Search results for: feature expanding.

Authors: Sonia Wahengbam, Natasha Elangbam

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Female impersonation has existed through the length of human civilization and the breadth of its cultures. Transvestism and drag queen cultures have created multi-sited spaces where in the shadow of art, one can cross the gender barrier and express one’s hidden identity. This paper will explore a dynamic cultural space that exists in Manipur, a state in the northeastern region of India, where the female impersonators (nupi shabis) of a folk theater (Shumang Leela) are using this traditional and popular art form to claim social acceptance of their homosexual identities through the medium of entertainment. It will highlight how by crossing the gender boundary, this third gender group has carved out a unique socio-economic niche where they have exploited their sexual identities to their advantage. The paper will trace the expanding cultural ‘’borderland’’ of Manipur where there is an increasing sense of ‘becoming’, belonging and sharing” of identities through the interweaving of old and new media. The research will be based on interviews with the nupi shabis, cultural critics and other experts.

Keywords: transvestism, Manipur, female impersonators (nupi shabis), Shumang Leela, gender

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Authors: Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Diego Santibañez Oyarce, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Streptococcus pyogenes is a gram-positive bacteria involved in a wide range of diseases and is a major-human-specific bacterial pathogen. In Chile, this year the 'Ministerio de Salud' declared an alert due to the increase in strains throughout the year. This increase can be attributed to the multitude of factors including antimicrobial resistance (AMR) and Virulence Factors (VF). Understanding these VF and AMR is crucial for developing effective strategies and improving public health responses. Moreover, experimental identification and characterization of these pathogenic mechanisms are labor-intensive and time-consuming. Therefore, new computational methods are required to provide robust techniques for accelerating this identification. Advances in Machine Learning (ML) algorithms represent the opportunity to refine and accelerate the discovery of VF associated with Streptococcus pyogenes. In this work, we evaluate the accuracy of various machine learning models in predicting the virulence factors and antimicrobial resistance of Streptococcus pyogenes, with the objective of providing new methods for identifying the pathogenic mechanisms of this organism.Our comprehensive approach involved the download of 32,798 genbank files of S. pyogenes from NCBI dataset, coupled with the incorporation of data from Virulence Factor Database (VFDB) and Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. These datasets provided labeled examples of both virulent and non-virulent genes, enabling a robust foundation for feature extraction and model training. We employed preprocessing, characterization and feature extraction techniques on primary nucleotide/amino acid sequences and selected the optimal more for model training. The feature set was constructed using sequence-based descriptors (e.g., k-mers and One-hot encoding), and functional annotations based on database prediction. The ML models compared are logistic regression, decision trees, support vector machines, neural networks among others. The results of this work show some differences in accuracy between the algorithms, these differences allow us to identify different aspects that represent unique opportunities for a more precise and efficient characterization and identification of VF and AMR. This comparative analysis underscores the value of integrating machine learning techniques in predicting S. pyogenes virulence and AMR, offering potential pathways for more effective diagnostic and therapeutic strategies. Future work will focus on incorporating additional omics data, such as transcriptomics, and exploring advanced deep learning models to further enhance predictive capabilities.

Keywords: antibiotic resistance, streptococcus pyogenes, virulence factors., machine learning

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Authors: Fawzia Mohammed Idris

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Zakat is an Islamic procedure for wealth distribution as a social protection mechanism for needy people. This study aimed to assess the possibility to expand the share of fund for national health insurance fund from zakat funds allocated for poor people by measuring the reduction of poverty that result from the investing on direct payment to the needy or by covering them in social health insurance. This study used stata regression as a statistical analysis tool and the finding clarified that there is no significant relationship between the poverty rate as the main indicator and, the number of poor people covered by national health insurance on one hand and the number of benefits poor people from the distribution of zakat fund. This study experienced many difficulties regarding the quality and the consistency of the data. The study suggested that a joint mission between national health insurance fund and zakat chamber to conduct study to assess the efficient use of zakat fund allocated to poor people.

