Search results for: sustainable supply chain performance

Authors: Moustafa Osman Mohamed

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The resilience and sustainability of construction ecology are essential to world’s socio-economic development. Environmental resilience is crucial in relating construction ecology to the topology of spatial-economic model. Sustainable spatial-economic models focus on green business practices to comply with Earth’s Systems, allowing for the natural exchange patterns of ecosystems. Systems ecology has consistent and periodic cycles to preserve energy and materials flow within Earth’s Systems. When model structures influence the communication of internal and external features in system networks, they postulated the valence of the first-level spatial outcomes (i.e., project compatibility success). These outcomes rely on second-level outcomes (i.e., participant security satisfaction). These outcomes are based on measuring database efficiency from 2015 to 2025. The model topology incorporates state-of-the-art value-orientation impacts and addresses the complexity of sustainability issues. These include building a consistent database necessary to approach spatial structure, constructing the spatial-economic model, developing parameters associated with sustainability indicators, quantifying social, economic, and environmental impacts, and using value-orientation as a set of important sustainability policy measures. The model demonstrates environmental resilience by managing and developing schemes from perspective of multiple sources pollutants through input–output criteria. These criteria evaluate the external insertions effects to conduct Monte Carlo simulations and analysis for using matrices in a unique spatial structure. The balance, or “equilibrium patterns” such as collective biosphere features, has a composite index of the distributed feedback flows. These feedback flows have a dynamic structure with physical and chemical properties, gradually extending incremental patterns. While these structures argue from a system ecology perspective, static loads are not decisive from an artistic or architectural perspective. The popularity of system resilience in the system's structure related to ecology has led to some confusion and vagueness. However, this topic is relevant for forecasting future scenarios where industrial regions must manage the impact of relevant environmental deviations. The model attempts to unify analytic and analogical structures of urban environments using database software to integrate sustainability outcomes based on the systems topology of construction ecology.

Keywords: system ecology, construction ecology, industrial ecology, spatial-economic model, systems topology

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Authors: Adekunle Taiwo Adenike, I. K. Ogundoyin

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Lassa fever is a neglected tropical virus that has become a significant public health issue in Nigeria, with the country having the greatest burden in Africa. This paper presents a Geo-Computational Model for Analysis and Prediction of Lassa Fever Dynamics and Outbreaks in Nigeria. The model investigates the dynamics of the virus with respect to environmental factors and human populations. It confirms the role of the rodent host in virus transmission and identifies how climate and human population are affected. The proposed methodology is carried out on a Linux operating system using the OSGeoLive virtual machine for geographical computing, which serves as a base for spatial ecology computing. The model design uses Unified Modeling Language (UML), and the performance evaluation uses machine learning algorithms such as random forest, fuzzy logic, and neural networks. The study aims to contribute to the control of Lassa fever, which is achievable through the combined efforts of public health professionals and geocomputational and machine learning tools. The research findings will potentially be more readily accepted and utilized by decision-makers for the attainment of Lassa fever elimination.

Keywords: geo-computational model, lassa fever dynamics, lassa fever, outbreak prediction, nigeria

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Authors: Sulaiman Al Amro

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There are currently considerable challenges concerning data security and privacy, particularly in relation to modern technologies. This includes the virtual world known as the Metaverse, which consists of a virtual space that integrates various technologies and is therefore susceptible to cyber threats such as malware, phishing, and identity theft. This has led recent studies to propose the development of Metaverse forensic frameworks and the integration of advanced technologies, including machine learning for intrusion detection and security. In this context, the application of first-order logic offers a formal and systematic approach to defining the conditions of cyberattacks, thereby contributing to the development of effective detection mechanisms. In addition, formalizing the rules and patterns of cyber threats has the potential to enhance the overall security posture of the Metaverse and, thus, the integrity and safety of this virtual environment. The current paper focuses on the primary actions employed by avatars for potential attacks, including Interval Temporal Logic (ITL) and behavior-based detection to detect an avatar’s abnormal activities within the Metaverse. The research established that the proposed framework attained an accuracy of 92.307%, resulting in the experimental results demonstrating the efficacy of ITL, including its superior performance in addressing the threats posed by avatars within the Metaverse domain.

Keywords: security, privacy, metaverse, cyberattacks, detection, first-order logic

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Authors: Djaafar F., Hadri B., Bachir G.

