Search results for: normalised weighting approach

Authors: Xi Gu, Guan Heng Yeoh, Victoria Timchenko

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In the current work, a three-dimensional geometry of a 75% stenosed blood vessel is analysed. Large eddy simulation (LES) with the help of a dynamic subgrid scale Smagorinsky model is applied to model the turbulent pulsatile flow. The geometry, the transmural pressure and the properties of the blood and the elastic boundary were based on clinical measurement data. For the flexible wall model, a thin solid region is constructed around the 75% stenosed blood vessel. The deformation of this solid region was modelled as a deforming boundary to reduce the computational cost of the solid model. Fluid-structure interaction is realised via a two-way coupling between the blood flow modelled via LES and the deforming vessel. The information of the flow pressure and the wall motion was exchanged continually during the cycle by an arbitrary lagrangian-eulerian method. The boundary condition of current time step depended on previous solutions. The fluctuation of the velocity in the post-stenotic region was analysed in the study. The axial velocity at normalised position Z=0.5 shows a negative value near the vessel wall. The displacement of the elastic boundary was concerned in this study. In particular, the wall displacement at the systole and the diastole were compared. The negative displacement at the stenosis indicates a collapse at the maximum velocity and the deceleration phase.

Keywords: Large Eddy Simulation, Fluid Structural Interaction, constricted artery, Computational Fluid Dynamics

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Authors: Wang Xingbo

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Computation of determinant in the form |I-X| is primary and fundamental because it can help to compute many other determinants. This article puts forward a time-reducible approach to compute determinant |I-X|. The approach is derived from the Newton’s identity and its time complexity is no more than that to compute the eigenvalues of the square matrix X. Mathematical deductions and numerical example are presented in detail for the approach. By comparison with classical approaches the new approach is proved to be superior to the classical ones and it can naturally reduce the computational time with the improvement of efficiency to compute eigenvalues of the square matrix.

Keywords: algorithm, determinant, computation, eigenvalue, time complexity

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Authors: Adrian Florin Busu

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The communicative approach, or communicative language teaching, used for enhancing communicative skills in students in automatics is a modern teaching approach based on the concept of learning a language through having to communicate real meaning. In the communicative approach, real communication is both the objective of learning and the means through which it takes place. This approach was initiated during the 1970’s and quickly became prominent, as it proposed an alternative to the previous systems-oriented approaches. In other words, instead of focusing on the acquisition of grammar and vocabulary, the communicative approach aims at developing students’ competence to communicate in the target language with an enhanced focus on real-life situations. To put it in an nutshell, CLT considers using the language to be just as important as actually learning the language.

Keywords: communication, approach, objective, learning

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Authors: Manta Nowbuth, Marie Anais Kimberley Therese

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The vulnerability of coastal areas to storm surges stands as a critical global concern. The increasing frequency and intensity of extreme weather events have increased the risks faced by communities living along the coastlines Worldwide. Small Island developing states (SIDS) stands out as being exceptionally vulnerable, coastal regions, ecosystems of human habitation and natural forces, bear witness to the frontlines of climate-induced challenges, and the intensification of storm surges underscores the urgent need for a comprehensive understanding of coastal vulnerability. With limited landmass, low-lying terrains, and resilience on coastal resources, SIDS face an amplified vulnerability to the consequences of storm surges, the delicate balance between human activities and environmental dynamics in these island nations increases the urgency of tailored strategies for assessing and mitigating coastal vulnerability. This research uses an approach to evaluate the vulnerability of coastal communities in Mauritius. The Satellite imagery analysis makes use of sentinel satellite imageries, modified normalised difference water index, classification techniques and the DSAS add on to quantify the extent of shoreline erosion or accumulation, providing a spatial perspective on coastal vulnerability. The coastal Vulnerability Index (CVI) is applied by Gonitz et al Formula, this index considers factors such as coastal slope, sea level rise, mean significant wave height, and tidal range. Weighted assessments identify regions with varying levels of vulnerability, ranging from low to high. The study was carried out in a Village Located in the south of Mauritius, namely Rivière des Galets, with a population of about 500 people over an area of 60,000m². The Village of Rivière des Galets being located in the south, and the southern coast of Mauritius being exposed to the open Indian ocean, is vulnerable to swells, The swells generated by the South east trade winds can lead to large waves and rough sea conditions along the Southern Coastline which has an impact on the coastal activities, including fishing, tourism and coastal Infrastructures, hence, On the one hand, the results highlighted that from a stretch of 123km of coastline the linear rate regression for the 5 –year span varies from-24.1m/yr. to 8.2m/yr., the maximum rate of change in terms of eroded land is -24m/yr. and the maximum rate of accretion is 8.2m/yr. On the other hand, the coastal vulnerability index varies from 9.1 to 45.6 and it was categorised into low, moderate, high and very high risks zones. It has been observed that region which lacks protective barriers and are made of sandy beaches are categorised as high risks zone and hence it is imperative to high risk regions for immediate attention and intervention, as they will most likely be exposed to coastal hazards and impacts from climate change, which demands proactive measures for enhanced resilience and sustainable adaptation strategies.

