Search results for: distance based analysis

Authors: Xu Zhang

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This article unveils an indicator of language contact between English and Cantonese in one of the Outer Circle Englishes, Hong Kong (HK) English, through an empirical investigation into 1000 tokens from the Global Web-based English (GloWbE) corpus, employing frequency analysis and logistic regression analysis. It is perceived that Cantonese and general Chinese are contextually marked by an integral underlying thinking pattern. Chinese speakers exhibit a reliance on semantic context over syntactic rules and lexical forms. This linguistic trait carries over to their use of English, affording greater flexibility to formal elements in constructing English sentences. The study focuses on the syntactic positioning of the focusing subjunct ‘also’, a linguistic element used to add new or contrasting prominence to specific sentence constituents. The English language generally allows flexibility in the relative position of 'also’, while there is a preference for close marking relationships. This article shifts attention to Hong Kong, where Cantonese and English converge, and 'also' finds counterparts in Cantonese ‘jaa’ and Mandarin ‘ye’. Employing a corpus-based data-driven method, we investigate the syntactic position of 'also' in both HK and GB English. The study aims to ascertain whether HK English exhibits a greater 'syntactic freedom,' allowing for a more distant marking relationship with 'also' compared to GB English. The analysis involves a random extraction of 500 samples from both HK and GB English from the GloWbE corpus, forming a dataset (N=1000). Exclusions are made for cases where 'also' functions as an additive conjunct or serves as a copulative adverb, as well as sentences lacking sufficient indication that 'also' functions as a focusing particle. The final dataset comprises 820 tokens, with 416 for GB and 404 for HK, annotated according to the focused constituent and the relative position of ‘also’. Frequency analysis reveals significant differences in the relative position of 'also' and marking relationships between HK and GB English. Regression analysis indicates a preference in HK English for a distant marking relationship between 'also' and its focused constituent. Notably, the subject and other constituents emerge as significant predictors of a distant position for 'also.' Together, these findings underscore the nuanced linguistic dynamics in HK English and contribute to our understanding of language contact. It suggests that future pedagogical practice should consider incorporating the syntactic variation within English varieties, facilitating leaners’ effective communication in diverse English-speaking environments and enhancing their intercultural communication competence.

Keywords: also, Cantonese, English, focus marker, frequency analysis, language contact, logistic regression analysis

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Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Elena Tkachenko, Elena Rogova, Daria Koval

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The paper examines the ways of cash flows forecasting in the dynamic external environment. The so-called new reality in economy lowers the predictability of the companies’ performance indicators due to the lack of long-term steady trends in external conditions of development and fast changes in the markets. The traditional methods based on the trend analysis lead to a very high error of approximation. The macroeconomic situation for the last 10 years is defined by continuous consequences of financial crisis and arising of another one. In these conditions, the instruments of forecasting on the basis of fuzzy sets show good results. The fuzzy sets based models turn out to lower the error of approximation to acceptable level and to provide the companies with reliable cash flows estimation that helps to reach the financial stability. In the paper, the applicability of the model of cash flows forecasting based on fuzzy logic was analyzed.

Keywords: cash flow, industrial enterprise, forecasting, fuzzy sets

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Authors: Ting (Grace) Lin, Jianhong (Cecilia) Xia, Todd Robinson

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Accessibility analysis, examining people’s ability to access facilities and destinations, is a fundamental assessment for transport planning, policy making, and social exclusion research. Dynamic accessibility which measures accessibility in real-time traffic environment has been an advanced accessibility indicator in transport research. It is also a useful indicator to help travelers to understand travel time daily variability, assists traffic engineers to monitor traffic congestions, and finally develop effective strategies in order to mitigate traffic congestions. This research involved real-time traffic information by collecting travel time data with 15-minute interval via the TomTom^® API. A framework for measuring dynamic accessibility was then developed based on the gravity theory and accessibility dichotomy theory through space and time interpolation. Finally, the dynamic accessibility can be derived at any given time and location under dynamic accessibility spatial analysis framework.

Keywords: dynamic accessibility, hot spot, transport research, TomTom® API

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Authors: Maria Fernanda Ordoñez Martinez, Alvaro Mauricio Montenegro

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This work presents a statistical methodology for measuring and founding constructs in Latent Semantic Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations present on Item Response Theory. More precisely, we propose initially reducing dimensionality with specific use of Principal Component Analysis for the linguistic data and then, producing axes of groups made from a clustering analysis of the semantic data. This approach allows the user to give meaning to previous clusters and found the real latent structure presented by data. The methodology is applied in a set of real semantic data presenting impressive results for the coherence, speed and precision.