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

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

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Authors: Masoud Mahdavi

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The use of sloping lands is increasing due to the reduction of suitable lands for the construction of buildings. In the design and construction of buildings on sloping lands, the foundation has special loading conditions that require the designer and executor to use the slopped foundation. The creation of underground cavities, including urban and subway tunnels, sewers, urban facilities, etc., inside the ground, causes the behavior of the foundation to be unknown. In the present study, using Abacus software, a 45-degree stepped foundation on the ground is designed. The foundations are placed on the ground in a cohesive (no-hole) manner with circular cavities that show the effect of increasing the cross-sectional area of ​​the underground cavities on the foundation's performance. The Kobe earthquake struck the foundation and ground for two seconds. The underground cavities have a circular cross-sectional area with a radius of 5 m, which is located at a depth of 22.54 m above the ground. The results showed that as the number of underground cavities increased, von Mises stress (in the vertical direction) increased. With the increase in the number of underground cavities, the plastic strain on the ground has increased. Also, with the increase in the number of underground cavities, the change in location and speed in the foundation has increased.

Keywords: stepped foundation, sloping ground, Kobe earthquake, Abaqus software, underground excavations

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Authors: K. C. Iyer, Yogita Manan Bindal, Sumit Kumar Bakshi

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The construction industry is plagued with disputes and litigation in India with many stalled projects seeking dispute resolution. This has an adverse effect on the performance and overall project delivery and impacts future investments within the industry. While construction industry is the major driver of growth, there has not been major reforms in the government construction contracts. The study is aimed at identifying the proactive means of dispute avoidance, focusing on reforms required within the construction contracts, by studying 49 arbitration awards of construction disputes. The claims presented in the awards are aggregated to study the causes linked to the contract document and are referred against the prospective recommendation and practices as surveyed from literature review of research papers. Within contract administration, record keeping has been a major concern as they are required by the parties to substantiate the claims or the counterclaims and therefore are essential in any dispute redressal process. The study also observes that the right judgment is inhibited when the record keeping is improper and due to lack of coherence between documents, the dispute resolution period is also prolonged. The finding of the research will be relevant to industry practitioners in contract drafting with a view to avoid disputes.

Keywords: construction contract, contract administration, contract management, dispute avoidance

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Authors: Mohammad Mohammadzadeh, Alireza Ghasempour

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In this paper, a new design of monopole antenna has been proposed that increases the contrast of intravascular magnetic resonance images through increasing the homogeneity of the intrinsic signal-to-noise ratio (ISNR) distribution around the antenna. The antenna is made of a coaxial cable with three parasitic elements. Lengths and positions of the elements are optimized by the improved genetic algorithm (IGA) for 1.5, 3, 4.7, and 7Tesla MRI systems based on a defined cost function. Simulations were also conducted to verify the performance of the designed antenna. Our simulation results show that each time IGA is executed different values for the parasitic elements are obtained so that the cost functions of those antennas are high. According to the obtained results, IGA can also find the best values for the parasitic elements (regarding cost function) in the next executions. Additionally, two dimensional and one-dimensional maps of ISNR were drawn for the proposed antenna and compared to the previously published monopole antenna with one parasitic element at the frequency of 64MHz inside a saline phantom. Results verified that in spite of ISNR decreasing, there is a considerable improvement in the homogeneity of ISNR distribution of the proposed antenna so that their multiplication increases.

Keywords: intravascular MR antenna, monopole antenna, parasitic elements, signal-to-noise ratio (SNR), genetic algorithm

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Authors: Yuhang Wang, Jorg Schluter, Sergiy Shelyag

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The high cost associated with high-resolution computational fluid dynamics (CFD) is one of the main challenges that inhibit the design, development, and optimisation of new combustion systems adapted for renewable fuels. In this study, we propose a physics-guided CNN-based model to predict turbulence evolution and mixing without requiring a traditional CFD solver. The model architecture is built upon U-Net and the inception module, while a physics-guided loss function is designed by introducing two additional physical constraints to allow for the conservation of both mass and pressure over the entire predicted flow fields. Then, the model is trained on the Large Eddy Simulation (LES) results of a natural turbulent mixing layer with two different Reynolds number cases (Re = 3000 and 30000). As a result, the model prediction shows an excellent agreement with the corresponding CFD solutions in terms of both spatial distributions and temporal evolution of turbulent mixing. Such promising model prediction performance opens up the possibilities of doing accurate high-resolution manifold-based combustion simulations at a low computational cost for accelerating the iterative design process of new combustion systems.

