Search results for: fine marble

Authors: Abiola Ayopo Abiodun, Zalihe Nalbantoglu

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The electrokinetic application (EKA), a relatively modern chemical treatment has a potential for in-situ ground improvement in an open field or under existing structures. It utilizes a low electrical gradient to transport electrolytic chemical ions between bespoke electrodes inserted in the fine-grained, low permeable soft soils. The paper investigates the efficacy of the EKA as a mitigation technique for the soft clay beds. The laboratory model of the EKA comprises of rectangular plexiglass test tank, electrolytes compartments, geosynthetic electrodes and direct electric current supply. Within this setup, the EK effects resulted from the exchange of ions between anolyte (anodic) and catholyte (cathodic) ends through the tested soil were examined by basic experimental laboratory testing methods. As such, the treated soft soil properties were investigated as a function of the anode-to-cathode distances and curing periods. The test results showed that there have been some changes in the physical and engineering properties of the treated soft soils. The significant changes in the physicochemical and electrical properties suggested that their corresponding changes can be utilized as a monitoring technique to evaluate the improvement in the engineering properties EK treated soft clay soils.

Keywords: electrokinetic, electrolytes, exchange ions, geosynthetic electrodes, soft soils

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Authors: Laidi Maamar, Achwak Madani, Abdellah El Ahdj Abdellah

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The aim of this work is to use Support Vector regression (SVR) combined with dragonfly, firefly, Bee Colony and particle swarm Optimization algorithm to predict global solar radiation on horizontal surfaces in some cities in Algeria. Combining these optimization algorithms with SVR aims principally to enhance accuracy by fine-tuning the parameters, speeding up the convergence of the SVR model, and exploring a larger search space efficiently; these parameters are the regularization parameter (C), kernel parameters, and epsilon parameter. By doing so, the aim is to improve the generalization and predictive accuracy of the SVR model. Overall, the aim is to leverage the strengths of both SVR and optimization algorithms to create a more powerful and effective regression model for various cities and under different climate conditions. Results demonstrate close agreement between predicted and measured data in terms of different metrics. In summary, SVM has proven to be a valuable tool in modeling global solar radiation, offering accurate predictions and demonstrating versatility when combined with other algorithms or used in hybrid forecasting models.

Keywords: support vector regression (SVR), optimization algorithms, global solar radiation prediction, hybrid forecasting models

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Authors: Fauzi Jarushi, Paul Cosentino, Edward Kalajian, Hadeel Dekhn

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At certain depths during large diameter displacement pile driving, rebound well over 0.25 inches was experienced, followed by a small permanent set during each hammer blow. High pile rebound (HPR) soils may stop the pile driving and results in a limited pile capacity. In some cases, rebound leads to pile damage, delaying the construction project, and the requiring foundations redesign. HPR was evaluated at seven Florida sites, during driving of square precast, prestressed concrete piles driven into saturated, fine silty to clayey sands and sandy clays. Pile Driving Analyzer (PDA) deflection versus time data recorded during installation, was used to develop correlations between cone penetrometer (CPT) pore-water pressures, pile displacements and rebound. At five sites where piles experienced excessive HPR with minimal set, the pore pressure yielded very high positive values of greater than 20 tsf. However, at the site where the pile rebounded, followed by an acceptable permanent set, the measured pore pressure ranged between 5 and 20 tsf. The pore pressure exhibited values of less than 5 tsf at the site where no rebound was noticed. In summary, direct correlations between CPTu pore pressure and rebound were produced, allowing identification of soils that produce HPR.

Keywords: CPTU, pore water pressure, pile rebound

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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: Kateryna Merkulova, Alessio Castello, Maria Kreuzer

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This research investigates the drivers of long-term relationship building between customers and suppliers within the luxury food supply chain, a topic that remains largely unexplored in the current state of academic literature. This paper identifies for the first time the key elements that influence the formation and maintenance of effective supply chain relationships, which are crucial for navigating the complexities of the luxury food industry. In particular, it explores the critical role of trust in a business-to-business context, specifically emphasizing its significance in the luxury food supply chain. Empirically, this research is contextualized in the region of the French Riviera, which offers a gastronomic playground for food enthusiasts, making it ideally suited to explore the luxury food sector. Qualitative in-depth interviews with stakeholders along the luxury supply chain (i.e., suppliers, chefs, restaurant owners, and fine food shop managers) allow identifying key drivers of trustful business relationships. Triangulating different perspectives of stakeholders within the luxury supply chain adds validity and robustness to the findings. The findings have important theoretical and managerial implications for the effective functioning of long-term supplier-buyer relationships.