Keywords: climate change, coastal vulnerability, disaster management, remote sensing, satellite imagery, storm surge

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Authors: M. Kalyuga

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Prepositions have long been considered to be one of the major challenges for second language learners, since they have multiple uses that differ greatly from one language to another. The traditional approach to second language teaching supplies students with a list of uses of a preposition that they have to memorise and no explanation is provided. Contrary to the traditional grammar approach, the cognitive linguistic approach offers an explanation for the use of prepositions and provides strategies to comprehend and learn prepositions that would be otherwise seem obscure. The present paper demonstrates the use of the cognitive approach for the explanation of prepositions through the example of the Russian preposition 'за'. The paper demonstrates how various spatial and non-spatial uses of this preposition are linked together through metaphorical and metonymical mapping. The diversity of expressions with за is explained by the range of spatial scenes this preposition is associated with.

Keywords: language teaching, Russian, preposition 'за', cognitive approach

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Authors: benabbess anja

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This research presents the design and implementation of a real-time course recommendation system for online learning platforms, leveraging user competencies and expertise levels. The system begins by extracting and classifying the complexity levels of courses from Udemy datasets using semantic enrichment techniques and resources such as WordNet and BERT. A predictive model assigns complexity levels to each course, adding columns that represent the course category, sub-category, and complexity level to the existing dataset. Simultaneously, user profiles are constructed through questionnaires capturing their skills, sub-skills, and proficiency levels. The recommendation process involves generating embeddings with BERT, followed by calculating cosine similarity between user profiles and courses. Courses are ranked based on their relevance, with the BERT model delivering the most accurate results. To enable real-time recommendations, Apache Kafka is integrated to track user interactions (clicks, comments, time spent, completed courses, feedback) and update user profiles. The embeddings are regenerated, and similarities with courses are recalculated to reflect users' evolving needs and behaviors, incorporating a progressive weighting of interactions for more personalized suggestions. This approach ensures dynamic and real-time course recommendations tailored to user progress and engagement, providing a more personalized and effective learning experience. This system aims to improve user engagement and optimize learning paths by offering courses that precisely match users' needs and current skill levels.

Keywords: recommendation system, online learning, real-time, user skills, expertise level, personalized recommendations, dynamic suggestions

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Authors: Pedro F. Albuquerque, Pedro V. Gamboa, Miguel A. Silvestre

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The present work describes the implementation of the Enhanced Collaborative Optimization (ECO) multilevel architecture with a gradient-based optimization algorithm with the aim of performing a multidisciplinary design optimization of a generic unmanned aerial vehicle with morphing technologies. The concepts of weighting coefficient and a dynamic compatibility parameter are presented for the ECO architecture. A routine that calculates the aircraft performance for the user defined mission profile and vehicle’s performance requirements has been implemented using low fidelity models for the aerodynamics, stability, propulsion, weight, balance and flight performance. A benchmarking case study for evaluating the advantage of using a variable span wing within the optimization methodology developed is presented.

Keywords: multidisciplinary, multilevel, morphing, enhanced collaborative optimization

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Authors: Eric Mensah

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The effects of rapid urbanisation of tropical sub-Saharan developing cities on local and global climate are of great concern due to the negative impacts of Urban Heat Island (UHI) effects. The importance of urban parks, vegetative cover and forest reserves in these tropical cities have been undervalued with a rapid degradation and loss of these vegetative covers to urban developments which continue to cause an increase in daily mean temperatures and changes to local climatic conditions. Using Landsat data of the same months and period intervals, the spatial variations of land cover changes, temperature, and vegetation were examined to determine how vegetation improves local temperature and the effects of urbanisation on daily mean temperatures over the past 12 years. The remote sensing techniques of maximum likelihood supervised classification, land surface temperature retrieval technique, and normalised differential vegetation index techniques were used to analyse and create the land use land cover (LULC), land surface temperature (LST), and vegetation and non-vegetation cover maps respectively. Results from the study showed an increase in daily mean temperature by 0.80 °C as a result of rapid increase in urban area by 46.13 sq. km and loss of vegetative cover by 46.24 sq. km between 2005 and 2017. The LST map also shows the existence of UHI within the urban areas of Accra, the potential mitigating effects offered by the existence of forest and vegetative cover as demonstrated by the existence of cool islands around the Achimota ecological forest and University of Ghana botanical gardens areas.

Keywords: land surface temperature, climate, remote sensing, urbanisation

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Authors: Mareye Zeleke Mekonen

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The Kafficho language has distinct issues in information retrieval because of its restricted resources and dearth of standardized methods. In this endeavor, with the cooperation and support of linguists and native speakers, we investigate the creation of information retrieval systems specifically designed for the Kafficho language. The Kafficho information retrieval system allows Kafficho speakers to access information easily in an efficient and effective way. Our objective is to conduct an information retrieval experiment using 220 Kafficho text files, including fifteen sample questions. Tokenization, normalization, stop word removal, stemming, and other data pre-processing chores, together with additional tasks like term weighting, were prerequisites for the vector space model to represent each page and a particular query. The three well-known measurement metrics we used for our word were Precision, Recall, and and F-measure, with values of 87%, 28%, and 35%, respectively. This demonstrates how well the Kaffiho information retrieval system performed well while utilizing the vector space paradigm.