Keywords: computational fluid dynamics, turbulence, machine learning, combustion modelling

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Authors: Ashkan Nazari, Saied Taheri

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Knowledge of tire-pavement interaction plays a crucial role in designing safer and more reliable tires. Characterizing the tire-pavement frictional interaction leads to a better understanding of vehicle performance in braking and acceleration. In this work, we devise a multi-scale simulation approach to incorporate the effect of pavement surface asperities in different length-scales. We construct two- and three-dimensional Finite Element (FE) models to simulate the interaction between a rubber block and a rough pavement surface with asperities in different scales. To achieve this, the road profile is scanned via a laser profilometer and the obtained asperities are implemented in an FE software (ABAQUS) in micro and macro length-scales. The hysteresis friction, which is due to the dissipative nature of rubber, is the main component of the friction force and therefore is the subject of study in this work. Using different scales not only will assist in characterizing the pavement asperities with sufficient details but also, it is highly effective in preventing extreme local deformations and stress gradients which results in divergence in FE simulations. The simulation results will be validated with experimental results as well as the results reported in the literature.

Keywords: friction, finite element, multi-scale modeling, rubber

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Authors: Nazmul Shahadat, Anthony S. Maida

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In recent years, hypercomplex inspired neural networks improved deep CNN architectures due to their ability to share weights across input channels and thus improve cohesiveness of representations within the layers. The work described herein studies the effect of replacing existing layers in an Axial Attention ResNet with their quaternion variants that use cross-channel weight sharing to assess the effect on image classification. We expect the quaternion enhancements to produce improved feature maps with more interlinked representations. We experiment with the stem of the network, the bottleneck layer, and the fully connected backend by replacing them with quaternion versions. These modifications lead to novel architectures which yield improved accuracy performance on the ImageNet300k classification dataset. Our baseline networks for comparison were the original real-valued ResNet, the original quaternion-valued ResNet, and the Axial Attention ResNet. Since improvement was observed regardless of which part of the network was modified, there is a promise that this technique may be generally useful in improving classification accuracy for a large class of networks.

Keywords: axial attention, representational networks, weight sharing, cross-channel correlations, quaternion-enhanced axial attention, deep networks

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Authors: Djallel Bouamama, Yasser R. Haddadi

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Accurate brain tumor segmentation is crucial for diagnosis and treatment planning, yet it remains a challenging task due to the variability in tumor shapes and intensities. This paper introduces a distinct approach to brain tumor image segmentation by leveraging an advanced architecture known as Mamba-Unet. Building on the well-established U-Net framework, Mamba-Unet incorporates distinct design enhancements to improve segmentation performance. Our proposed method integrates a multi-scale attention mechanism and a hybrid loss function to effectively capture fine-grained details and contextual information in brain MRI scans. We demonstrate that Mamba-Unet significantly enhances segmentation accuracy compared to conventional U-Net models by utilizing a comprehensive dataset of annotated brain MRI scans. Quantitative evaluations reveal that Mamba-Unet surpasses traditional U-Net architectures and other contemporary segmentation models regarding Dice coefficient, sensitivity, and specificity. The improvements are attributed to the method's ability to manage class imbalance better and resolve complex tumor boundaries. This work advances the state-of-the-art in brain tumor segmentation and holds promise for improving clinical workflows and patient outcomes through more precise and reliable tumor detection.

Keywords: brain tumor classification, image segmentation, CNN, U-NET

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Authors: Sina Abadzadesahraei, Stephen Déry, John Rex

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Climate research has repeatedly identified strong associations between anthropogenic emissions of ‘greenhouses gases’ and observed increases of global mean surface air temperature over the past century. Studies have also demonstrated that the degree of warming varies regionally. Canada is not exempt from this situation, and evidence is mounting that climate change is beginning to cause diverse impacts in both environmental and socio-economic spheres of interest. For example, northeastern British Columbia (BC), whose climate is controlled by a combination of maritime, continental and arctic influences, is warming at a greater rate than the remainder of the province. There are indications that these changing conditions are already leading to shifting patterns in the region’s hydrological cycle, and thus its available water resources. Coincident with these changes, northeastern BC is undergoing rapid development for oil and gas extraction: This depends largely on subsurface hydraulic fracturing (‘fracking’), which uses enormous amounts of freshwater. While this industrial activity has made substantial contributions to regional and provincial economies, it is important to ensure that sufficient and sustainable water supplies are available for all those dependent on the resource, including ecological systems. In this turn demands a comprehensive understanding of how water in all its forms interacts with landscapes, the atmosphere, and of the potential impacts of changing climatic conditions on these processes. The aim of this study is therefore to characterize and quantify all components of the water budget in the small watershed of Coles Lake (141.8 km², 100 km north of Fort Nelson, BC), through a combination of field observations and numerical modelling. Baseline information will aid the assessment of the sustainability of current and future plans for freshwater extraction by the oil and gas industry, and will help to maintain the precarious balance between economic and environmental well-being. This project is a perfect example of interdisciplinary research, in that it not only examines the hydrology of the region but also investigates how natural gas operations and growth can affect water resources. Therefore, a fruitful collaboration between academia, government and industry has been established to fulfill the objectives of this research in a meaningful manner. This project aims to provide numerous benefits to BC communities. Further, the outcome and detailed information of this research can be a huge asset to researchers examining the effect of climate change on water resources worldwide.