Keywords: luxury food, relationship building, B2B, supply chain, trust

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Authors: Nicanor Garcia Alvarez, Belarmino Adenso-Diaz, Laura Calzada Infante

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In recent years, researchers have shown an interest in modelling maritime traffic as a complex network. In this paper, we propose a bipartite weighted network to model maritime traffic and detect port maritime communities. The bipartite weighted network considers two different types of nodes. The first one represents Spanish ports, while the second one represents the countries with which there is major import/export activity. The flow among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the data is segmented by each type of traffic. This will allow fine tuning and the creation of communities for each type of traffic and therefore finding similar ports for a specific type of traffic, which will provide decision-makers with tools to search for alliances or identify their competitors. The traffic with the greatest impact on the Spanish gross domestic product is selected, and the evolution of the communities formed by the most important ports and their differences between 2019 and 2009 will be analyzed. Finally, the set of communities formed by the ports of the Spanish port system will be inspected to determine global similarities between them, analyzing the sum of the membership of the different ports in communities formed for each type of traffic in particular.

Keywords: bipartite networks, competition, infomap, maritime traffic, port communities

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Authors: Peter Jurči, Jana Ptačinová, Mária Hudáková, Mária Dománková, Martin Kusý, Martin Sahul

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The strength, hardness, and toughness (ductility) are in strong conflict for the metallic materials. The only possibility how to make their simultaneous improvement is to provide the microstructural refinement, by cold deformation, and subsequent recrystallization. However, application of this kind of treatment is impossible for high-carbon high-alloyed ledeburitic tool steels. Alternatively, it has been demonstrated over the last few years that sub-zero treatment induces some microstructural changes in these materials, which might favourably influence their complex of mechanical properties. Commercially available PM ledeburitic steel Vanadis 6 has been used for the current investigations. The paper demonstrates that sub-zero treatment induces clear refinement of the martensite, reduces the amount of retained austenite, enhances the population density of fine carbides, and makes alterations in microstructural development that take place during tempering. As a consequence, the steel manifests improved wear resistance at higher toughness and fracture toughness. Based on the obtained results, the key question “can the wear performance be improved by sub-zero treatment simultaneously with toughness” can be answered by “definitely yes”.

Keywords: ledeburitic tool steels, microstructure, sub-zero treatment, mechanical properties

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Authors: Prapoj Na Bangchang

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The research aimed to study the satisfaction of Suan Sunandha Rajabhat University students towards the university radio station which broadcasts in both analog on FM 97.25 MHz and online via the university website. The sample used in this study consists of undergraduate students year 1 to year 4 from 6 faculties i.e. Faculty of Education, Faculty of Humanities and Social Sciences, Faculty of Management Science and Faculty of Industrial Technology, and Faculty of Fine and Applied Arts totaling 200 students. The tools used for data collection is survey. Data analysis applied statistics that are percentage, mean and standard deviation. The results showed that Suan Sunandha Rajabhat University students were satisfied to the place of listening service, followed by channels of broadcasting that cover both analog signals on 97.25 MHz FM and online via the Internet. However, the satisfaction level of the content offered was very low. Most of the students want the station to improve the content. Entertainment content was requested the most, followed by sports content. The lowest satisfaction level is with the broadcasting quality through analog signal. Most students asked the station to improve on the issue. However, overall, Suan Sunandha Rajabhat University students were satisfied with the university radio station broadcasted online via the university website.

Keywords: satisfaction, students, radio station, Suan Sunandha Rajabhat University

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Authors: Fatma El-Zahraa El-Taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions, is critical to decisions such as crossing roads or selecting the safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer the state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset is examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of the detection of intersections in satellite images is evaluated.

Keywords: satellite images, remote sensing images, data acquisition, autonomous vehicles

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Authors: Jamshaid Ul Rahman, Faiza Makhdoom, Dianchen Lu

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Activation functions play a decisive role in determining the capacity of Deep Neural Networks (DNNs) as they enable neural networks to capture inherent nonlinearities present in data fed to them. The prior research on activation functions primarily focused on the utility of monotonic or non-oscillatory functions, until Growing Cosine Unit (GCU) broke the taboo for a number of applications. In this paper, a Convolutional Neural Network (CNN) model named as ASU-CNN is proposed which utilizes recently designed activation function ASU across its layers. The effect of this non-monotonic and oscillatory function is inspected through feature map visualizations from different convolutional layers. The optimization of proposed network is offered by Adam with a fine-tuned adjustment of learning rate. The network achieved promising results on both training and testing data for the classification of CIFAR-10. The experimental results affirm the computational feasibility and efficacy of the proposed model for performing tasks related to the field of computer vision.