Keywords: Kafficho, information retrieval, stemming, vector space

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Authors: Nguyen Tien Thanh, Günter Meon

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Precipitation plays a key role in water cycle, defining the local climatic conditions and in ecosystem. It is also an important input parameter for water resources management and hydrologic models. With spatial continuous data, a certainty of discharge predictions or other environmental factors is unquestionably better than without. This is, however, not always willingly available to acquire for a small basin, especially for coastal region in Vietnam due to a low network of meteorological stations (30 stations) on long coast of 3260 km2. Furthermore, available gridded precipitation datasets are not fine enough when applying to hydrologic models. Under conditions of global warming, an application of spatial interpolation methods is a crucial for the climate change impact studies to obtain the spatial continuous data. In recent research projects, although some methods can perform better than others do, no methods draw the best results for all cases. The objective of this paper therefore, is to investigate different spatial interpolation methods for daily precipitation over a small basin (approximately 400 km2) located in coastal region, Southern Vietnam and find out the most efficient interpolation method on this catchment. The five different interpolation methods consisting of cressman, ordinary kriging, regression kriging, dual kriging and inverse distance weighting have been applied to identify the best method for the area of study on the spatio-temporal scale (daily, 10 km x 10 km). A 30-year precipitation database was created and merged into available gridded datasets. Finally, observed changes in constructed precipitation were performed. The results demonstrate that the method of ordinary kriging interpolation is an effective approach to analyze the daily precipitation. The mixed trends of increasing and decreasing monthly, seasonal and annual precipitation have documented at significant levels.

Keywords: interpolation, precipitation, trend, vietnam

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Authors: Nazia Muhsin, Tofael Ahamed, Ryozo Noguchi, Tomohiro Takigawa

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One of the most challenging issues to achieve sustainable development on food security is land use changes. The crisis of lands for agricultural production mainly arises from the unplanned transformation of agricultural lands to infrastructure development i.e. urbanization and industrialization. Land use without sustainability assessment could have impact on the food security and environmental protections. Bangladesh, as the densely populated country with limited arable lands is now facing challenges to meet sustainable food security. Agricultural lands are using for economic growth by establishing industries. The industries are spreading from urban areas to the suburban areas and using the agricultural lands. To minimize the agricultural land losses for unplanned industrialization, compact economic zones should be find out in a scientific approach. Therefore, the purpose of the study was to find out suitable sites for industrial growth by land suitability analysis (LSA) by using Geographical Information System (GIS) and multi-criteria analysis (MCA). The goal of the study was to emphases both agricultural lands and industries for sustainable development in land use. The study also attempted to analysis the agricultural land use changes in a suburban area by statistical data of agricultural lands and primary data of the existing industries of the study place. The criteria were selected as proximity to major roads, and proximity to local roads, distant to rivers, waterbodies, settlements, flood-flow zones, agricultural lands for the LSA. The spatial dataset for the criteria were collected from the respective departments of Bangladesh. In addition, the elevation spatial dataset were used from the SRTM (Shuttle Radar Topography Mission) data source. The criteria were further analyzed with factors and constraints in ArcGIS®. Expert’s opinion were applied for weighting the criteria according to the analytical hierarchy process (AHP), a multi-criteria technique. The decision rule was set by using ‘weighted overlay’ tool to aggregate the factors and constraints with the weights of the criteria. The LSA found only 5% of land was most suitable for industrial sites and few compact lands for industrial zones. The developed LSA are expected to help policy makers of land use and urban developers to ensure the sustainability of land uses and agricultural production.

Keywords: AHP (analytical hierarchy process), GIS (geographic information system), LSA (land suitability analysis), MCA (multi-criteria analysis)

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Authors: Shailaja Thakur

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Managerial literature abounds with discussions on business strategies, success stories as well as cases of failure, which provide an indication of the parameters that should be considered in gauging the dynamism of an entrepreneur. Neoclassical economics has reduced entrepreneurship to a mere factor of production, driven solely by the profit motive, thus stripping him of all creativity and restricting his decision making to mechanical calculations. His ‘dynamism’ is gauged simply by the amount of profits he earns, marginalizing any discussion on the means that he employs to attain this objective. With theoretical backing, we have developed an Index of Entrepreneurial Dynamism (IED) giving weights to the different moves that the entrepreneur makes during his business journey. Strategies such as changes in product lines, markets and technology are gauged as very important (weighting of 4); while adaptations in terms of technology, raw materials used, upgradations in skill set are given a slightly lesser weight of 3. Use of formal market analysis, diversification in related products are considered moderately important (weight of 2) and being a first generation entrepreneur, employing managers and having plans to diversify are taken to be only slightly important business strategies (weight of 1). The maximum that an entrepreneur can score on this index is 53. A semi-structured questionnaire is employed to solicit the responses from the entrepreneurs on the various strategies that have been employed by them during the course of their business. Binary as well as graded responses are obtained, weighted and summed up to give the IED. This index was tested on about 150 tribal entrepreneurs in Mizoram, a state of India and was found to be highly effective in gauging their dynamism. This index has universal acceptability but is devoid of the socio-cultural context, which is very central to the success and performance of the entrepreneurs. We hypothesize that a society that respects risk taking takes failures in its stride, glorifies entrepreneurial role models, promotes merit and achievement is one that has a conducive socio- cultural environment for entrepreneurship. For obtaining an idea about the social acceptability, we are putting forth questions related to the social acceptability of business to another set of respondents from different walks of life- bureaucracy, academia, and other professional fields. Similar weighting technique is employed, and index is generated. This index is used for discounting the IED of the respondent entrepreneurs from that region/ society. This methodology is being tested for a sample of entrepreneurs from two very different socio- cultural milieus- a tribal society and a ‘mainstream’ society- with the hypothesis that the entrepreneurs in the tribal milieu might be showing a higher level of dynamism than their counterparts in other regions. An entrepreneur who scores high on IED and belongs to society and culture that holds entrepreneurship in high esteem, might not be in reality as dynamic as a person who shows similar dynamism in a relatively discouraging or even an outright hostile environment.