Keywords: semantic analysis, factorial analysis, dimension reduction, penalized logistic regression

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Authors: Julie Anne Braun, Leonardo D. da Fonseca, Gerson C. Parreira, Ricardo J. E. Andrade

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Polyurethanes (PU) are multifunctional polymers used across various industries. In construction, thermosetting polyurethanes are applied as coatings for flooring, paints, and waterproofing. They are widely specified in Brazil for waterproofing concrete structures like roof slabs and parking decks. Applied to concrete, they form a fully adhered membrane, providing a protective barrier with low water absorption, high chemical resistance, impermeability to liquids, and low vapor permeability. Their mechanical properties, including tensile strength (1 to 35 MPa) and Shore A hardness (83 to 88), depend on resin molecular weight and functionality, often using Methylene diphenyl diisocyanate. PU production, reliant on fossil-derived isocyanates and polyols, contributes significantly to carbon emissions. Sustainable alternatives, such as biopolyurethanes from renewable sources, are needed. Castor oil is a viable option for synthesizing sustainable polyurethanes. As a bio-based feedstock, castor oil is extensively cultivated in Brazil, making it a feasible option for the national market and ranking third internationally. This study aims to develop and characterize castor oil-based biopolyurethane for high-performance waterproofing and coating applications. A comparative analysis between castor oil-based PU and polyether polyol-based PU was conducted. Mechanical tests (tensile strength, Shore A hardness, abrasion resistance) and surface properties (contact angle, water absorption) were evaluated. Thermal, chemical, and morphological properties were assessed using thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The results demonstrated that both polyurethanes exhibited high mechanical strength. Specifically, the tensile strength for castor oil-based PU was 19.18 MPa, compared to 12.94 MPa for polyether polyol-based PU. Similarly, the elongation values were 146.90% for castor oil-based PU and 135.50% for polyether polyol-based PU. Both materials exhibited satisfactory performance in terms of abrasion resistance, with mass loss of 0.067% for castor oil PU and 0.043% for polyether polyol PU and Shore A hardness values of 89 and 86, respectively, indicating high surface hardness. The results of the water absorption and contact angle tests confirmed the hydrophilic nature of polyether polyol PU, with a contact angle of 58.73° and water absorption of 2.53%. Conversely, the castor oil-based PU exhibited hydrophobic properties, with a contact angle of 81.05° and water absorption of 0.45%. The results of the FTIR analysis indicated the absence of a peak around 2275 cm-1, which suggests that all of the NCO groups were consumed in the stoichiometric reaction. This conclusion is supported by the high mechanical test results. The TGA results indicated that polyether polyol PU demonstrated superior thermal stability, exhibiting a mass loss of 13% at the initial transition (around 310°C), in comparison to castor oil-based PU, which experienced a higher initial mass loss of 25% at 335°C. In summary, castor oil-based PU demonstrated mechanical properties comparable to polyether polyol PU, making it suitable for applications such as trafficable coatings. However, its higher hydrophobicity makes it more promising for watertightness. Increasing environmental concerns necessitate reducing reliance on non-renewable resources and mitigating the environmental impacts of polyurethane production. Castor oil is a viable option for sustainable polyurethanes, aligning with emission reduction goals and responsible use of natural resources.

Keywords: polyurethane, castor oil, sustainable, waterproofing, construction industry

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Authors: Mohammad Ghahramani, Fahimeh Saei Manesh

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Winning a soccer game is based on thorough and deep analysis of the ongoing match. On the other hand, giant gambling companies are in vital need of such analysis to reduce their loss against their customers. In this research work, we perform deep, real-time analysis on every soccer match around the world that distinguishes our work from others by focusing on particular seasons, teams and partial analytics. Our contributions are presented in the platform called “Analyst Masters.” First, we introduce various sources of information available for soccer analysis for teams around the world that helped us record live statistical data and information from more than 50,000 soccer matches a year. Our second and main contribution is to introduce our proposed in-play performance evaluation. The third contribution is developing new features from stable soccer matches. The statistics of soccer matches and their odds before and in-play are considered in the image format versus time including the halftime. Local Binary patterns, (LBP) is then employed to extract features from the image. Our analyses reveal incredibly interesting features and rules if a soccer match has reached enough stability. For example, our “8-minute rule” implies if 'Team A' scores a goal and can maintain the result for at least 8 minutes then the match would end in their favor in a stable match. We could also make accurate predictions before the match of scoring less/more than 2.5 goals. We benefit from the Gradient Boosting Trees, GBT, to extract highly related features. Once the features are selected from this pool of data, the Decision trees decide if the match is stable. A stable match is then passed to a post-processing stage to check its properties such as betters’ and punters’ behavior and its statistical data to issue the prediction. The proposed method was trained using 140,000 soccer matches and tested on more than 100,000 samples achieving 98% accuracy to select stable matches. Our database from 240,000 matches shows that one can get over 20% betting profit per month using Analyst Masters. Such consistent profit outperforms human experts and shows the inefficiency of the betting market. Top soccer tipsters achieve 50% accuracy and 8% monthly profit in average only on regional matches. Both our collected database of more than 240,000 soccer matches from 2012 and our algorithm would greatly benefit coaches and punters to get accurate analysis.