Keywords: amplifying sine unit, activation function, convolutional neural networks, oscillatory activation, image classification, CIFAR-10

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Authors: S. Ishak, M. G. Nasuruddin

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Traditional Malay performances are carried out for both entertainment and curing purposes. In curing rituals, the men and women serving as shamans, communicates with the spirits and beings from the nether world to facilitate the curing process. The dependency on engaging with these other-worldly beings however, have raised religious issues of being syirik, namely practicing in rituals which are religiously forbidden. This study aims to observe how ritual leaders attempt to negotiate the fine balance between what has been religiously forbidden and the psychological and sociological needs of the patient. Two curing rituals, the main peteri and the malibobou were chosen to exemplify the communication between the physical and spiritual realities. In both rituals, the healers engaged in procedures of curing as they attempted to diagnose sicknesses and proffer cures with the help of the spirits. The main peteri was conducted by a male shaman, the tuk teri whereas the malibobou was conducted by a female ritual specialist, the bobohizan. Main peteri and the malibobou both ended with ritually thanking and sending off the spirits back to their nether, invisible domains. These curing rituals heal not only the sick individual, but by extension, the village community. Therefore, there is a need to reconcile these rituals with religious tenets, beliefs and sociological-political-cultural dimensions.

Keywords: traditional healing, trance, spirits, main peteri, bobohizan

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Authors: F. A. Olutoge, O.R. Olulope, M. O. Odelola

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This study investigates the strength potentials of groundnut husk ash as partial cement replacement in mortar and also develops a predictive model using Artificial Neural Network. Groundnut husks sourced from Ogbomoso, Nigeria, was sun dried, calcined to ash in a furnace at a controlled temperature of 600⁰ C for a period of 6 hours, and sieved through the 75 microns. The ash was subjected to chemical analysis and setting time test. Fine aggregate (sand) for the mortar was sourced from Ado Ekiti, Nigeria. The cement: GHA constituents were blended in ratios 100:0, 95:5, 90:10, 85:15 and 80:20 %. The sum of SiO₂, Al₂O₃, and Fe₂O₃ content in GHA is 26.98%. The compressive strength for mortars PC, GHA5, GHA10, GHA15, and GHA20 ranged from 6.3-10.2 N/mm² at 7days, 7.5-12.3 N/mm² at 14 days, 9.31-13.7 N/mm² at 28 days, 10.4-16.7 N/mm² at 56days and 13.35- 22.3 N/mm² at 90 days respectively, PC, GHA5 and GHA10 had competitive values up to 28 days, but GHA10 gave the highest values at 56 and 90 days while GHA20 had the lowest values at all ages due to dilution effect. Flexural strengths values at 28 days ranged from 1.08 to 1.87 N/mm² and increased to a range of 1.53-4.10 N/mm² at 90 days. The ANN model gave good prediction for compressive strength of the mortars. This study has shown that groundnut husk ash as partial cement replacement improves the strength properties of mortar.

Keywords: compressive strength, groundnut husk ash, mortar, pozzolanic index

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Authors: Andrey Khalov

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The rapid growth of unstructured data necessitates advanced methods for transforming raw information into structured knowledge, particularly in domain-specific contexts such as IT service management and outsourcing. This paper presents a methodology for automatically constructing domain ontologies using the DOLCE framework as the base ontology. The research focuses on expanding ITIL-based ontologies by integrating concepts from ITSMO, followed by the extraction of entities and relationships from domain-specific texts through transformers and statistical methods like formal concept analysis (FCA). In particular, this work introduces an R-GNN-based approach for ontology mapping, enabling more efficient entity extraction and ontology alignment with existing knowledge bases. Additionally, the research explores transfer learning techniques using pre-trained transformer models (e.g., DeBERTa-v3-large) fine-tuned on synthetic datasets generated via large language models such as LLaMA. The resulting ontology, termed IT Ontology (ITO), is evaluated against existing methodologies, highlighting significant improvements in precision and recall. This study advances the field of ontology engineering by automating the extraction, expansion, and refinement of ontologies tailored to the IT domain, thus bridging the gap between unstructured data and actionable knowledge.

Keywords: ontology mapping, knowledge graphs, R-GNN, ITIL, NER

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Authors: Charles-Olivier Amédée-Manesme, Benoit Faye, Eric Le Fur

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In this paper, the heterogeneity of the Bordeaux Legends 50 wine market price segment is addressed. For this purpose, quantile regression is applied – with market segmentation based on wine bottle price quantile – and the hedonic price of wine attributes is computed for various price segments of the market. The approach is applied to a major privately held data set which consists of approximately 30,000 transactions over the 2003–2014 period. The findings suggest that the relative hedonic prices of several wine attributes differ significantly among deciles. In particular, the elasticity coefficient of the expert ratings shows strong variation among prices. If - as suggested in the literature - expert ratings have a positive influence on wine price on average, they have a clearly decreasing impact over the quantiles. Finally, the lower the wine price, the higher the potential for price appreciation over time. Other variables such as chateaux or vintage are also shown to vary across the distribution of wine prices. While enhancing our understanding of the complex market dynamics that underlie Bordeaux wines’ price, this research provides empirical evidence that the QR approach adequately captures heterogeneity among wine price ranges, which simultaneously applies to wine stock, vintage and auctions’ house.