Keywords: index of entrepreneurial dynamism, India, social acceptability, tribal entrepreneurs

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Authors: Aafaf El Jazouli, Ahmed Barakat, Rida Khellouk

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Mapping of soil degradation is derived from field observations, laboratory measurements, and remote sensing data, integrated quantitative methods to map the spatial characteristics of soil properties at different spatial and temporal scales to provide up-to-date information on the field. Since soil salinity, texture and organic matter play a vital role in assessing topsoil characteristics and soil quality, remote sensing can be considered an effective method for studying these properties. The main objective of this research is to asses soil degradation by combining remote sensing data and laboratory analysis. In order to achieve this goal, the required study of soil samples was taken at 50 locations in the upper basin of Oum Er Rbia in the Middle Atlas in Morocco. These samples were dried, sieved to 2 mm and analyzed in the laboratory. Landsat 8 OLI imagery was analyzed using physical or empirical methods to derive soil properties. In addition, remote sensing can serve as a supporting data source. Deterministic potential (Spline and Inverse Distance weighting) and probabilistic interpolation methods (ordinary kriging and universal kriging) were used to produce maps of each grain size class and soil properties using GIS software. As a result, a correlation was found between soil texture and soil organic matter content. This approach developed in ongoing research will improve the prospects for the use of remote sensing data for mapping soil degradation in arid and semi-arid environments.

Keywords: Soil degradation, GIS, interpolation methods (spline, IDW, kriging), Landsat 8 OLI, Oum Er Rbia high basin

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Authors: Fuad Ali Mohammed Al-Yarimi

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Many algorithms have been proposed to provide privacy preserving in data mining. These protocols are based on two main approaches named as: the perturbation approach and the Cryptographic approach. The first one is based on perturbation of the valuable information while the second one uses cryptographic techniques. The perturbation approach is much more efficient with reduced accuracy while the cryptographic approach can provide solutions with perfect accuracy. However, the cryptographic approach is a much slower method and requires considerable computation and communication overhead. In this paper, a new scalable protocol is proposed which combines the advantages of the perturbation and distortion along with cryptographic approach to perform privacy preserving in distributed frequent itemset mining on horizontally distributed data. Both the privacy and performance characteristics of the proposed protocol are studied empirically.

Keywords: anonymity data, data mining, distributed frequent itemset mining, gaussian perturbation, perturbation approach, privacy preserving data mining

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Authors: Karolina Rutkowska, Hubert Pausch, Jolanta Oprzadek, Krzysztof Flisikowski

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The placenta is one of the most important organs that plays a crucial role in the fetal growth and development. Placenta dysfunction is one of the primary cause of the intrauterine growth restriction (IUGR). Cattle have the cotyledonary placenta which consists of two anatomical parts: fetal and maternal. In the case of cattle during the first months of pregnancy, it is very easy to separate maternal caruncle from fetal cotyledon tissue, easier in fact than removing an ordinary glove from one's hand. Which in fact make easier to conduct tissue-specific molecular studies. Typically, animal models for the study of IUGR are created using surgical methods and malnutrition of the pregnant mother or in the case of mice by genetic modifications. However, proposed cattle model with MIMT1Del/WT deletion is unique because it was created without any surgical methods what significantly distinguish it from the other animal models. The primary objective of the study was to identify differential expression of selected miRNAs in the placenta from normal and intrauterine growth restricted fetuses. There was examined the expression of miRNA in the fetal and maternal part of the placenta from 24 fetuses (12 samples from the fetal part of the placenta and 12 samples from maternal part of the placenta). In the study, there was done miRNAs sequencing in the placenta of MIMT1Del/WT fetuses and MIMT1WT/WT fetuses. Then, there were selected miRNAs that are involved in fetal growth and development. Analysis of miRNAs expression was conducted on ABI7500 machine. miRNAs expression was analyzed by reverse-transcription polymerase chain reaction (RT-PCR). As the reference gene was used SNORD47. The results were expressed as 2ΔΔCt: ΔΔCt = (Ctij − CtSNORD47j) − (Cti1 − CtSNORD471). Where Ctij and CtSNORD47j are the Ct values for gene i and for SNORD47 in a sample (named j); Cti1 and CtSNORD471 are the Ct values in sample 1. Differences between groups were evaluated with analysis of variance by using One-Way ANOVA. Bonferroni’s tests were used for interpretation of the data. All normalised miRNA expression values are expressed on a value of natural logarithm. The data were expressed as least squares mean with standard errors. Significance was declared when P < 0.05. The study shows that miRNAs expression depends on the part of the placenta where they origin (fetal or maternal) and on the genotype of the animal. miRNAs offer a particularly new approach to study IUGR. Corresponding tissue samples were collected according to the standard veterinary protocols according to the European Union Normative for Care and Use of Experimental Animals. All animal experiments were approved by the Animal Ethics Committee of the State Provincial Office of Southern Finland (ESAVI-2010-08583/YM-23).