Keywords: health finance, poverty, social health insurance, zakat

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Authors: Joseph Levodo, Ndimbarafine Young Tobin, E. Messina, P. Edouma

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Energy efficiency can contribute significantly towards increasing clean energy access to modern energy services. Many developing countries have largely focused on expanding energy access by increasing supply. This is due to the fact the links between energy efficiency and clean energy access are often unnoticed. Energy efficiency measures offer the promise of reducing energy use and saving money on electricity bills, as well as reducing negative environmental externalities associated with the production of electricity. This paper seeks to address the economic and effectiveness of reducing energy consumption by integrating energy efficiency as a priority to meet energy access examines the barriers to energy efficient in sub-Saharan African countries. The findings from this study reveal that an appropriate policy can promote the development of more energy-efficient buildings, products and strengthen incentives for consumers, businesses, and industrial customers to pursue cost-effective energy-efficiency measures and to make investments that will provide future energy-efficiency improvements.

Keywords: barriers, Sub-Saharan Africa, cost effective, energy savings, clean energy

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Authors: Douglas W. Scott

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The Allemande from J. S. Bach's Partita for solo flute (BWV 1013) presents many unique challenges for any flautist, especially in terms of segmentation analysis required to select breathing places in the first half. Without claiming to identify a 'correct' solution to this problem, this paper analyzes the section in terms of a set of techniques based around a statistical property commonly (if not ubiquitously) found in music, namely Zipf’s law. Specifically, the paper considers violations of this expected profile at various levels of analysis, an approach which has yielded interesting insights in previous studies. The investigation is then grounded by considering four actual solutions to the problem found in recordings made by different flautists, which opens up the possibility of expanding Zipfian analysis to include a consideration of inter-onset-intervals (IOIs). It is found that significant deviations from the expected Zipfian distributions can reveal and highlight stylistic choices made by different performers.

Keywords: inter-onset-interval, Partita for solo flute, BWV 1013, segmentation analysis, Zipf’s law

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Authors: Tomas Vampola, Michael Valášek

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On the basis of simulation-generated failure states of structural elements of a turboprop engine suitable for the busy-jet class of aircraft, an algorithm for early prediction of damage or reduction in functionality of structural elements of the engine is designed and verified with real data obtained at dynamometric testing facilities of aircraft engines. Based on an expanding database of experimentally determined data from temperature and pressure sensors during the operation of turboprop engines, this strategy is constantly modified with the aim of using the minimum number of sensors to detect an inadmissible or deteriorated operating mode of specific structural elements of an aircraft engine. The assembled algorithm for the early prediction of reduced functionality of the aircraft engine significantly contributes to the safety of air traffic and to a large extent, contributes to the economy of operation with positive effects on the reduction of the energy demand of operation and the elimination of adverse effects on the environment.

Keywords: detectability of malfunction, dynamometric testing, prediction of damage, turboprop engine

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Authors: Rutuja Rajendra Ghadage

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Villages surrounding the city undergo the process of peri urbanization, which transforms their original village character. These villages undergo fast and unplanned physical growth and development. Due to the expansion of urban activities, peri-urban villages are experiencing extensive changes. Focusing on the peri-urban villages of Baramati city in Maharashtra, India, this paper assesses the nature and extent of spatial development and identifies the factors contributing to the rapid development of eleven sample Peri-urban villages. After reviewing similar studies, four indicators are selected to assess the spatial development of peri-urban villages; 1) population, 2) road network, 3) land use landcover change, and 4) built-up distribution. The spatial development of peri-urban villages of Baramati is uneven as few villages are still expanding or growing while few villages have started intensifying. The main factor for this development is the presence of industries and educational institutions. They have affected spatial development directly as well as indirectly. In the future, most of the peri-urban villages of Baramati will be in the intensification phase, so if this happens in an unplanned manner, it will create stress on services and facilities.

Keywords: factors and indicators of spatial development, peri urban villages, peri urbanization, spatial development

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Authors: Yahaya Sulaiman, Ibrahim Muhammad Yakuba, Abubakar Usman

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In this paper, we discuss that Sustainable Development Goals are in consonance with Islamic ethos and philosophy. Islam made emphasize on human well-being from spiritual, physiological, intellectual and economic perspectives. Islamic worldview and values framework strengthens moral consciousness, urge pro-social behaviour and engender environmental ethics which can help in influencing our attitudes towards meeting sustainable development challenges. Islamic social finance institutions like Zakat and Waqf can contribute towards scaling up efforts in commercially non-viable, but socially vital projects and programs. There is much potential for Islamic finance to promote sustainable economic development through such approaches as widening access to finance, financing infrastructure projects, and expanding the reach of Takaful. Real sector based productive enterprise in Islamic finance has positive implications for the ecosystem. Risk-sharing shifts the emphasis from credit-worthiness of the borrower to be placed on the value creation and economic viability of investments that create new wealth. Islamic social finance package can cater to the financially excluded households.