Keywords: hedonics, market segmentation, quantile regression, heterogeneity, wine economics

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Authors: Jaroslaw Mizera, Pawel Wisniewski, Ryszard Sitek

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Selective Laser Melting (SLM) is an advanced additive manufacturing technique used for producing parts made of wide range of materials such as: austenitic steel, titanium, nickel etc. In the our experiment we produced a Ti-AlN composite from a mixture of titanium and aluminum nitride respectively 70% at. and 30% at. using SLM technique. In order to define the size of powder particles, laser diffraction tests were performed on HORIBA LA-950 device. The microstructure and chemical composition of the composite was examined by Scanning Electron Microscopy (SEM). The chemical composition in micro areas of the obtained samples was determined by of EDS. The phase composition was analyzed by X-ray phase analysis (XRD). Microhardness Vickers tests were performed using Zwick/Roell microhardness machine under the load of 0.2kG (HV0.2). Hardness measurements were made along the building (xy) and along the plane of the lateral side of the cuboid (xz). The powder used for manufacturing of the samples had a mean particle size of 41μm. It was homogenous with a spherical shape. The specimens were built chiefly from Ti, TiN and AlN. The dendritic microstructure was porous and fine-grained. Some of the aluminum nitride remained unmelted but no porosity was observed in the interface. The formed material was characterized by high hardness exceeding 700 HV0.2 over the entire cross-section.

Keywords: Selective Laser Melting, Composite, SEM, microhardness

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Authors: Maanav M. Patel, Aarsh S. Mistry, Yash A. Dhaduk

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Nowadays, only a small percentage of waste tyres are being land-filled. The Recycled Tyres Rubber is being used in new tyres, in tyre-derived fuel, in civil engineering applications and products, in molded rubber products, in agricultural uses, recreational and sports applications and in rubber modified asphalt applications. The benefits of using rubber modified asphalts are being more widely experienced and recognized, and the incorporation of tyres into asphalt is likely to increase. The technology with much different evidence of success demonstrated by roads built in the last 40 years is the rubberised asphalt mixture obtained through the so-called ‘‘wet process’’ which involves the utilisation of the Recycled Tyre Rubber Modified Bitumen (RTR-MBs). Since 1960s, asphalt mixtures produced with RTRMBs have been used in different parts of the world as solutions for different quality problems and, despite some downsides, in the majority of the cases they have demonstrated to enhance performance of road’s pavement. The present study aims in investigating the experimental performance of the bitumen modified with 15% by weight of crumb rubber varying its sizes. Four different categories of size of crumb rubber will be used, which are coarse (1 mm - 600 μm); medium size (600 μm - 300 μm); fine (300 μm150 μm); and superfine (150 μm - 75 μm). Common laboratory tests will be performed on the modified bitumen using various sizes of crumb rubber and thus analyzed. Marshall Stability method is adopted for mix design.

Keywords: Bitumen, CRMB, Marshall Stability Test, Pavement

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Authors: Rabah Laouar, Yahia Boudra, Adel Satouh, Adrian Boyce

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The ultramafic rocks of the Collo region crop out as « stratified » masses that cross-cut older metamorphic formation of the basement. These rocks are mainly peridotites and serpentinites. The peridotites are composed of olivine, orthopyroxene, clinopyroxene and spinel (chromite). The chemical composition of these lherzolites show a magnesian character with high MgO contents (34.4 to 37.5%), high Cr (0.14 to 0.27%), Ni (0.14 to 0.26%) and Co (34 to 133 ppm) and low CaO and Al₂O₃ (0.02 to 2.2 and 0.5 to 2.8 % respectively). They represent a residue (restite) of a mantle magmas partial melting. The chromite which represents about 2 to 3% of the rock is a ubiquitous mineral and shows two different generations: primary idiomorphic millimetric crystals and secondary very fine, xenomorphic and interstitial aggregates. The primary chromites are alumino-ferro-magnesian crystals. They show high Al₂O₃ (25.77% to 27.36%) and MgO (10.70% to 13.36%). Cr# (100*Cr/ (Al+Cr)) varies between 45 and 48, and Mg# (100*Mg/Mg+Fe₂+) varies between 49 and 59. On the other hand, the secondary interstitial grains are iron-rich chromites; they show low Al₂O₃ (4.67% to 9.54%) and MgO (4.60% to 4.65%). Cr# is relatively high (77 to 88) whereas Mg# show relatively low values, varying between 22 and 25. Oxygen isotopic composition of both types of chromites is consistent with their derivation from a mantle source (ð¹⁸O vary between +3.9 and +5.2‰), though a contribution of ¹⁶O-rich component to the secondary chromites is not ruled out.