Keywords: placenta, intrauterine growth restriction, miRNA, cattle

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Authors: Soyon Kim, Edward Kim

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In order to retrieve information from the massive stream of songs in the music industry, music search by title, lyrics, artist, mood, and genre has become more important. Despite the subjectivity and controversy over the definition of music genres across different nations and cultures, automatic genre classification systems that facilitate the process of music categorization have been developed. Manual genre selection by music producers is being provided as statistical data for designing automatic genre classification systems. In this paper, an automatic music genre classification system utilizing non-negative matrix factorization (NMF) is proposed. Short-term characteristics of the music signal can be captured based on the timbre features such as mel-frequency cepstral coefficient (MFCC), decorrelated filter bank (DFB), octave-based spectral contrast (OSC), and octave band sum (OBS). Long-term time-varying characteristics of the music signal can be summarized with (1) the statistical features such as mean, variance, minimum, and maximum of the timbre features and (2) the modulation spectrum features such as spectral flatness measure, spectral crest measure, spectral peak, spectral valley, and spectral contrast of the timbre features. Not only these conventional basic long-term feature vectors, but also NMF based feature vectors are proposed to be used together for genre classification. In the training stage, NMF basis vectors were extracted for each genre class. The NMF features were calculated in the log spectral magnitude domain (NMF-LSM) as well as in the basic feature vector domain (NMF-BFV). For NMF-LSM, an entire full band spectrum was used. However, for NMF-BFV, only low band spectrum was used since high frequency modulation spectrum of the basic feature vectors did not contain important information for genre classification. In the test stage, using the set of pre-trained NMF basis vectors, the genre classification system extracted the NMF weighting values of each genre as the NMF feature vectors. A support vector machine (SVM) was used as a classifier. The GTZAN multi-genre music database was used for training and testing. It is composed of 10 genres and 100 songs for each genre. To increase the reliability of the experiments, 10-fold cross validation was used. For a given input song, an extracted NMF-LSM feature vector was composed of 10 weighting values that corresponded to the classification probabilities for 10 genres. An NMF-BFV feature vector also had a dimensionality of 10. Combined with the basic long-term features such as statistical features and modulation spectrum features, the NMF features provided the increased accuracy with a slight increase in feature dimensionality. The conventional basic features by themselves yielded 84.0% accuracy, but the basic features with NMF-LSM and NMF-BFV provided 85.1% and 84.2% accuracy, respectively. The basic features required dimensionality of 460, but NMF-LSM and NMF-BFV required dimensionalities of 10 and 10, respectively. Combining the basic features, NMF-LSM and NMF-BFV together with the SVM with a radial basis function (RBF) kernel produced the significantly higher classification accuracy of 88.3% with a feature dimensionality of 480.

Keywords: mel-frequency cepstral coefficient (MFCC), music genre classification, non-negative matrix factorization (NMF), support vector machine (SVM)

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Authors: Adriano Pinargote, Josue Mosquera, Eduardo Montero, Dalton Noboa, Jenny Venegas, Genesis Vasquez Escuela

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In the framework of Pre University learning of the Polytechnic School of the Litoral, Guayaquil, Ecuador, the methodology of Active Learning (Flipped Classroom) has been implemented for applicants who wish to obtain a quota within the university. To complement the Active Learning cycle, it has been proposed that the respective students influence the qualification of their work groups, for which a web platform has been created that allows them to evaluate the performance of their peers through a digital coevaluation that measures through statistical methods, the group and individual performance score that can reflect in numbers a weighting score corresponding to the grade of each student. Their feedback provided by the group help to improve the performance of the activities carried out in classes because the note reflects the commitment with their classmates shown in the class, within this analysis we will determine if this implementation directly influences the performance of the grades obtained by the student.