Keywords: assessment, Islamic, economic, sustainable, development

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Authors: Miranda E. Karban

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A distinctive pattern of occipital squama convexity, known as the occipital bun or chignon, has traditionally been considered a derived Neandertal trait. However, some early modern and extant Homo sapiens share similar occipital bone morphology, showing pronounced internal and external occipital squama curvature and paralambdoidal flattening. It has been posited that these morphological patterns are homologous in the two groups, but this claim remains disputed. Many developmental hypotheses have been proposed, including assertions that the chignon represents a developmental response to a long and narrow cranial vault, a narrow or flexed basicranium, or a prognathic face. These claims, however, remain to be metrically quantified in a large subadult sample, and little is known about the feature’s developmental, functional, or evolutionary significance. This study assesses patterns of chignon development and covariation in a comparative sample of extant human growth study cephalograms. Cephalograms from a total of 549 European-derived North American subjects (286 male, 263 female) were scored on a 5-stage ranking system of chignon prominence. Occipital squama shape was found to exist along a continuum, with 34 subjects (6.19%) possessing defined chignons, and 54 subjects (9.84%) possessing very little occipital squama convexity. From this larger sample, those subjects represented by a complete radiographic series were selected for metric analysis. Measurements were collected from lateral and posteroanterior (PA) cephalograms of 26 subjects (16 male, 10 female), each represented at 3 longitudinal age groups. Age group 1 (range: 3.0-6.0 years) includes subjects during a period of rapid brain growth. Age group 2 (range: 8.0-9.5 years) includes subjects during a stage in which brain growth has largely ceased, but cranial and facial development continues. Age group 3 (range: 15.9-20.4 years) includes subjects at their adult stage. A total of 16 landmarks and 153 sliding semi-landmarks were digitized at each age point, and geometric morphometric analyses, including relative warps analysis and two-block partial least squares analysis, were conducted to study covariation patterns between midsagittal occipital bone shape and other aspects of craniofacial morphology. A convex occipital squama was found to covary significantly with a low, elongated neurocranial vault, and this pattern was found to exist from the youngest age group. Other tested patterns of covariation, including cranial and basicranial breadth, basicranial angle, midcoronal cranial vault shape, and facial prognathism, were not found to be significant at any age group. These results suggest that the chignon, at least in this sample, should not be considered an independent feature, but rather the result of developmental interactions relating to neurocranial elongation. While more work must be done to quantify chignon morphology in fossil subadults, this study finds no evidence to disprove the developmental homology of the feature in modern humans and Neandertals.

Keywords: chignon, craniofacial covariation, human cranial development, longitudinal growth study, occipital bun

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Authors: Zelalem Fantahun

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Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.

Keywords: POS tagging, Amharic, unsupervised learning, k-means

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Authors: Michal Krecichwost, Zauzanna Miodonska, Pawel Badura

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The diagnosis of sigmatism is mostly based on the observation of articulatory organs. It is, however, not always possible to precisely observe the vocal apparatus, in particular in the oral cavity of the patient. Speech processing can allow to objectify the therapy and simplify the verification of its progress. In the described study the methodology for classification of incorrectly pronounced phoneme [s] is proposed. The recordings come from adults. They were registered with the speech recorder at the sampling rate of 44.1 kHz and the resolution of 16 bit. The database of pathological and normative speech has been collected for the study including reference assessments provided by the speech therapy experts. Ten adult subjects were asked to simulate a certain type of stigmatism under the speech therapy expert supervision. In the recordings, the analyzed phone [s] was surrounded by vowels, viz: ASA, ESE, ISI, SPA, USU, YSY. Thirteen MFCC (mel-frequency cepstral coefficients) and RMS (root mean square) values are calculated within each frame being a part of the analyzed phoneme. Additionally, 3 fricative formants along with corresponding amplitudes are determined for the entire segment. In order to aggregate the information within the segment, the average value of each MFCC coefficient is calculated. All features of other types are aggregated by means of their 75th percentile. The proposed method of features aggregation reduces the size of the feature vector used in the classification. Binary SVM (support vector machine) classifier is employed at the phoneme recognition stage. The first group consists of pathological phones, while the other of the normative ones. The proposed feature vector yields classification sensitivity and specificity measures above 90% level in case of individual logo phones. The employment of a fricative formants-based information improves the sole-MFCC classification results average of 5 percentage points. The study shows that the employment of specific parameters for the selected phones improves the efficiency of pathology detection referred to the traditional methods of speech signal parameterization.