Keywords: peridotites, serpentinites, chromite, partial melting, collo, Algeria

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Authors: Peter Joseph Basil Morris, Chhabi Nigam, S. Ramakrishnan, P. Radhakrishna

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This paper brings out the analysis of the airborne Synthetic Aperture Radar (SAR) data using the Range Migration Algorithm (RMA) for the spotlight mode of operation. Unlike in polar format algorithm (PFA), space-variant defocusing and geometric distortion effects are mitigated in RMA since it does not assume that the illuminating wave-fronts are planar. This facilitates the use of RMA for imaging scenarios involving severe differential range curvatures enabling the imaging of larger scenes at fine resolution and at shorter ranges with low center frequencies. The RMA algorithm for the spotlight mode of SAR is analyzed in this paper using the airborne data. Pre-processing operations viz: - range de-skew and motion compensation to a line are performed on the raw data before being fed to the RMA component. Various stages of the RMA viz:- 2D Matched Filtering, Along Track Fourier Transform and Slot Interpolation are analyzed to find the performance limits and the dependence of the imaging geometry on the resolution of the final image. The ability of RMA to compensate for severe differential range curvatures in the two-dimensional spatial frequency domain are also illustrated in this paper.

Keywords: range migration algorithm, spotlight SAR, synthetic aperture radar, matched filtering, slot interpolation

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Authors: Xuguo Zhang, Jimmy Fung, Kenneth Leung, Alexis Lau

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Fine particulate matter concentrations have been decreasing in the past few years while the ozone concentrations are posing an increasing trend in the Greater Bay Area (GBA) of China. A series of control policies have been released to mitigate the country-wide air pollution, however, how to effectively evaluate the exercised control measures and efficiently reveal potential projected mitigation pathways are still limited. By refining an enhanced air-quality-modeling system, this study provides an account of the air quality assessments from 2019 to 2025 to appraise the air quality results and improvement under designed scenarios for assessing the optimum scope for tightening the Air Quality Objectives (AQOs). The results show that it is doable to tighten the 24-hour AQO for SO2 from the World Health Objective air quality guidelines Interim Targets Level-1 (IT-1) (125μg/m3) to IT-2 level (50μg/m3) with the current number of exceedance allowed (three) remains unchanged. It is also possible to tighten the annual AQO for PM2.5 from IT-1 (35 μg/m3) to IT 2 (25 μg/m3), and its 24-hr AQO from IT-1 (75 μg/m3) to IT 2 (50 μg/m3) with the number of exceedances allowed increased from current nine to 35. Regional cooperation under the development of the GBA cooperation are still needed to be focused and strengthen due to the cross-boundary transport characteristics of the air pollution.

Keywords: air quality attainment, Hong Kong, mitigation policy, chemical transport modeling, sensitivity analysis

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Authors: Musatafa Abbas Abbood Albadr, Masri Ayob, Sabrina Tiun, Fahad Taha Al-Dhief, Mohammad Kamrul Hasan

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Breast Cancer (BC) is considered one of the most frequent reasons of cancer death in women between 40 to 55 ages. The BC is diagnosed by using digital images of the FNA (Fine Needle Aspirate) for both benign and malignant tumors of the breast mass. Therefore, this work proposes the Online Sequential Extreme Learning Machine (OSELM) algorithm for diagnosing BC by using the tumor features of the breast mass. The current work has used the Wisconsin Diagnosis Breast Cancer (WDBC) dataset, which contains 569 samples (i.e., 357 samples for benign class and 212 samples for malignant class). Further, numerous measurements of assessment were used in order to evaluate the proposed OSELM algorithm, such as specificity, precision, F-measure, accuracy, G-mean, MCC, and recall. According to the outcomes of the experiment, the highest performance of the proposed OSELM was accomplished with 97.66% accuracy, 98.39% recall, 95.31% precision, 97.25% specificity, 96.83% F-measure, 95.00% MCC, and 96.84% G-Mean. The proposed OSELM algorithm demonstrates promising results in diagnosing BC. Besides, the performance of the proposed OSELM algorithm was superior to all its comparatives with respect to the rate of classification.

Keywords: breast cancer, machine learning, online sequential extreme learning machine, artificial intelligence

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Authors: Cecilia Velasco, Q.