Keywords: active learning, coevaluation, flipped classroom, pre university

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Authors: Beatriz Mella Lira, Karla Yohannessen, Robin Hickman

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The aim of the paper is recognising inequalities through the self-assessment of health-related factors, in the context of daily mobilities in Santiago de Chile. Human capabilities will be used as the theoretical basis for the recognition and assessment of these factors regarding the functioning (what people are currently able to do) and capabilities (what people want to achieve and what is valuable for them), reflecting differences across social groups and among types of transport users. The self-assessment of health-related factors considers perceptions of stress, physical effort, proximity to other transport users, pollution, safety, and comfort. The types of transport users are classified as: private (cars, taxis, colectivos, motos), public (buses and metro) and active (bicycles and walking). The methodology follows a capability-based questionnaire, which was applied in different areas of Santiago de Chile, considering concepts extracted from the human capabilities list. The self-assessment of these health-related factors examines the context of peoples’ mobilities for performing their daily activities, considering socioeconomic differences as income, age, gender, disabilities, residence location and primary mode choice. The paper uses Relative Importance Index (RII) for weighting the relative influence or valuation of the factors. The respondents were asked to rate the importance of each factor on a scale from 1 to 5, in an ascending order of importance. The results suggest that these health-related factors impact not just the perceptions of users, but their well-being and their propensity for achieving their capabilities and the things they value in life. The paper is focused on the development of an applicable approach, measuring factors that should be included in transport project appraisal, as a more comprehensive and complementary method.

Keywords: active transport, health, human capabilities, Santiago de Chile, transport inequalities, transportation planning, urban planning

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Authors: Lanja F. Rauf, Salahalddin S. Ali, Nadhir Al-Ansari

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Evolving groundwater vulnerability from DRASTIC to modified DRASTIC methods helps choose the most accurate areas that are most delicate toward pollution. This study aims to modify DRASTIC with land use and water quality index for groundwater vulnerability assessment in the Halabja-Khurmal sub-basin, NE/Iraq. The Halabja- Khurmal sub-basin groundwater vulnerability index is calculated from nine hydrogeological parameters by the overlay weighting method. As a result, 1.3 % of the total area has a very high vulnerability value and 46.1 % with high vulnerability. The regions with high groundwater vulnerability have a high water table and groundwater recharge. Nitrate concentration was used to validate the result, and the Pearson correlation and recession analysis between the modified DRASTIC index and nitrate concentration depicted a strong relation with 0.76 and 0.7, respectively.

Keywords: groundwater vulnerability, modified DRASTIC, land-use, nitrate pollution, water quality index

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Authors: Dian Hartiningsih, Miranda Diponegoro, Evita Eddie Singgih

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In facing the 21st century, children need to be prepared in reaching their optimum development level which encompasses all aspect of growth and to achieve the learning goals which include not only knowledge and skill, but also disposition and feeling. Teachers as the forefront of education need to be equipped with the understanding and skill of a learning method which can prepare the children to face this 21st century challenge. Project approach is an approach which utilizes active learning which is beneficial for the children. Subject to this research are kindergarten teachers at Dwi Matra Kindergarten and Kirana Preschool. This research is a quantitative research using before and after study design. The result suggest that through preliminary training program on learning with project approach, the kindergarten teachers ability to explain project approach including understanding, benefit and stages of project approach have increased significantly, the teachers ability to design learning with project approach have also improved significantly. The result of learning design that the teachers had made shows a remarkable result for the first stage of the project approach; however the second and third design result was not as optimal. Challenges faced in the research will be elaborated further in the research discussion.

Keywords: project approach, teacher training, learning method, kindergarten

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Authors: Alokananda Ghosh, Shraban Sarkar

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The study aims to identify suitable sites for new hospitals with critical obstetric care facilities in Birbhum, one of the vulnerable and underserved districts of Eastern India, considering six main and 14 sub-criteria, using GIS-based Analytic Hierarchy Process (AHP) and Multi-Attribute Utility Theory (MAUT) approach. The criteria were identified through field surveys and previous literature. After collecting expert decisions, a pairwise comparison matrix was prepared using the Saaty scale to calculate the weights through AHP. On the contrary, objective weighting methods, i.e., Entropy and Criteria Importance through Interaction Correlation (CRITIC), were used to perform the MAUT. Finally, suitability maps were prepared by weighted sum analysis. Sensitivity analyses of AHP were performed to explore the effect of dominant criteria. Results from AHP reveal that ‘maternal death in transit’ followed by ‘accessibility and connectivity’, ‘maternal health care service (MHCS) coverage gap’ were three important criteria with comparatively higher weighted values. Whereas ‘accessibility and connectivity’ and ‘maternal death in transit’ were observed to have more imprint in entropy and CRITIC, respectively. While comparing the predictive suitable classes of these three models with the layer of existing hospitals, except Entropy-MAUT, the other two are pointing towards the left-over underserved areas of existing facilities. Only 43%-67% of existing hospitals were in the moderate to lower suitable class. Therefore, the results of the predictive models might bring valuable input in future planning.

Keywords: hospital site suitability, analytic hierarchy process, multi-attribute utility theory, entropy, criteria importance through interaction correlation, multi-criteria decision analysis

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Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are playing an increasingly important role in automated customer service. These models, which are able to recognize complex relationships between input and output sequences, are crucial for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the focus of the model during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the domain of chatbots using the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Utilizing the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k=3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k=3). These results emphasize the crucial influence of selecting an appropriate attention-scoring function in improving the performance of seq2seq models for chatbots. Particularly, the model that integrates tanh activation proves to be a promising approach to improve the quality of chatbots in the customer support context.