Keywords: soccer, analytics, machine learning, database

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Authors: Azimollah Aleshzadeh, Enver Vural Yavuz

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The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection.

Keywords: entropy weight method, evidence belief function, information content model, landslide susceptibility mapping

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Authors: Faisal Nouroz, Mukaramin Mukaramin

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Of the transposable elements (TEs), the retrotransposons are the most copious elements identified from many sequenced genomes. They have played a major role in genome evolution, rearrangement, and expansions based on their copy and paste mode of proliferation. They are further divided into LTR and Non-LTR retrotransposons. The purpose of the current study was to identify the LTR REs in sequenced Phoenix dactylifera genome and to study their structural diversity. A total of 150 P. dactylifera BAC sequences with > 60kb sizes were randomly retrieved from National Center for Biotechnology Information (NCBI) database and screened for the presence of LTR retrotransposons. Seven bacterial artificial chromosomes (BAC) sequences showed full-length LTR Retrotransposons with 4 Copia and 3 Gypsy families having variable copy numbers in respective families. Reverse transcriptase (RT) domain was found as the most conserved domain among Copia and Gypsy superfamilies and was used to deduce evolutionary analysis. The amino acid residues among various RT sequences showed variability in their percentages indicating post divergence evolution. Amino acid Leucine was found in highest proportions followed by Lysine, while Methionine and Tryptophan were in lowest percentages. The phylogenetic analysis based on RT domains confirmed that although having most conserved RT regions, several evolutionary events occurred causing nucleotide polymorphisms and hence clustering of Gypsy and Copia superfamilies into their respective lineages. The study will be helpful in identification and annotation of these elements in other species and genera and their distribution patterns on chromosomes by fluorescent in situ hybridization techniques.

Keywords: transposable elements, Phoenix dactylifera, retrotransposons, phylogenetic analysis

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Authors: Zhang Dongqing

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Concern for students' mental health and the application of intelligent advanced technologies are driving changes in teaching models. The traditional teacher-centered classroom is beginning to transform into a student-centered smart interactive learning environment. Nowadays, smart classrooms are compatible with constructivist learning. This theory emphasizes the role of teachers in the teaching process as helpers and facilitators of knowledge construction, and students learn by interacting with them. The spatial design of classrooms is closely related to the teaching model and should also be developed in the direction of smart classroom design. The goal is to explore the impact of smart classroom layout on student-centered teaching environment and teacher-student interaction under the guidance of constructivist learning theory, by combining the design process and feedback analysis of the smart transformation project on the campus of Tongji University in Shanghai. During the research process, the theoretical basis of constructivist learning was consolidated through literature research and case analysis. The integration and visual field analysis of the traditional and transformed indoor floor plans were conducted using space syntax tools. Finally, questionnaire surveys and interviews were used to collect data. The main conclusions are as followed: flexible spatial layouts can promote students' learning effects and mental health; the interactivity of smart classroom layouts is different and needs to be combined with different teaching models; the public areas of teaching buildings can also improve the interactive learning atmosphere by adding discussion space. This article provides a data-based research basis for improving students' learning effects and mental health, and provides a reference for future smart classroom design.

Keywords: spatial layout, smart classroom, space syntax, renovation, educational environment

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Authors: Wenxuan Li, Lei Li, Jin Li, Yuanhang He

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This paper designed a secure chip for IoT communication security integrated with the PUF-based firmware protection scheme. Then, the Xilinx Kintex-7 and STM-32 were used for the prototype verification. Firmware protection worked well on FPGA and embedded platforms. For the ASIC implementation of the PUF module, contact PUF is chosen. The post-processing method and its improvement are analyzed with emphasis. This paper proposed a more efficient post-processing method for contact PUF named SXOR, which has practical value for realizing lightweight security modules in IoT devices. The analysis was carried out under the hypothesis that the contact holes are independent and combine the existing data in the open literature. The post-processing effects of SXOR and XOR are basically the same under the condition that the proposed post-processing circuit occupies only 50.6% of the area of XOR. The average Hamming weight of the PUF output bit sequence obtained by the proposed post-processing method is 0.499735, and the average Hamming weight obtained by the XOR-based post-processing method is 0.499999.