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This study was undertaken to find out the perceived efficiency, appropriateness effectiveness, acceptability and relevance, if at all such exist, of the Mother Tongue Based Multilingual Education Policy under the K-12 Curriculum, as seen by the stakeholders who are directly affected by this policy. The researcher believed that it is right and fitting to get the views and opinions of the people directly involved and/or concerned about this education policy. The results of the study will hopefully guide lawmakers and/or policymakers to fine-tune educational policy or policies. The locale of the study was the DepEd schools in Laguna, (San Pablo City and other nearby cities). The subjects of the study were the teachers (first phase) from the public schools of Department of Education (San Pablo City), in particular and parents (second phase) from nearby cities who are the direct stakeholders of this Policy. To determine the perception of the teachers toward Mother Tongue Based Multilingual Education Policy; its acceptability, efficiency, appropriateness, effectiveness and relevance, factor analysis was used to refine the instrument (questionnaire). To find out the significant difference between the perceptions of the primary and intermediate group of teachers, including those who teach mother tongue and non-mother tongue subjects, t-test of difference between means was employed.

Keywords: DepEd, K12 curriculum, MTBMLE, stakeholders

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Authors: Muller Salah Zaky Toudry

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The complexity arises in defining the development great due to its notion, based on inherent market situations and their requirements, the diverse stakeholders itself and their desired output. An quantitative survey based totally approach was adopted in this optimistic examine. A questionnaire-primarily based survey was performed for the assessment of production fine belief and expectations within the context of excellent development technique. The survey feedback of experts of the leading creation corporations/companies of Pakistan production industry have been analyzed. The monetary ability, organizational shape, and production revel in of the construction companies shaped basis for their selection. The great belief become located to be venture-scope-orientated and taken into consideration as an extra cost for a production assignment. Any excellent improvement technique changed into expected to maximize the profit for the employer, via enhancing the productiveness in a creation project. The look at is beneficial for the construction specialists to evaluate the prevailing creation great perception and the expectations from implementation of any pleasant improvement approach in production projects.

Keywords: correlation analysis, lean construction tools, lean construction, logistic regression analysis, risk management, safety construction quality, expectation, improvement, perception client loyalty, NPS, pre-construction, schedule reduction

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Authors: Rahah Hasan, Faridah Sahari

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This paper describes the development of modern art in Borneo, particularly in Sarawak, Sabah, and Brunei, after the Second World War until the 1970s. This was the period when the British Colonial government dictated the education system, which consequentially inculcated visual art through art and craft subjects imposed on all vernacular schools in Borneo. British influence within the state governance, social, and education system designed with Western ideology created not only a westernized society and mindset but at the same time generated artistic opportunities for emerging local painters to be involved in the initiation of Modern Art in Borneo. Through the historical method and analysis of primary and secondary data, it was obvious that the existence of colonial government departments and institutions such as museums and teaching colleges, and other social organizations in Borneo at that time contributed significantly to the artistic movement. The similar structure and motivation of development in other areas of Borneo confirmed that artistic affirmation of modern art advanced homogenously. Their understanding of easel painting as well as a unique interpretation of culture once distanced from traditional art, resulting in a new visual image that transcended their ethnicity and identity through new mediums and tools. These meticulous interventions modestly visualized in each painting, as discussed in this paper, hopefully, will give a deeper understanding and appreciation of the history of modern art in Borneo.

Keywords: art history, Borneo art, fine art, modern art

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Authors: Samuel Nii Tackie, Oyebade K. Oyedotun, Ebenezer O. Olaniyi, Adnan Khashman

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Artificial neural networks have been used in different fields of artificial intelligence, and more specifically in machine learning. Although, other machine learning options are feasible in most situations, but the ease with which neural networks lend themselves to different problems which include pattern recognition, image compression, classification, computer vision, regression etc. has earned it a remarkable place in the machine learning field. This research exploits neural networks as a data mining tool in predicting the number of times a student repeats a course, considering some attributes relating to the course itself, the teacher, and the particular student. Neural networks were used in this work to map the relationship between some attributes related to students’ course assessment and the number of times a student will possibly repeat a course before he passes. It is the hope that the possibility to predict students’ performance from such complex relationships can help facilitate the fine-tuning of academic systems and policies implemented in learning environments. To validate the power of neural networks in data mining, Turkish students’ performance database has been used; feedforward and radial basis function networks were trained for this task; and the performances obtained from these networks evaluated in consideration of achieved recognition rates and training time.

Keywords: artificial neural network, data mining, classification, students’ evaluation

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Authors: Atilla Bayram

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This paper presents the trajectory tracking control of a spatial redundant hybrid manipulator. This manipulator consists of two parallel manipulators which are a variable geometry truss (VGT) module. In fact, each VGT module with 3-degress of freedom (DOF) is a planar parallel manipulator and their operational planes of these VGT modules are arranged to be orthogonal to each other. Also, the manipulator contains a twist motion part attached to the top of the second VGT module to supply the missing orientation of the endeffector. These three modules constitute totally 7-DOF hybrid (parallel-parallel) redundant spatial manipulator. The forward kinematics equations of this manipulator are obtained, then, according to these equations, the inverse kinematics is solved based on an optimization with the joint limit avoidance. The dynamic equations are formed by using virtual work method. In order to test the performance of the redundant manipulator and the controllers presented, two different desired trajectories are followed by using the computed force control method and a switching control method. The switching control method is combined with the computed force control method and genetic algorithm. In the switching control method, the genetic algorithm is only used for fine tuning in the compensation of the trajectory tracking errors.