Keywords: northeastern British Columbia, water resources, climate change, oil and gas extraction

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Authors: Y. Bai, M. Bodlak, V. Frolov, S. Huber, V. Jary, I. Konorov, D. Levit, J. Novy, D. Steffen, O. Subrt, M. Virius

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Modern experiments in high energy physics impose great demands on the reliability, the efficiency, and the data rate of Data Acquisition Systems (DAQ). This contribution focuses on the development and deployment of the new communication library DIALOG for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. The iFDAQ utilizing a hardware event builder is designed to be able to readout data at the maximum rate of the experiment. The DIALOG library is a communication system both for distributed and mixed environments, it provides a network transparent inter-process communication layer. Using the high-performance and modern C++ framework Qt and its Qt Network API, the DIALOG library presents an alternative to the previously used DIM library. The DIALOG library was fully incorporated to all processes in the iFDAQ during the run 2016. From the software point of view, it might be considered as a significant improvement of iFDAQ in comparison with the previous run. To extend the possibilities of debugging, the online monitoring of communication among processes via DIALOG GUI is a desirable feature. In the paper, we present the DIALOG library from several insights and discuss it in a detailed way. Moreover, the efficiency measurement and comparison with the DIM library with respect to the iFDAQ requirements is provided.

Keywords: data acquisition system, DIALOG library, DIM library, FPGA, Qt framework, TCP/IP

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Authors: Qian Zhu, Shidong Nie, Bo Yang, Gang Xiong, Guoxin Dai

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GJ steel is a new type of high-performance structural steel which has been increasingly adopted in practical engineering. Q460GJ structural steel has a nominal yield strength of 460 MPa, which does not decrease significantly with the increase of steel plate thickness like normal structural steel. Thus, Q460GJ structural steel is normally used in medium-walled welded sections. However, research works on the residual stress in GJ steel members are few though it is one of the vital factors that can affect the member and structural behavior. This article aims to investigate the residual stresses in welded I-shaped sections fabricated from Q460GJ structural steel plates by experimental tests. A total of four full scale welded medium-walled I-shaped sections were tested by sectioning method. Both circular curve correction method and straightening measurement method were adopted in this study to obtain the final magnitude and distribution of the longitudinal residual stresses. In addition, this paper also explores the interaction between flanges and webs. And based on the statistical evaluation of the experimental data, a multilayer residual stress model is proposed.

Keywords: Q460GJ structural steel, residual stresses, sectioning method, welded medium-walled I-shaped sections

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Authors: Bisemiire Anthony,

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PESH Poultry is a business project proposed specifically to solve unemployment and income-related problems affecting the youths in the Busia district. The project is intended to transform the life of the youth in terms of economic, social and behavioral, as well as the domestic well-being of the community at large. PESH Poultry is a start-up poultry farm that will be engaged in the keeping of poultry birds, broilers and layers for the production of quality and affordable poultry meat and eggs respectively and other poultry derivatives targeting consumers in eastern Uganda, for example, hotels, restaurants, households and bakeries. We intend to use a semi-intensive system of farming, where water and some food are provided in a separate nighttime shelter for the birds; our location will be in Lumino, Busia district. The poultry project will be established and owned by Bisemiire Anthony, Nandera Patience, Naula Justine, Bwire Benjamin and other investors. The farm will be managed and directed by Nandera Patience, who has five years of work experience and business administration knowledge. We will sell poultry products, including poultry eggs, chicken meat, feathers and poultry manure. We also offer consultancy services for poultry farming. Our eggs and chicken meat are hygienic, rich in protein and high quality. We produce processes and packages to meet the standard organization of Uganda and international standards. The business project shall comprise five (5) workers on the key management team who will share various roles and responsibilities in the identified business functions such as marketing, finance and other related poultry farming activities. PESH Poultry seeks 30 million Ugandan shillings in long-term financing to cover start-up costs, equipment, building expenses and working capital. Funding for the launch of the business will be provided primarily by equity from the investors. The business will reach positive cash flow in its first year of operation, allowing for the expected repayment of its loan obligations. Revenue will top UGX 11,750,000, and net income will reach about UGX115 950,000 in the 1st year of operation. The payback period for our project is 2 years and 3 months. The farm plans on starting with 1000 layer birds and 1000 broiler birds, 20 workers in the first year of operation.