Keywords: computer-aided pronunciation evaluation, sibilants, sigmatism diagnosis, speech processing

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Authors: Aditi Viswanathan, Shree Ranjani, Aruna Govada

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With data sizes constantly expanding, and with classical machine learning algorithms that analyze such data requiring larger and larger amounts of computation time and storage space, the need to distribute computation and memory requirements among several computers has become apparent. Although substantial work has been done in developing distributed binary SVM algorithms and multi-class SVM algorithms individually, the field of multi-class distributed SVMs remains largely unexplored. This research seeks to develop an algorithm that implements the Support Vector Machine over a multi-class data set and is efficient in a distributed environment. For this, we recursively choose the best binary split of a set of classes using a greedy technique. Much like the divide and conquer approach. Our algorithm has shown better computation time during the testing phase than the traditional sequential SVM methods (One vs. One, One vs. Rest) and out-performs them as the size of the data set grows. This approach also classifies the data with higher accuracy than the traditional multi-class algorithms.

Keywords: distributed algorithm, MapReduce, multi-class, support vector machine

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Authors: Abigail Qian Zhou

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In recent years, the prosperity of mass tourism in China has accelerated the breadth and depth of direct communication between countries, and the national image has been placed in a new communication context. Outbound tourists are not only directly involved in the formation of the national image, but are also the most direct medium and the most active symbol representing the national image. This study uses Chinese middle-class tourists visiting Japan as a case study, and analyzes, through participant observation and semi-structured interviews, the communication function of the national image transmitted by 'human medium' in tourism activities. It also explores the 'human medium' in the era of mass tourism. This study hopes to build a bridge for tourism research and national image and media studies. It will provide a theoretical basis and practical guidance for promoting the national image, strengthening exchanges between tourists and local populations, and expanding the tourism market in the future.

Keywords: human medium, national image, communication, Chinese middle class, outbound tourists

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Authors: I. O. Oladipo, Olusegun Adewale Ajayi, Omoniyi Oladipupo Adigun

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Information Communication Technology (ICT) have the potential to contribute to different facets of educational development and effective learning; expanding access, promoting efficiency, improve the quality of learning, enhancing the quality of teaching and provide important mechanism for the economic crisis. Considering the prevalence of unemployment among the higher institution graduates in this nation, in which much seems not to have been achieved in this direction. In view of this, the purpose of this study is to create an awareness and enlightenment of ICT for empowerment opportunities after school. A self-developed modified 4-likert scale questionnaire was used for data collection among Colleges of Education, Physical and Health Education students in Oyo State. Inferential statistical analysis of chi-square set at 0.05 alpha levels was used to analyze the stated hypotheses. The study concludes that awareness and enlightenment of ICT significantly influence empowerment opportunities and recommended that college of education students should be encouraged on the application of ICT for job opportunity after school.

Keywords: employment, empowerment, information communication technology, physical education

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Authors: Richard, Iyan Subiyanto, Chairul Hudaya

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Activated carbon has been playing a significant role for many applications, especially in energy storage devices. However, commercially activated carbons generally require complicated processes and high production costs. Therefore, in this study, an activated carbon originating from green coke waste, that is economically affordable will be used as a carbon source. To synthesize activated carbon, KOH as an activator was employed with variation of C:KOH in ratio of 1:2, 1:3, 1:4, and 1:5, respectively, with an activation temperature of 700°C. The characterizations of activated carbon are obtained from Scanning Electron Microscopy, Energy Dispersive X-Ray, Raman Spectroscopy, and Brunauer-Emmett-Teller. The optimal activated carbon sample with specific surface area of 2,024 m²/g with high carbon content ( > 80%) supported by the high porosity carbon image obtained by SEM was prepared at C:KOH ratio of 1:4. The result shows that the synthesized activated carbon would be an ideal choice for energy storage device applications. Therefore, this study is expected to reduce the costs of activated carbon production by expanding the utilization of petroleum waste.