Keywords: PUF, IoT, authentication, secure communication, encryption, XOR

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Authors: Mariia Timofeeva, Andrew Ooi, Eric K. W. Poon, Peter Barlis

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Atherosclerotic plaque build-up, commonly known as stenosis, limits blood flow and hence oxygen and nutrient supplies to the heart muscle. Thus, assessment of its severity is of great interest to health professionals. Numerical simulation of the fractional flow reserve (FFR) has proved to be well correlated with invasively measured FFR used for physiological assessment of the severity of coronary stenosis in arteries. Atherosclerosis may impact the diseased artery in several locations causing serial stenoses, which is a complicated subset of coronary artery disease that requires careful treatment planning. However, hemodynamic of the serial sequential stenoses in coronary arteries has not been extensively studied. The hemodynamics of the serial stenoses is complex because the stenoses in the series interact and affect the flow through each other. To address this, serial stenoses in a 3.4 mm left anterior descending (LAD) artery are examined in this study. Two diameter stenoses (DS) are considered, 30 and 50 percent of the reference diameter. Serial stenoses configurations are divided into three groups based on the order of the stenoses in the series, spacing between them, and deviation of the stenoses’ symmetry (eccentricity). A patient-specific pulsatile waveform is used in the simulations. Blood flow within the stenotic artery is assumed to be laminar, Newtonian, and incompressible. Results for the FFR are reported. Based on the simulation results, it can be deduced that the larger drop in pressure (smaller value of the FFR) is expected when the percentage of the second stenosis in the series is bigger. Varying the distance between the stenoses affects the location of the maximum drop in the pressure, while the minimal FFR in the artery remains unchanged. Eccentric serial stenoses are characterized by a noticeably larger decrease in pressure through the stenoses and by the development of the chaotic flow downstream of the stenoses. The largest drop in the pressure (about 4% difference compared to the axisymmetric case) is obtained for the serial stenoses, where both the stenoses are highly eccentric with the centerlines deflected to the different sides of the LAD. In conclusion, varying configuration of the sequential serial stenoses results in a different distribution of FFR through the LAD. Results presented in this study provide insight into the clinical assessment of the severity of the coronary serial stenoses, which is proved to depend on the relative position of the stenoses and the deviation of the stenoses’ symmetry.

Keywords: computational fluid dynamics, coronary artery, fractional flow reserve, serial stenoses

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Authors: G. A. Rombach, A. Faron

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Crack formation and growth in reinforced concrete members are, in many cases, the cause of the collapse of technical structures. Such serious failures impair structural behavior and can also damage property and persons. An intensive investigation of the crack propagation is indispensable. Numerical methods are being developed to analyze crack growth in an element and to detect fracture failure at an early stage. For reinforced concrete components, however, further research and action are required in the analysis of shear cracks. This paper presents numerical simulations and continuum mechanical modeling of bending shear crack propagation in a three-dimensional reinforced concrete beam without transverse reinforcement. The analysis will provide a further understanding of crack growth and redistribution of inner forces in concrete members. As a numerical method to map discrete cracks, the extended finite element method (XFEM) is applied. The crack propagation is compared with the smeared crack approach using concrete damage plasticity. For validation, the crack patterns of real experiments are compared with the results of the different finite element models. The evaluation is based on single span beams under bending. With the analysis, it is possible to predict the fracture behavior of concrete members.

Keywords: concrete damage plasticity, crack propagation, extended finite element method, fracture mechanics

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Authors: Ankit Nagar, Dinesh Kumar Nauriyal, Sukhpal Singh

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This paper examines the key determinants of farmers’ access to agricultural extension services, sources of agricultural extension services preferred and accessed by the farmers. An ordered logistic regression model was used to analyse the data of the 360 sample households based on a primary survey conducted in western Uttar Pradesh, India. The study finds that farmers' decision to engage in the agricultural extension programme is significantly influenced by factors such as education level, gender, farming experience, social group, group membership, farm size, credit access, awareness about the extension scheme, farmers' perception, and distance from extension sources. The most intriguing finding of this study is that the progressive farmers, which have long been regarded as a major source of knowledge diffusion, are the most distrusted sources of information as they are suspected of withholding vital information from potential beneficiaries. The positive relationship between farm size and ‘Access’ underlines that the extension services should revisit their strategies for targeting more marginal and small farmers constituting over 85 percent of the agricultural households by incorporating their priorities in their outreach programs. The study suggests that marginal and small farmers' productive potential could still be greatly augmented by the appropriate technology, advisory services, guidance, and improved market access. Also, the perception of poor quality of the public extension services can be corrected by initiatives aimed at building up extension workers' capacity.

Keywords: agriculture, access, extension services, ordered logistic regression

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Authors: Sadao Araki, Daisuke Gondo, Satoshi Imasaka, Hideki Yamamoto