Keywords: chicken, pullets, turkey, ducks

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Authors: A.Velavan, C. G. Saravanan, M. Vikneswaran, E. James Gunasekaran

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In present investigation, experiments were carried out to compare the effect of the ceramic coated piston crown and uncoated piston on combustion, performance and emission characteristics of a port injected Spark Ignited engine. The piston crown was coated with aluminium alloy in the form ceramic oxide layer of thickness 500 µm using micro-arc oxidation technique. This ceramic coating will act as a thermal barrier which reduces in-cylinder heat rejection and increases the durability of the piston by withstanding high temperature and pressure produced during combustion. Flame visualization inside the combustion chamber was carried out using AVL Visioscope combustion analyzer to predict the type of combustion occurs at different load condition. Based on the experimental results, it was found that the coated piston shows an improved thermal efficiency when compared to uncoated piston. This is because more heat presents in the combustion chamber which helps efficient combustion of the fuel. The CO and HC emissions were found to be reduced due to better combustion of the fuel whereas NOx emission was increased due to increase in combustion temperature for ceramic coated piston.

Keywords: coated piston, micro-arc oxidation, thermal barrier, thermal efficiency, visioscope

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Authors: Evrim Genc Kumtepe, Elif Toprak, Aylin Ozturk, Gamze Tuna, Hakan Kilinc, Irem Aydin Menderis

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Support services are very significant elements for all educational institutions in general; however, for distance learners, these services are more essential than traditional (face-to-face) counterparts. One of the most important reasons for this is that learners and instructors do not share the same physical environment and that distance learning settings generally require intrapersonal interactions rather than interpersonal ones. Some learners in distance learning programs feel isolated. Furthermore, some fail to feel a sense of belonging to the institution because of lack of self-management skills, lack of motivation levels, and the need of being socialized, so that they are more likely to fail or drop out of an online class. In order to overcome all these problems, support services have emerged as a critical element for an effective and sustainable distance education system. Within the context of distance education support services, it is natural to include technology-based and web-based services and also the related materials. Moreover, institutions in education sector are expected to use information and communication technologies effectively in order to be successful in educational activities and programs. In terms of the sustainability of the system, an institution should provide distance education services through ICT enabled processes to support all stakeholders in the system, particularly distance learners. In this study, it is envisaged to develop a model based on the current support services literature in the field of open and distance learning and the applications of the distance higher education institutions. Specifically, content analysis technique is used to evaluate the existing literature in the distance education support services, the information published on websites, and applications of distance higher education institutions across the world. A total of 60 institutions met the inclusion criteria which are language option (English) and availability of materials in the websites. The six field experts contributed to brainstorming process to develop and extract codes for the coding scheme. During the coding process, these preset and emergent codes are used to conduct analyses. Two coders independently reviewed and coded each assigned website to ensure that all coders are interpreting the data the same way and to establish inter-coder reliability. Once each web page is included in descriptive and relational analysis, a model of support services is developed by examining the generated codes and themes. It is believed that such a model would serve as a quality guide for future institutions, as well as the current ones.

Keywords: support services, open education, distance learning, support model

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Authors: Neetu Manocha

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Image segmentation is a technique where a picture is parted into distinct parts having similar features which have a place with similar items. Various segmentation strategies have been proposed as of late by prominent analysts. But, after ultimate thorough research, the novelists have analyzed that generally, the old methods do not decrease the segmentation error rate. Then author finds the technique HIST-SI to decrease the segmentation error rates. In this technique, cluster-based and threshold-based segmentation techniques are merged together. After then, to improve the result of HIST-SI, the authors added the method of filtering and linking in this technique named Imp_HIST-SI to decrease the segmentation error rates. The goal of this research is to find a new technique to decrease the segmentation error rates and produce much better results than the HIST-SI technique. For testing the proposed technique, a dataset of Bhuvan – a National Geoportal developed and hosted by ISRO (Indian Space Research Organisation) is used. Experiments are conducted using Scikit-image & OpenCV tools of Python, and performance is evaluated and compared over various existing image segmentation techniques for several matrices, i.e., Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR).