Keywords: attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence

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Authors: H. Majour, L. Djabri

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Many methods in the groundwater vulnerability have been developed in the world (methods like PRAST, DRIST, APRON/ARAA, PRASTCHIM, GOD). In this study, our choice dealt with two recent complementary methods using category mapping of index with weighting criteria (Point County Systems Model MSCP) namely the standard DRASTIC method and SI (Susceptibility Index). At present, these two methods are the most used for the mapping of the intrinsic vulnerability of groundwater. Two classes of groundwater vulnerability in the Biskra sandy aquifer were identified by the DRASTIC method (average and high) and the SI method (very high and high). Integrated analysis has revealed that the high class is predominant for the DRASTIC method whereas for that of SI the preponderance is for the very high class. Furthermore, we notice that the method SI estimates better the vulnerability for the pollution in nitrates, with a rate of 85 % between the concentrations in nitrates of groundwater and the various established classes of vulnerability, against 75 % for the DRASTIC method. By including the land use parameter, the SI method produced more realistic results.

Keywords: DRASTIC, SI, GIS, Biskra sandy aquifer, Algeria

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Authors: Barkaoui Asma

Abstract:

In our article, we use the economic approach of measuring advertising effectiveness to show the margin of advertising spread gained through digital communication. For economists, profit maximization depends on determining the optimal advertising budget. For this, they use the theories of the marginalist current to determine when the maximum level of benefits is reached. Using the economic approach we show the significant return on investment for advertisers. We then discuss the risks of perception of advertising pressure by consumers.

Keywords: digital advertising, economic approach, effectiveness, pressure

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Authors: Nicola Colaninno, Eugenio Morello

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The urban environment affects local-to-global climate and, in turn, suffers global warming phenomena, with worrying impacts on human well-being, health, social and economic activities. Physic-morphological features of the built-up space affect urban air temperature, locally, causing the urban environment to be warmer compared to surrounding rural. This occurrence, typically known as the Urban Heat Island (UHI), is normally assessed by means of air temperature from fixed weather stations and/or traverse observations or based on remotely sensed Land Surface Temperatures (LST). The information provided by ground weather stations is key for assessing local air temperature. However, the spatial coverage is normally limited due to low density and uneven distribution of the stations. Although different interpolation techniques such as Inverse Distance Weighting (IDW), Ordinary Kriging (OK), or Multiple Linear Regression (MLR) are used to estimate air temperature from observed points, such an approach may not effectively reflect the real climatic conditions of an interpolated point. Quantifying local UHI for extensive areas based on weather stations’ observations only is not practicable. Alternatively, the use of thermal remote sensing has been widely investigated based on LST. Data from Landsat, ASTER, or MODIS have been extensively used. Indeed, LST has an indirect but significant influence on air temperatures. However, high-resolution near-surface air temperature (NSAT) is currently difficult to retrieve. Here we have experimented Geographically Weighted Regression (GWR) as an effective approach to enable NSAT estimation by accounting for spatial non-stationarity of the phenomenon. The model combines on-site measurements of air temperature, from fixed weather stations and satellite-derived LST. The approach is structured upon two main steps. First, a GWR model has been set to estimate NSAT at low resolution, by combining air temperature from discrete observations retrieved by weather stations (dependent variable) and the LST from satellite observations (predictor). At this step, MODIS data, from Terra satellite, at 1 kilometer of spatial resolution have been employed. Two time periods are considered according to satellite revisit period, i.e. 10:30 am and 9:30 pm. Afterward, the results have been downscaled at 30 meters of spatial resolution by setting a GWR model between the previously retrieved near-surface air temperature (dependent variable), the multispectral information as provided by the Landsat mission, in particular the albedo, and Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM), both at 30 meters. Albedo and DEM are now the predictors. The area under investigation is the Metropolitan City of Milan, which covers an area of approximately 1,575 km2 and encompasses a population of over 3 million inhabitants. Both models, low- (1 km) and high-resolution (30 meters), have been validated according to a cross-validation that relies on indicators such as R2, Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). All the employed indicators give evidence of highly efficient models. In addition, an alternative network of weather stations, available for the City of Milano only, has been employed for testing the accuracy of the predicted temperatures, giving and RMSE of 0.6 and 0.7 for daytime and night-time, respectively.

Keywords: urban climate, urban heat island, geographically weighted regression, remote sensing

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Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

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We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process.

Keywords: deep-learning approach, object-classes, semantic classification, Arabic

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Authors: Marcelino Caetano Noronha, Vosco Pereira, Jose Soares Pinto, Ferdinando Da C. Saores

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One particularly popular social media platform is Youtube. It’s a video-sharing platform where users can submit videos, and other users can like, dislike or comment on the videos. In this study, we conduct a binary classification task on YouTube’s video comments and review from the users regarding the accession process of Timor Leste to become the eleventh member of the Association of South East Asian Nations (ASEAN). We scrape the data directly from the public YouTube video and apply several pre-processing and weighting techniques. Before conducting the classification, we categorized the data into two classes, namely positive and negative. In the classification part, we apply Support Vector Machine (SVM) algorithm. By comparing with Naïve Bayes Algorithm, the experiment showed SVM achieved 84.1% of Accuracy, 94.5% of Precision, and Recall 73.8% simultaneously.