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The separation of organic compounds from aqueous solutions is a key technology for recycling valuable organic compounds and for the treatment of wastewater. The wastewater from chemical plants often contains organic compounds such as ethyl acetate (EA), methylethyl ketone (MEK) and isopropyl alcohol (IPA). In this study, we prepared hydrophobic silica membranes by a sol-gel method. We used phenyltrimethoxysilane (PhTMS), ethyltrimethoxysilan (ETMS), Propyltrimethoxysilane (PrTMS), N-butyltrimethoxysilane (BTMS), N-Hexyltrimethoxysilane (HTMS) as silica sources to introduce each functional groups on the membrane surface. Cetyltrimethyl ammonium bromide (CTAB) was used as a molecular template to create suitable pore that enable the permeation of organic compounds. These membranes with five different functional groups were characterized by SEM, FT-IR, and permporometry. Thicknesses and pore diameters of silica layer for all membrane were about 1.0 μm and about 1 nm, respectively. In other words, functional groups had an insignificant effect on the membrane thicknesses and the formation of the pore by CTAB. We confirmed the effect of functional groups on the flux and separation factor for ethyl acetate (EA), methyl ethyl ketone, acetone and 1-butanol (1-BtOH) /water mixtures. All membranes showed a high flux for ethyl acetate compared with other compounds. In particular, the hydrophobic silica membrane prepared by using BTMS showed 0.75 kg m-2 h-1 of flux for EA. For all membranes, the fluxes of organic compounds showed the large values in the order corresponding to EA > MEK > acetone > 1-BtOH. On the other hand, carbon chain length of functional groups among ETMS, PrTMS, BTMS, PrTMS and HTMS did not have a major effect on the organic flux. Although we confirmed the relationship between organic fluxes and organic molecular diameters or fugacity of organic compounds, these factors had a low correlation with organic fluxes. It is considered that these factors affect the diffusivity. Generally, permeation through membranes is based on the diffusivity and solubility. Therefore, it is deemed that organic fluxes through these hydrophobic membranes are strongly influenced by solubility. We tried to estimate the organic fluxes by Hansen solubility parameter (HSP). HSP, which is based on the cohesion energy per molar volume and is composed of dispersion forces (δd), intermolecular dipole interactions (δp), and hydrogen-bonding interactions (δh), has recently attracted attention as a means for evaluating the resolution and aggregation behavior. Evaluation of solubility for two substances can be represented by using the Ra [(MPa)1/2] value, meaning the distance of HSPs for both of substances. A smaller Ra value means a higher solubility for each substance. On the other hand, it can be estimated that the substances with large Ra value show low solubility. We established the correlation equation, which was based on Ra, of organic flux at low concentrations of organic compounds and at 295-325 K.

Keywords: hydrophobic, membrane, Hansen solubility parameter, functional group

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Authors: Clara Inés Pardo Martínez

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In emerging economies, recycling is an opportunity for the cities to increase the lifespan of sanitary landfills, reduce the costs of the solid waste management, decrease the environmental problems of the waste treatment through reincorporate waste in the productive cycle and protect and develop people’s livelihoods of informal waste pickers. However, few studies have analysed the possibilities and strategies to integrate formal and informal sectors in the solid waste management for the benefit of both. This study seek to make a strength, weakness, opportunity, and threat (SWOT) analysis in three recycling associations of Bogotá with the aim to understand and determine the situation of recycling from perspective of informal sector in its transition to enter as authorized waste providers. Data used in the analysis are derived from multiple strategies such as literature review, the Bogota’s recycling database, focus group meetings, governmental reports, national laws and regulations and specific interviews with key stakeholders. Results of this study show as the main stakeholders of formal and informal sector of waste management can identify the internal and internal conditions of recycling in Bogotá. Several strategies were designed based on the SWOTs determined, could be useful for Bogotá to advance and promote recycling as a key strategy for integrated sustainable waste management in the city.

Keywords: Bogotá, recycling, solid waste management, SWOT analysis

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Authors: Mina Salamatmanesh, Elizabeth Fitzpatrick, Tim Ramsay, Josee Lagacé, Lindsey Sikora, JoAnne Whittingham

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Introduction: Hearing loss (HL) is one of the most common disorders that presents at birth and in early childhood. Universal newborn hearing screening (UNHS) has been adopted based on the assumption that with early identification of HL, children will have access to optimal amplification and intervention at younger ages, therefore, taking advantage of the brain’s maximal plasticity. One particular challenge for parents in the early years is achieving consistent hearing aid (HA) use which is critical to the child’s development and constitutes the first step in the rehabilitation process. This study examined the consistency of hearing aid use in young children based on data logging information documented during audiology sessions in the first three years after hearing aid fitting. Methodology: The first 100 children who were diagnosed with bilateral HL before 72 months of age since 2003 to 2015 in a pediatric audiology clinic and who had at least two hearing aid follow-up sessions with available data logging information were included in the study. Data from each audiology session (age of child at the session, average hours of use per day (for each ear) in the first three years after HA fitting) were collected. Clinical characteristics (degree of hearing loss, age of HA fitting) were also documented to further understanding of factors that impact HA use. Results: Preliminary analysis of the results of the first 20 children shows that all of them (100%) have at least one data logging session recorded in the clinical audiology system (Noah). Of the 20 children, 17(85%) have three data logging events recorded in the first three years after HA fitting. Based on the statistical analysis of the first 20 cases, the median hours of use in the first follow-up session after the hearing aid fitting in the right ear is 3.9 hours with an interquartile range (IQR) of 10.2h. For the left ear the median is 4.4 and the IQR is 9.7h. In the first session 47% of the children use their hearing aids ≤5 hours, 12% use them between 5 to 10 hours and 22% use them ≥10 hours a day. However, these children showed increased use by the third follow-up session with a median (IQR) of 9.1 hours for the right ear and 2.5, and of 8.2 hours for left ear (IQR) IQR is 5.6 By the third follow-up session, 14% of children used hearing aids ≤5 hours, while 38% of children used them ≥10 hours. Based on the primary results, factors like age and level of HL significantly impact the hours of use. Conclusion: The use of data logging information to assess the actual hours of HA provides an opportunity to examine the: a) challenges of families of young children with HAs, b) factors that impact use in very young children. Data logging when used collaboratively with parents, can be a powerful tool to identify problems and to encourage and assist families in maximizing their child’s hearing potential.