Keywords: satellite image, image segmentation, edge detection, error rate, MSE, PSNR, HIST-SI, linking, filtering, imp_HIST-SI

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Authors: Muhammad Rizwan, Naveed Ahmad, Akhtar Naeem Khan

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Seismic behavior factors are evaluated for the performance assessment of low rise reinforced concrete RC frame structures based on experimental study of unidirectional dynamic shake table testing of two 1/3rd reduced scaled two storey frames, with a code confirming special moment resisting frame (SMRF) model and a noncompliant model of similar characteristics but built in low strength concrete .The models were subjected to a scaled accelerogram record of 1994 Northridge earthquake to deformed the test models to final collapse stage in order to obtain the structural response parameters. The fully compliant model was observed with more stable beam-sway response, experiencing beam flexure yielding and ground-storey column base yielding upon subjecting to 100% of the record. The response modification factor - R factor obtained for the code complaint and deficient prototype structures were 7.5 and 4.5 respectively, which is about 10% and 40% less than the UBC-97 specified value for special moment resisting reinforced concrete frame structures.

Keywords: Northridge 1994 earthquake, reinforced concrete frame, response modification factor, shake table testing

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Authors: N. Sena, C. Vasconcelos

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Portugal has a lower rate of people who exercise. Fitness centers are a widely recognized context for the performance of an exercise. Thus, the objective of this study is to analyze the motivational factors for the practice of exercise in a sample of Portuguese fitness center users. The sample consists of 34 users (23 men and 11 women), aged between 16 and 60 years old (24.7 ± 11,5 years old). The instrument used for data collection was the Motivation Questionnaire for Exercise (version translated and validated into Portuguese), consisting of forty-nine items grouped into ten motivational factors. Responses to the Exercise Motivation Questionnaire are given on a 6-point Likert scale (0="not at all true for me" to 5="completely true for me"). With regard to the results, it is possible to verify that the motivational factors considered most relevant by the sample of our study were “Well-being” (4.44 ± 0.28), followed by “Health” (4.29 ± 0.57) and “Stress Management” (4.06 ± 0.54). The factors “Affiliation” (3.11 ± 0.49) “Personal Appreciation” (2.26 ± 0.59) and “Medical History” (1.71 ± 0.74) were considered by the respondents to be the least important factors for performing the exercise. The conclusion of this study is that in the sample of this study, the factors that most motivated the practice of exercise were “Well-being”, “Health” and “Stress Management”. In the opposite direction, the factors that least motivated the individuals in this sample to practice exercise were “Affiliation”, “Personal Appreciation” and “Medical History”.

Keywords: exercise, fitness center users, motivational factors, Portugal

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Authors: Rasha Saad, Jean Frederic Weber, Fatimah Bebe, Sadia Sultan

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The goal of study was to screen the effects of candesartan and four endophytic fungi for their potential in microbial biotransformation. In this experiment, four types of unidentified fungi with the codes of TH2L1, TH2R10, TH1P35 and TH1S46 were used in screening process by MECFUS (Microtiter plate, Elicitors, Combination, Freeze-drying, UHPLC, Statistical analysis) protocol. The experiment was carried out by using 96-well microtiter plate (MTP) with different media and elicitors. Various media with two concentrations of Potato Dextrose Broth (PDB) and elicitors used were to induce the production of secondary metabolites from the fungi as well as the biotransformation of the drug compound. After incubation, cultures were extracted by freeze drying method and finally analyzed by ultra-High performance Liquid Chromatography (uHPLC). The extracts analyzed by uHPLC followed by LC/Ms, demonstrated the presence of biotransformation products from the drug compound and elicitation of the secondary metabolism from the fungi by the occurrence of the additional peaks. From the four fungi, TH1S46 showed highly potential produced secondary metabolites as well as the biotransformation of candesartan. For other fungi, they responded when candesartan was introduced. Moreover, the additional peaks produced in uHPLC need to be further investigation by using LC-MS or NMR.