Keywords: computed force method, genetic algorithm, hybrid manipulator, inverse kinematics of redundant manipulators, variable geometry truss

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Authors: Heather E. Ewart, Keith Jensen, Rebecca N. Cliffe

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Fragmentation and changes in the structural composition of tropical forests – as a result of intensifying anthropogenic disturbance – are increasing pressures on local biodiversity. Species with low dispersal abilities have some of the highest extinction risks in response to environmental change, as even small-scale environmental variation can substantially impact their space use and energetic balance. Understanding the implications of forest disturbance is therefore essential, ultimately allowing for more effective and targeted conservation initiatives. Here, the impact of different levels of forest disturbance on the space use, energetics, movement and behavior of 18 brown-throated sloths (Bradypus variegatus) were assessed in the South Caribbean of Costa Rica. A multi-scale framework was used to measure forest disturbance, including large-scale (landscape-level classifications) and fine-scale (within and surrounding individual home ranges) forest composition. Three landscape-level classifications were identified: primary forests (undisturbed), secondary forests (some disturbance, regenerating) and urban forests (high levels of disturbance and fragmentation). Finer-scale forest composition was determined using measurements of habitat structure and quality within and surrounding individual home ranges for each sloth (home range estimates were calculated using autocorrelated kernel density estimation [AKDE]). Measurements of forest quality included tree connectivity, density, diameter and height, species richness, and percentage of canopy cover. To determine space use, energetics, movement and behavior, six sloths in urban forests, seven sloths in secondary forests and five sloths in primary forests were tracked using a combination of Very High Frequency (VHF) radio transmitters and Global Positioning System (GPS) technology over an average period of 120 days. All sloths were also fitted with micro data-loggers (containing tri-axial accelerometers and pressure loggers) for an average of 30 days to allow for behavior-specific movement analyses (data analysis ongoing for data-loggers and primary forest sloths). Data-loggers included determination of activity budgets, circadian rhythms of activity and energy expenditure (using the vector of the dynamic body acceleration [VeDBA] as a proxy). Analyses to date indicate that home range size significantly increased with the level of forest disturbance. Female sloths inhabiting secondary forests averaged 0.67-hectare home ranges, while female sloths inhabiting urban forests averaged 1.93-hectare home ranges (estimates are represented by median values to account for the individual variation in home range size in sloths). Likewise, home range estimates for male sloths were 2.35 hectares in secondary forests and 4.83 in urban forests. Sloths in urban forests also used nearly double (median = 22.5) the number of trees as sloths in the secondary forest (median = 12). These preliminary data indicate that forest disturbance likely heightens the energetic requirements of sloths, a species already critically limited by low dispersal ability and rates of energy acquisition. Energetic and behavioral analyses from the data-loggers will be considered in the context of fine-scale forest composition measurements (i.e., habitat quality and structure) and are expected to reflect the observed home range and movement constraints. The implications of these results are far-reaching, presenting an opportunity to define a critical index of habitat connectivity for low dispersal species such as sloths.

Keywords: biodiversity conservation, forest disturbance, movement ecology, sloths

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Authors: A. P. I. Popoola, O. S. I. Fayomi, V. S. Aigbodion

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Mild steel has found many engineering applications due to its great formability, availability, low cost and good mechanical properties among others. However its functionality and durability is subject of concern due to corrosion deterioration. Based on these Yttrium is selected as reinforcing particles using electroplating process in this work to enhance the corrosion resistance. Bath formulation of zinc-yttrium was prepared at moderated temperature and pH, to coat mild steel sample. Corrosion and wear behaviour were analyzed using electrochemical potentiostat and abrasive test rig. The composition and microstructure of coated films were investigated standard method. The microstructure of the deposited plate obtained from optimum (10%Yttrium) bath revealed fine-grained deposit of the alloy in the presence of condensation product and hence modified the morphology of zinc–yttrium alloy deposit. It is demonstrated that by adding yttria particles, mild steel can be strengthened with improved polarization behaviour and higher resistance to corrosive in sodium chloride solutions. Microhardness of the coating compared to plain mild steel have increased before and after heat treatment, and an increased wear resistance was also obtained from the modified coating of zinc-yttrium.