Keywords: hearing loss, hearing aid, data logging, hours of use

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Authors: Shane David van Zyl, A. J. Burger

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The global green energy shift has placed significant value on the production of green hydrogen and its derivatives. The study examines the impact on capital expenditure (CAPEX), operational expenditure (OPEX), levelized cost, and environmental impact, depending on the relationship between various production capacities of potable water, green hydrogen, and green ammonia. A model-based sensitivity analysis approach was used to determine the relevance of various process parameters in the production of potable water combined with green hydrogen or green ammonia production. The effects of changes on CAPEX, OPEX and levelized costs of the products were determined. Furthermore, a qualitative environmental impact analysis was done to determine the effect on the environment. The findings indicated the individual process unit contribution to the overall CAPEX and OPEX while also determining the major contributors to changes in the levelized costs of products. The results emphasize the difference in costs associated with potable water, green hydrogen, and green ammonia production, indicating the extent to which potable water production costs become insignificant in the complete process, which, therefore, can have a large social benefit through increased potable water production resulting in decreased water scarcity in the south-west African region.

Keywords: CAPEX and OPEX, desalination, green hydrogen and green ammonia, sensitivity analysis

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Authors: Jame O. Ezema, Odenigbo Veronica

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The study covers the topic Information Communication and Technology (ICTs) knowledge as a way of enhancing Literacy and Lifelong learning in Nigeria. This work delved into defining of ICTs. Types of ICTs and media technologies were also mentioned. It further explained how ICTs can be strengthened and the uses of ICTs in education was duly emphasized. The paper also enumerated some side effects of ICTs on learners while the role of ICTs in enhancing literacy was explained. The study carried out strategies to use ICTs meaningfully in Literacy Programs and also emphasized the word lifelong learning in Nigeria. Some recommendations were made towards acquiring ICTs knowledge, so as to enhance Literacy and Lifelong learning in Nigeria.

Keywords: literacy, distance-learning, life-long learning for sustainable development, e-learning

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Authors: K. Shimola, M. Krishnaveni

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This paper examines vulnerability assessment of water resources in a semi-arid basin using the 4-step approach. The vulnerability assessment framework is developed to study the water resources vulnerability which includes the creation of GIS-based vulnerability maps. These maps represent the spatial variability of the vulnerability index. This paper introduces the 4-step approach to assess vulnerability that incorporates a new set of indicators. The approach is demonstrated using a framework composed of a precipitation data for (1975–2010) period, temperature data for (1965–2010) period, hydrological model outputs and the water resources GIS data base. The vulnerability assessment is a function of three components such as exposure, sensitivity and adaptive capacity. The current water resources vulnerability is assessed using GIS based spatio-temporal information. Rainfall Coefficient of Variation, monsoon onset and end date, rainy days, seasonality indices, temperature are selected for the criterion ‘exposure’. Water yield, ground water recharge, evapotranspiration (ET) are selected for the criterion ‘sensitivity’. Type of irrigation and storage structures are selected for the criterion ‘Adaptive capacity’. These indicators were mapped and integrated in GIS environment using overlay analysis. The five sub-basins, namely Arjunanadhi, Kousiganadhi, Sindapalli-Uppodai and Vallampatti Odai, fall under medium vulnerability profile, which indicates that the basin is under moderate stress of water resources. The paper also explores prioritization of sub-basinwise adaptation strategies to climate change based on the vulnerability indices.

Keywords: adaptive capacity, exposure, overlay analysis, sensitivity, vulnerability

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Authors: A. Eštoková, M. Kovalčíková, A. Luptáková, A. Sičáková, M. Ondová

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Concrete durability as an important engineering property of concrete, determining the service life of concrete structures very significantly, can be threatened and even lost due to the interactions of concrete with external environment. Bio-corrosion process caused by presence and activities of microorganisms producing sulphuric acid is a special type of sulphate deterioration of concrete materials. The effects of sulphur-oxidizing bacteria Acidithiobacillus thiooxidans on various concrete samples, based on silica fume and zeolite, were investigated in laboratory during 180 days. A laboratory study was conducted to compare the performance of concrete samples in terms of the concrete deterioration influenced by the leaching of calcium and silicon compounds from the cement matrix. The changes in the elemental concentrations of calcium and silicon in both solid samples and liquid leachates were measured by using X – ray fluorescence method. Experimental studies confirmed the silica fume based concrete samples were found out to have the best performance in terms of both silicon and calcium ions leaching.