Keywords: biotransformation, candesartan, endophytes, secondary metabolites

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Authors: Shonak Bansal, Prince Jain, Arun Kumar Singh, Neena Gupta

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Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength division multiplexing (WDM) systems in order to minimize the adverse four–wave mixing (FWM) crosstalk effect. The simulation results conclude that the proposed optimization algorithm has superior performance compared to the existing conventional computing and nature–inspired optimization algorithms to find OGRs in terms of ruler length, total optical channel bandwidth and computation time.

Keywords: channel allocation, conventional computing, four–wave mixing, nature–inspired algorithm, optimal Golomb ruler, lévy flight distribution, optimization, improved multi–objective firefly algorithms, Pareto optimal

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Authors: Ashraf Aly

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The aim of this study is to examine the impact of 5G communication technology radiation on human health and airport safety. The term 5G refers to the fifth generation of wireless mobile technology. The 5G wireless technology will increase the number of high-frequency-powered base stations and other devices and browsing and download speeds, as well as improve the network connectivity and play a big part in improving the performance of integrated applications, such as self-driving cars, medical devices, and robotics. 4G was the latest embedded version of mobile networking technology called 4G, and 5G is the new version of wireless technology. 5G networks have more features than 4G networks, such as lower latency, higher capacity, and increased bandwidth compared to 4G. 5G network improvements over 4G will have big impacts on how people live, business, and work all over the world. But neither 4G nor 5G have been tested for safety and show harmful effects from this wireless radiation. This paper presents biological factors on the effects of 5G radiation on human health. 5G services use C-band radio frequencies; these frequencies are close to those used by radio altimeters, which represent important equipment for airport and aircraft safety. The aviation industry, telecommunications companies, and their regulators have been discussing and weighing these interference concerns for years.

Keywords: wireless communication, radiofrequency, Electromagnetic field, environmental issues

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Authors: Ahmet Y. Gurkan, Cagatay S. Koksal, Cagri Aydin, U. Oral Unal

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The present paper covers the viscous flow computations for the asymmetric diffuser section of a large, high-speed cavitation tunnel which will be constructed in Istanbul Technical University. The analyses were carried out by using the incompressible Reynold-Averaged-Navier-Stokes equations. While determining the diffuser geometry, a high quality, separation-free flow field with minimum energy loses was particularly aimed. The expansion angle has a critical role on the diffuser hydrodynamic performance. In order obtain a relatively short diffuser length, due to the constructive limitations, and hydrodynamic energy effectiveness, three diffuser sections with varying expansion angles for side and bottom walls were considered. A systematic study was performed to determine the most effective diffuser configuration. The results revealed that the inlet condition of the diffuser greatly affects its flow field. The inclusion of the contraction section in the computations substantially modified the flow topology in the diffuser. The effect of the diffuser flow on the test section flow characteristics was clearly observed. The influence of the introduction of small chamfers at the corners of the diffuser geometry is also presented.

Keywords: asymmetric diffuser, diffuser design, cavitation tunnel, viscous flow, computational fluid dynamics (CFD), rans

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Authors: Siddharth Ojha, Varun Dua

Abstract:

Classified as one of the most important reasons of aerodynamic drag in the sedan automobiles is the fluid flow separation near the vehicle’s rear end. To retard the separation of flow, bump-shaped vortex generators are being tested for its implementation to the roof end of a sedan vehicle. Frequently used in the aircrafts to prevent the separation of fluid flow, vortex generators themselves produce drag, but they also substantially reduce drag by preventing flow separation at the downstream. The net effects of vortex generators can be calculated by summing the positive and negative impacts and effects. Since this effect depends on dimensions and geometry of vortex generators, those present on the vehicle roof are optimized for maximum efficiency and performance. The model was tested through ANSYS CFD analysis and modeling. The model was tested in the wind tunnel for observing it’s properties such as aerodynamic drag and flow separation and a major time lag was gained by employing vortex generators in the scaled model. Major conclusions which were recorded during the analysis were a substantial 24% reduction in the aerodynamic drag and 14% increase in the efficiency of the sedan automobile as the flow separation from the surface is delayed. This paper presents the results of optimization, the effect of vortex generators in the flow field and the mechanism by which these effects occur and are regulated.

