Analytical models were developed for predicting the surface roughness values of the specimens after the face milling process. Experimental data was collected and imported to the artificial neural network model. A multilayer perceptron model was used with the back propagation algorithm employing the input parameters of lead angle, cutting speed and feed rate in connection with chip thickness. Furthermore, analysis of variance was employed to determine the effects of the cutting parameters on surface roughness. Artificial neural network and regression analysis were used to predict surface roughness. The values thus predicted were compared with the collected experimental data, and the corresponding percentage error was computed. Analysis results revealed that the lead angle is the dominant factor affecting surface roughness. Experimental results indicated an improvement in the surface roughness value with decreasing lead angle value from 88° to 45°.

Keywords: CGI, milling, surface roughness, ANN, regression, modeling, analysis

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439 Applying Neural Networks for Solving Record Linkage Problem via Fuzzy Description Logics

Authors: Mikheil Kalmakhelidze

Abstract:

Record linkage (RL) problem has become more and more important in recent years due to the growing interest towards big data analysis. The problem can be formulated in a very simple way: Given two entries a and b of a database, decide whether they represent the same object or not. There are two classical deterministic and probabilistic ways of solving the RL problem. Using simple Bayes classifier in many cases produces useful results but sometimes they show to be poor. In recent years several successful approaches have been made towards solving specific RL problems by neural network algorithms including single layer perception, multilayer back propagation network etc. In our work, we model the RL problem for specific dataset of student applications in fuzzy description logic (FDL) where linkage of specific pair (a,b) depends on the truth value of corresponding formula A(a,b) in a canonical FDL model. As a main result, we build neural network for deciding truth value of FDL formulas in a canonical model and thus link RL problem to machine learning. We apply the approach to dataset with 10000 entries and also compare to classical RL solving approaches. The results show to be more accurate than standard probabilistic approach.

Keywords: description logic, fuzzy logic, neural networks, record linkage

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438 Application of the Critical Decision Method for Monitoring and Improving Safety in the Construction Industry

Authors: Juan Carlos Rubio Romero, Francico Salguero Caparros, Virginia Herrera-Pérez

Abstract:

No one is in the slightest doubt about the high levels of risk involved in work in the construction industry. They are even higher in structural construction work. The Critical Decision Method (CDM) is a semi-structured interview technique that uses cognitive tests to identify the different disturbances that workers have to deal with in their work activity. At present, the vision of safety focused on daily performance and things that go well for safety and health management is facing the new paradigm known as Resilience Engineering. The aim of this study has been to describe the variability in formwork labour on concrete structures in the construction industry and, from there, to find out the resilient attitude of workers to unexpected events that they have experienced during their working lives. For this purpose, a series of semi-structured interviews were carried out with construction employees with extensive experience in formwork labour in Spain by applying the Critical Decision Method. This work has been the first application of the Critical Decision Method in the field of construction and, more specifically, in the execution of structures. The results obtained show that situations categorised as unthought-of are identified to a greater extent than potentially unexpected situations. The identification during these interviews of both expected and unexpected events provides insight into the critical decisions made and actions taken to improve resilience in daily practice in this construction work. From this study, it is clear that it is essential to gain more knowledge about the nature of the human cognitive process in work situations within complex socio-technical systems such as construction sites. This could lead to a more effective design of workplaces in the search for improved human performance.

Keywords: resilience engineering, construction industry, unthought-of situations, critical decision method

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437 Action Research: The Goal Setting Intervention Promotes Students' Academic Achievement of the Bachelors of Early Childhood Education Program During the COVID-19 Pandemic

Authors: Mashaal Hooda

Abstract:

The rationale for conducting this action research was to increase students' Academic Achievement (AA) contexts of studying/researching by employing the Goal Setting intervention (GS). The purposive sample consisted of 10 female undergraduate students at a university in Dubai. The intervention was introduced through workshop classes conducted online. The pre-intervention consisted of discussions concentrating on participants' research contexts amidst a pandemic. The GS moderators were implemented in the class, followed by scaffolding and mentoring interactions and self-reflective accounts of students' actions and feelings of using the intervention to better plan and structure their dissertation tasks. The research incorporated a Mixed Methods Methodology (MMM). Quantitative data collection took place through surveys, while qualitative data were collected using semi-structured interviews. Triangulation of the emergent themes showed a positive increase in students achievable GS, self-regulatory study skills, feedback-seeking behaviours, research organisation and synthesis, self-reflection and Academic Resilient (AR) attitudes amalgamate to enhance students' AA outcomes. Though, students' intrinsic motivational levels to study and research observed minor changes only. Nonetheless, the pebble in the shoe was removed as students AA contexts improved in undertaking better actionable steps for their research. Therefore, the GS intervention enabled students to set, balance, and achieve academic goals while catering to their academic anxieties, mental health concerns, and adaptability to the e-learning platforms amidst the COVID-19 pandemic. Despite the wide-scale changes the pandemic brought to the teaching and learning communities, the GS intervention served as a targeted intervention to help students maintain their achievement contexts in a goal-oriented way.

Keywords: academic achievement, acadeic resilience, COVID-19, goal setting

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436 The Beam Expansion Method, A Simplified and Efficient Approach of Field Propagation and Resonators Modes Study

Authors: Zaia Derrar Kaddour

Abstract:

The study of a beam throughout an optical path is generally achieved by means of diffraction integral. Unfortunately, in some problems, this tool turns out to be not very friendly and hard to implement. Instead, the beam expansion method for computing field profiles appears to be an interesting alternative. The beam expansion method consists of expanding the field pattern as a series expansion in a set of orthogonal functions. Propagating each individual component through a circuit and adding up the derived elements leads easily to the result. The problem is then reduced to finding how the expansion coefficients change in a circuit. The beam expansion method requires a systematic study of each type of optical element that can be met in the considered optical path. In this work, we analyze the following fundamental elements: first order optical systems, hard apertures and waveguides. We show that the former element type is completely defined thanks to the Gouy phase shift expression we provide and the latters require a suitable mode conversion. For endorsing the usefulness and relevance of the beam expansion approach, we show here some of its applications such as the treatment of the thermal lens effect and the study of unstable resonators.

Keywords: gouy phase shift, modes, optical resonators, unstable resonators

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