Keywords: biocorrosion, concrete, leaching, bacteria

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Authors: Aw Adi Arryansyah

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Using electronic stethoscope for detecting heartbeat sound, and breath sounds, are the effective way to investigate cardiovascular diseases. On the other side, technology is growing towards mobile. Almost everyone has a smartphone. Smartphone has many platforms. Creating mobile applications also became easier. We also can use HTML5 technology to creating mobile apps. Android is the most widely used type. This is the reason for us to make a wireless electronic stethoscope based on Android mobile. Android based Wireless Electronic Stethoscope designed by a simple system, uses sound sensors mounted membrane, then connected with Bluetooth module which will send the heart auscultation voice input data by Bluetooth signal to an android platform. On the software side, android will read the voice input then it will translate to beautiful visualization and release the voice output which can be regulated about how much of it is going to be released. We can change the heart beat sound into BPM data, and heart beat analysis, like normal beat, bradycardia or tachycardia.

Keywords: wireless, HTML 5, auscultation, bradycardia, tachycardia

Procedia PDF Downloads 343

Authors: Nelson Kimeli Kemboi Yego, Juma Kasozi, Joseph Nkruzinza, Francis Kipkogei

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The study investigated the low uptake of health insurance in Kenya despite efforts to achieve universal health coverage through various health insurance schemes. Unsupervised machine learning techniques were employed to identify patterns in health insurance uptake based on sociodemographic factors among Kenyan households. The aim was to identify key demographic groups that are underinsured and to provide insights for the development of effective policies and outreach programs. Using the 2021 FinAccess Survey, the study clustered Kenyan households based on their health insurance uptake and sociodemographic features to reveal patterns in health insurance uptake across the country. The effectiveness of k-prototypes clustering, hierarchical clustering, and agglomerative hierarchical clustering in clustering based on sociodemographic factors was compared. The k-prototypes approach was found to be the most effective at uncovering distinct and well-separated clusters in the Kenyan sociodemographic data related to health insurance uptake based on silhouette, Calinski-Harabasz, Davies-Bouldin, and Rand indices. Hence, it was utilized in uncovering the patterns in uptake. The results of the analysis indicate that inclusivity in health insurance is greatly related to affordability. The findings suggest that targeted policy interventions and outreach programs are necessary to increase health insurance uptake in Kenya, with the ultimate goal of achieving universal health coverage. The study provides important insights for policymakers and stakeholders in the health insurance sector to address the low uptake of health insurance and to ensure that healthcare services are accessible and affordable to all Kenyans, regardless of their socio-demographic status. The study highlights the potential of unsupervised machine learning techniques to provide insights into complex health policy issues and improve decision-making in the health sector.

Keywords: health insurance, unsupervised learning, clustering algorithms, machine learning

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Authors: Nouf Aljohani

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The research project described in this presentation focuses on designing and evaluating oral tasks related to students’ needs and levels to foster communication and negotiation of meaning for a group of female Saudi university students. The significance of the current research project lies in its contribution to determining the usefulness of synchronous technology-mediated interactive group discussion in improving different speaking strategies through using synchronous technology. Also, it discovers how to optimize learning outcomes, expand evaluation for online learning tasks and engaging students’ experience in evaluating synchronous interactive tools and tasks. The researcher used SpeakApps, a synchronous technology, that allows the students to practice oral interaction outside the classroom. Such a course of action was considered necessary due to low English proficiency among Saudi students. According to the author's knowledge, the main factor that causes poor speaking skills is that students do not have sufficient time to communicate outside English language classes. Further, speaking and listening course contents are not well designed to match the Saudi learning context. The methodology included designing speaking tasks to match the educational setting; a CALL framework for designing and evaluating tasks; participant involvement in evaluating these tasks in each online session; and an investigation of the factors that led to the successful implementation of Task-based Language Teaching (TBLT) and using SpeakApps. The analysis and data were drawn from the technology acceptance model surveys, a group interview, teachers’ and students’ weekly reflections, and discourse analysis of students’ interactions.