Keywords: aerodynamics, aerodynamic devices, body, computational fluid dynamics (CFD), flow visualization

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Authors: Xiang Shijie, Zhou Dong, Tian Dan

Abstract:

Speaker recognition is a crucial task in the field of speech processing, aimed at identifying individuals based on their vocal characteristics. However, existing speaker recognition methods face numerous challenges. Traditional methods primarily rely on audio signals, which often suffer from limitations in noisy environments, variations in speaking style, and insufficient sample sizes. Additionally, relying solely on audio features can sometimes fail to capture the unique identity of the speaker comprehensively, impacting recognition accuracy. To address these issues, we propose a multi-modal network architecture that simultaneously processes both audio and text signals. By gradually integrating audio and text features, we leverage the strengths of both modalities to enhance the robustness and accuracy of speaker recognition. Our experiments demonstrate significant improvements with this multi-modal approach, particularly in complex environments, where recognition performance has been notably enhanced. Our research not only highlights the limitations of current speaker recognition methods but also showcases the effectiveness of multi-modal fusion techniques in overcoming these limitations, providing valuable insights for future research.

Keywords: feature fusion, memory network, multimodal input, speaker recognition

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Authors: Mohd Naqiuddin Bin Husri, Siti Rahmah Abd Rahman, Dalilah Abu Bakar, Dayang Izawati Abang Masli, Meilina Ong Abdullah

Abstract:

A serious shortage of prime agricultural land coupled with environmental concerns inland expansion has daunted efforts to increase the national yield average. To address this issue, maximising yield per unit hectare through quality planting material is of great importance. Breeding for improved planting materials has been a continuous effort since the early days of this industry, it is time-consuming, and the likelihood of segregation within the progenies further impedes progress in this area. Incorporation of the cloning technology in oil palm breeding programmes is therefore advantageous to expedite the development of commercial elite and high-yielding planting materials. After more than 22 years of research and development through this project, reliable protocols for liquid/suspension culture systems coupled with various innovative technologies which are effective at promoting proliferation and growth of oil palm culture have been established. Subsequently, clonal palms derived from the suspension culture system were extensively studied in the field, and the results have been encouraging. Clones such as CPS1, CPS2 and a few others recorded superior performance in comparison with D x P standard crosses.

Keywords: tissue culture, suspension culture, oil palm, Elaeis guineensis

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Authors: Halil Ibrahim Demir, Caner Erden, Abdullah Hulusi Kokcam, Mumtaz Ipek

Abstract:

Process planning, scheduling, and due date assignment are three important manufacturing functions which are studied independently in literature. There are hundreds of works on IPPS and SWDDA problems but a few works on IPPSDDA problem. Integrating these three functions is very crucial due to the high relationship between them. Since the scheduling problem is in the NP-Hard problem class without any integration, an integrated problem is even harder to solve. This study focuses on the integration of these functions. Sum of weighted tardiness, earliness, and due date related costs are used as a penalty function. Random search and hybrid metaheuristics are used to solve the integrated problem. Marginal improvement in random search is very high in the early iterations and reduces enormously in later iterations. At that point directed search contribute to marginal improvement more than random search. In this study, random and genetic search methods are combined to find better solutions. Results show that overall performance becomes better as the integration level increases.

Keywords: process planning, genetic algorithm, hybrid search, random search, weighted due-date assignment, weighted scheduling

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Authors: Dessie Tibebe, Muluken Asmare, Marye Mulugeta, Yezbie Kassa, Zerubabel Moges, Dereje Yenealem, Tarekegn Fentie, Agmas Amare

Abstract:

The performance of electrocoagulation (EC) using Aluminium electrodes for the treatment of effluent-containing chromium metal using a fixed bed electrochemical batch reactor was studied. In the present work, the efficiency evaluation of EC in removing physicochemical and heavy metals from real industrial tannery wastewater in the Amhara region, collected from Bahirdar, Debre Brihan, and Haik, was investigated. The treated and untreated samples were determined by AAS and ICP OES spectrophotometers. The results indicated that selected heavy metals were removed in all experiments with high removal percentages. The optimal results were obtained regarding both cost and electrocoagulation efficiency with initial pH = 3, initial concentration = 40 mg/L, electrolysis time = 30 min, current density = 40 mA/cm2, and temperature = 25oC favored metal removal. The maximum removal percentages of selected metals obtained were 84.42% for Haik, 92.64% for Bahir Dar and 94.90% for Debre Brihan. The sacrificial electrode and sludge were characterized by FT-IR, SEM and XRD. After treatment, some metals like chromium will be used again as a tanning agent in leather processing to promote a circular economy.

Keywords: electrochemical, treatment, aluminum, tannery effluent

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Authors: Jiawen Wang, Qijun Chen

Abstract:

The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

Procedia PDF Downloads 135