Keywords: classification, YouTube, sentiment analysis, support sector machine

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Authors: Nadia Ben Youssef, Aicha Bouzid

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Gradient estimation is one of the most fundamental tasks in the field of image processing in general, and more particularly for color images since that the research in color image gradient remains limited. The widely used gradient method is Di Zenzo’s gradient operator, which is based on the measure of squared local contrast of color images. The proposed gradient mechanism, presented in this paper, is based on the principle of the Di Zenzo’s approach using quaternion representation. This edge detector is compared to a marginal approach based on multiscale product of wavelet transform and another vector approach based on quaternion convolution and vector gradient approach. The experimental results indicate that the proposed color gradient operator outperforms marginal approach, however, it is less efficient then the second vector approach.

Keywords: gradient, edge detection, color image, quaternion

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Authors: Eglal Y. Ali, Smita Rao, Anat Lubetzky, Wen Ling

Abstract:

Background: Postural abnormalities, rigidity, clumsiness, and frequent falls are common among children with autism spectrum disorders (ASD). The central nervous system’s ability to process all reliable sensory inputs (weighting) and disregard potentially perturbing sensory input (reweighting) is critical for successfully maintaining standing postural control. This study examined how sensory inputs (visual and somatosensory) are weighted and reweighted to maintain standing postural control in children with ASD compared with typically developing (TD) children. Subjects: Forty (20 (TD) and 20 ASD) children and adolescents participated in this study. The groups were matched for age, weight, and height. Participants had normal somatosensory (no somatosensory hypersensitivity), visual, and vestibular perception. Participants with ASD were categorized with severity level 1 according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) and Social Responsiveness Scale. Methods: Using one force platform, the center of pressure (COP) was measured during quiet standing for 30 seconds, 3 times first standing on stable surface with eyes open (Condition 1), followed by randomization of the following 3 conditions: Condition 2 standing on stable surface with eyes closed, (visual input perturbed); Condition 3 standing on compliant foam surface with eyes open, (somatosensory input perturbed); and Condition 4 standing on compliant foam surface with eyes closed, (both visual and somatosensory inputs perturbed). Standing postural control was measured by three outcome measures: COP sway area, COP anterior-posterior (AP), and mediolateral (ML) path length (PL). A repeated measure mixed model Analysis of Variance was conducted to determine whether there was a significant difference between the two groups in the mean of the three outcome measures across the four conditions. Results: According to all three outcome measures, both groups showed a gradual increase in postural sway from condition 1 to condition 4. However, TD participants showed a larger postural sway than those with ASD. There was a significant main effect of condition on three outcome measures (p< 0.05). Only the COP AP PL showed a significant main effect of the group (p<0.05) and a significant group by condition interaction (p<0.05). In COP AP PL, TD participants showed a significant difference between condition 2 and the baseline (p<0.05), whereas the ASD group did not. This suggests that the ASD group did not weight visual input as much as the TD group. A significant difference between conditions for the ASD group was seen only when participants stood on foam regardless of the visual condition, suggesting that the ASD group relied more on the somatosensory inputs to maintain the standing postural control. Furthermore, the ASD group exhibited significantly smaller postural sway compared with TD participants during standing on the stable surface, whereas the postural sway of the ASD group was close to that of the TD group on foam. Conclusion: These results suggest that participants with high functioning ASD (level 1, no somatosensory hypersensitivity in ankles and feet) over-rely on somatosensory inputs and use a stiffening strategy for standing postural control. This deviation in the reweighting mechanism might explain the postural abnormalities mentioned above among children with ASD.

Keywords: autism spectrum disorders, postural sway, sensory weighting and reweighting, standing postural control

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Authors: Newton Muhury, Armando A. Apan, Tek N. Marasani, Gebiaw T. Ayele

Abstract:

The changing climate has degraded freshwater availability in Australia that influencing vegetation growth to a great extent. This study assessed the vegetation responses to groundwater using Terra’s moderate resolution imaging spectroradiometer (MODIS), Normalised Difference Vegetation Index (NDVI), and soil water content (SWC). A hydrological model, SWAT, has been set up in a southeast Australian river catchment for groundwater analysis. The model was calibrated and validated against monthly streamflow from 2001 to 2006 and 2007 to 2010, respectively. The SWAT simulated soil water content for 43 sub-basins and monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) were applied in the machine learning tool, Waikato Environment for Knowledge Analysis (WEKA), using two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The assessment shows that different types of vegetation response and soil water content vary in the dry and wet seasons. The WEKA model generated high positive relationships (r = 0.76, 0.73, and 0.81) between NDVI values of all vegetation in the sub-basins against soil water content (SWC), the groundwater flow (GW), and the combination of these two variables, respectively, during the dry season. However, these responses were reduced by 36.8% (r = 0.48) and 13.6% (r = 0.63) against GW and SWC, respectively, in the wet season. Although the rainfall pattern is highly variable in the study area, the summer rainfall is very effective for the growth of the grass vegetation type. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

Procedia PDF Downloads 101