Keywords: CALL evaluation, synchronous technology, speaking skill, task-based language teaching

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Authors: Ishani D. Goonasekara, Erio Camporesi, Timur Bulgakov, Rungtiwa Phookamsak, Kevin D. Hyde

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Phaeosphaeriaceae comprises a large number of species occurring mainly on grasses and cereal crops as endophytes, saprobes and especially pathogens. Parastagonospora is an important genus in Phaeosphaeriaceae that includes pathogens causing leaf and glume blotch on cereal crops. Currently, there are fifteen Parastagonospora species described, including both pathogens and saprobes. In this study, one sexual morph species and an asexual morph species, occurring as saprobes on members of Poaceae are introduced based on morphology and a combined molecular analysis of the LSU, SSU, ITS, and RPB2 gene sequence data. The sexual morph species Parastagonospora elymi was isolated from a Russian sample of Elymus repens, a grass commonly known as couch grass, and important for grazing animals, as a weed and used in traditional Austrian medicine. P. elymi is similar to the sexual morph of P. avenae in having cylindrical asci, bearing 8, overlapping biseriate, fusiform ascospores but can be distinguished by its subglobose to conical shaped, wider ascomata. In addition, no sheath was observed surrounding the ascospores. The asexual morph species was isolated from a specimen from Italy, on Dactylis glomerata, a commonly found grass distributed in temperate regions. It is introduced as Parastagonospora macrouniseptata, a coelomycete, and bears a close resemblance to P. allouniseptata and P. uniseptata in having globose to subglobose, pycnidial conidiomata and hyaline, cylindrical, 1-septate conidia. However, the new species could be distinguished in having much larger conidiomata. In the phylogenetic analysis which consisted of a maximum likelihood and Bayesian analysis P. elymi showed low bootstrap support, but well segregated from other strains within the Parastagonospora clade. P. neoallouniseptata formed a sister clade with P. allouniseptata with high statistical support.

Keywords: dothideomycetes, multi-gene analysis, Poaceae, saprobes, taxonomy

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Authors: Mi Ok Kang

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This study examined the influences of including LGBTQ-related content in a multicultural teacher education course on the development of prospective teachers’ social justice identities. Appling a content analysis to 53 reflection texts written by participating prospective teachers in response to the relevant course content, this study deduced the stages of social justice identity development (naïve, acceptance, resistance, redefinition, and internalization) that participants reached during the course. The analysis demonstrated that the participants reached various stages in the social identity development model and none of the participants remained at the naïve stage during/after class. The majority (53%) of the participants reached the internalization stage during the coursework and became conscious about the heterosexual privileges they have had and aware of possible impacts of such privilege on their future LGBTQ students. Also the participants had begun to develop pedagogic action plans and devised applicable teaching strategies for their future students based on the new understanding of heteronormativity. We expect this study will benefit teacher educators and educational administrators who want to address LGBTQ-related issues in their multicultural education programs and/or revisit the goals, directions, and implications of their approach.

Keywords: LGBTQ, heteronormativity, social justice identity, teacher education, multicultural education, content analysis

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Authors: R. Daïra, V. Chalvidan

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We present the speckle interferometry method to determine the deformation of a piece. This method of holographic imaging using a CCD camera for simultaneous digital recording of two states object and reference. The reconstruction is obtained numerically. This latest method has the advantage of being simpler than the methods currently available, and it does not suffer the holographic configuration faults online. Furthermore, it is entirely digital and avoids heavy analysis after recording the hologram. This work was carried out in the laboratory HOLO 3 (optical metrology laboratory in Saint Louis, France) and it consists in controlling qualitatively and quantitatively the deformation of object by using a camera CCD connected to a computer equipped with software of Fringe Analysis.

Keywords: speckle, nondestructive testing, interferometry, image processing

Procedia PDF Downloads 493

Authors: Ilan Tamir

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Fans’ chants in sports stadium have, over the years, become an integral part of the spectator experience. While chants add color, atmosphere, and a demonstration of fans’ support for their team, chants also play a significant role in defining fans’ perceptions of their team’s identity and its differentiation from other teams. An analysis of football chants may therefore shed light on fans’ deep-seated worldviews of their own role, their team, the sport in general, and even life itself. This study, based on an analysis of Israeli football chants over years, identifies key changing and stable perceptions of football fans. Overall 94 chants collected, over a period of five decades. After a pilot study, the chants organized in two groups (one covering 1970-1999 and the other 2000-2016). The chants analyzed through qualitative content analysis in order to understand fans values as a reflection of the society. Findings point to several values that have remained stable over years, including fans’ attitudes toward their team and its rivals, and their attitude toward God. On the other hand, recently emerging phenomena such as radicalization of hatred toward the commercialization of sport reflect social and cultural changes, both in and outside the world of sport.

Keywords: sport, fans, chants, soccer

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Authors: Jaisoon Baek, Gyuhwan Oh

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In this study, we developed a puzzle game based on coding and a web-based management system to observe the user's learning status in real time and maximize the understanding of the coding of elementary students. We have improved upon and existing coding game which cannot be connected to textual language coding or comprehends learning state. We analyzed the syntax of various coding languages for the curriculum and provided a menu to convert icon into textual coding languages. In addition, the management system includes multiple types of tutoring, real-time analysis of user play data and feedback. Following its application in regular elementary school software classes, students reported positive effects on understanding and interest in coding were shown by students. It is expected that this will contribute to quality improvement in software education by providing contents with proven educational value by breaking away from simple learning-oriented coding games.

Keywords: coding education, serious game, coding, education management system

Procedia PDF Downloads 136