Keywords: microhardness, zinc-yttrium, coating, mild steel, microstructure, wear, corrosion

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Authors: Dauda A. Oladosu, Kamorudeen A Olaiya, Abdurahman Bello

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The deployment of smart meters by utility providers to gather fine grained spatiotemporal consumption data has grossly influenced the consumers’ emotion and behavior towards energy utilization. The quest for reduction in power consumption is now a subject of concern and one the methods adopted by the consumers to achieve this is Non-intrusive Load (appliance) Monitoring. Hence, this work presents performance Analysis of Domotics System as a tool for load monitoring when integrated with Consumer Control Unit of residential building. The system was developed with basic elements which enhance remote sensing, DTMF (Dual Tone Multi-frequency) recognition and cryptic messaging when specific task was performed. To demonstrate its applicability and suitability, this prototype was used consistently for six months at different load demands and the utilities consumed were documented. The results obtained shows good response when phone dialed, and the packet delivery of feedback SMS was quite satisfactory, making the implemented system to be of good quality with affordable cost and performs the desired functions. Besides, comparative analysis showed notable reduction in energy consumption and invariably lessened electrical bill of the consumer.

Keywords: automation, domotics, energy, load, remote, schedule

Procedia PDF Downloads 317

Authors: Julien Caudeville, Muriel Ismert

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Analyzing the relationship between environment and health has become a major preoccupation for public health as evidenced by the emergence of the French national plans for health and environment. These plans have identified the following two priorities: (1) to identify and manage geographic areas, where hotspot exposures are suspected to generate a potential hazard to human health; (2) to reduce exposure inequalities. At a regional scale and fine resolution of exposure outcome prerequisite, environmental monitoring networks are not sufficient to characterize the multidimensionality of the exposure concept. In an attempt to increase representativeness of spatial exposure assessment approaches, risk composite indicators could be built using additional available databases and theoretical framework approaches to combine factor risks. To achieve those objectives, combining data process and transfer modeling with a spatial approach is a fundamental prerequisite that implies the need to first overcome different scientific limitations: to define interest variables and indicators that could be built to associate and describe the global source-effect chain; to link and process data from different sources and different spatial supports; to develop adapted methods in order to improve spatial data representativeness and resolution. A GIS-based modeling platform for quantifying human exposure to chemical substances (PLAINE: environmental inequalities analysis platform) was used to build health risk indicators within the Lorraine region (France). Those indicators combined chemical substances (in soil, air and water) and noise risk factors. Tools have been developed using modeling, spatial analysis and geostatistic methods to build and discretize interest variables from different supports and resolutions on a 1 km2 regular grid within the Lorraine region. By example, surface soil concentrations have been estimated by developing a Kriging method able to integrate surface and point spatial supports. Then, an exposure model developed by INERIS was used to assess the transfer from soil to individual exposure through ingestion pathways. We used distance from polluted soil site to build a proxy for contaminated site. Air indicator combined modeled concentrations and estimated emissions to take in account 30 polluants in the analysis. For water, drinking water concentrations were compared to drinking water standards to build a score spatialized using a distribution unit serve map. The Lden (day-evening-night) indicator was used to map noise around road infrastructures. Aggregation of the different factor risks was made using different methodologies to discuss weighting and aggregation procedures impact on the effectiveness of risk maps to take decisions for safeguarding citizen health. Results permit to identify pollutant sources, determinants of exposure, and potential hotspots areas. A diagnostic tool was developed for stakeholders to visualize and analyze the composite indicators in an operational and accurate manner. The designed support system will be used in many applications and contexts: (1) mapping environmental disparities throughout the Lorraine region; (2) identifying vulnerable population and determinants of exposure to set priorities and target for pollution prevention, regulation and remediation; (3) providing exposure database to quantify relationships between environmental indicators and cancer mortality data provided by French Regional Health Observatories.

Keywords: health risk, environment, composite indicator, hotspot areas

Procedia PDF Downloads 247

Authors: Muhanad Al-Jubouri

Abstract:

A local scour is the most important of the several scours impacting bridge performance and security. Even though scour is widespread in bridges, especially during flood seasons, the experimental tests could not be applied to many standard highway bridges. A computational fluid dynamics numerical model was used to solve the problem of calculating local scouring and deposition for non-cohesive silt and clear water conditions near single and double cylindrical piers with the effect of floating debris. When FLOW-3D software is employed with the Rang turbulence model, the Nilsson bed-load transfer equation and fine mesh size are considered. The numerical findings of single cylindrical piers correspond pretty well with the physical model's results. Furthermore, after parameter effectiveness investigates the range of outcomes based on predicted user inputs such as the bed-load equation, mesh cell size, and turbulence model, the final numerical predictions are compared to experimental data. When the findings are compared, the error rate for the deepest point of the scour is equivalent to 3.8% for the single pier example.

Keywords: local scouring, non-cohesive, clear water, computational fluid dynamics, turbulence model, bed-load equation, debris

Procedia PDF Downloads 69