Keywords: activated carbon, energy storage material, green coke, specific surface area

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Authors: Maria Christofi, George Plastiras, Rafaella Elia, Vaggelis Tsiourtis, Theocharis Theocharides, Miltiadis Katsaros

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The rapidly expanding urban areas of the world constitute a challenge of how we need to make the transition to "the next urbanization", which will be defined by new analytical tools and new sources of data. This paper is about the production of a spatial application, the ‘FUMapp’, where space and its initiative will be available literally, in meters, but also abstractly, at a sensed level. While existing spatial applications typically focus on illustrations of the urban infrastructure, the suggested application goes beyond the existing: It investigates how our environment's perception adapts to the alterations of the built environment through a dataset construction of biophysical measurements (eye-tracking, heart beating), and physical metrics (spatial characteristics, size of stimuli, rhythm of mobility). It explores the intersections between architecture, cognition, and computing where future design can be improved and identifies the flexibility and livability of the ‘available space’ of specific examined urban paths.

Keywords: biophysical data, flexibility of urban, livability, next urbanization, spatial application

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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Authors: Fadhl Qutaish

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This paper examines the pharyngealization spread in one of the Yemeni Arabic dialects, namely, Ibbi Arabic (IA). It investigates how pharyngealized sounds spread their acoustic features onto the neighboring vowels and change their default features. This feature has been investigated quietly well in MSA but still has to be deeply studied in the different dialect of Arabic which will bring about a clearer picture of the similarities and the differences among these dialects and help in mapping them based on the way this feature is utilized. Though the studies are numerous, no one of them has illustrated how far in the multi-syllabic word the spread can be and whether it takes a steady or gradient manner. This study tries to fill this gap and give a satisfactory explanation of the pharyngealization spread in Ibbi Dialect. This study is the first step towards a larger investigation of the different dialects of Yemeni Arabic in the future. The data recorded are represented in minimal pairs in which the trigger (pharyngealized or the non-pharyngealized sound) is in the initial or final position of monosyllabic and multisyllabic words. A group of 24 words were divided into four groups and repeated three times by three subjects which will yield 216 tokens that are tested and analyzed. The subjects are three male speakers aged between 28 and 31 with no history of neurological, speaking or hearing problems. All of them are bilingual speakers of Arabic and English and native speakers of Ibbi-Dialect. Recordings were done in a sound-proof room and praat software was used for the analysis and coding of the trajectories of F1 and F2 for the low vowel /a/ to see the effect of pharyngealization on the formant trajectory within the same syllable and in other syllables of the same word by comparing the F1 and F2 formants to the non-pharyngealized environment. The results show that pharyngealization spread is gradient (progressively and regressively). The spread is reflected in the gradual raising of F1 as we move closer towards the trigger and the gradual lowering of F2 as well. The results of the F1 mean values in tri-syllabic words when the trigger is word initially show that there is a raise of 37.9 HZ in the first syllable, 26.8HZ in the second syllable and 14.2HZ in the third syllable. F2 mean values undergo a lowering of 239 HZ in the first syllable, 211.7 HZ in the second syllable and 176.5 in the third syllable. This gradual decrease in the difference of F2 values in the non-pharyngealized and pharyngealized context illustrates that the spread is gradient. A similar result was found when the trigger is word-final which proves that the spread is gradient (progressively and regressively.

Keywords: pharyngealization, Yemeni Arabic, Ibbi dialect, pharyngealization spread

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Authors: Ashley L. Freeman, Jessica D. Watkins

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TeleEmergency Medicine (TeleEM) is an innovative approach leveraging virtual technology to deliver specialized emergency medical care across diverse healthcare settings, including internal acute care and critical access hospitals, remote patient monitoring, and nurse triage escalation, in addition to external emergency departments, skilled nursing facilities, and community health centers. TeleEM represents a significant advancement in the delivery of emergency medical care, providing healthcare professionals the capability to deliver expertise that closely mirrors in-person emergency medicine, exceeding geographical boundaries. Through qualitative research, the extension of timely, high-quality care has proven to address the critical needs of patients in remote and underserved areas. TeleEM’s service design allows for the expansion of existing services and the establishment of new ones in diverse geographic locations. This ensures that healthcare institutions can readily scale and adapt services to evolving community requirements by leveraging on-demand (non-scheduled) telemedicine visits through the deployment of multiple video solutions. In terms of financial management, TeleEM currently employs billing suppression and subscription models to enhance accessibility for a wide range of healthcare facilities. Plans are in motion to transition to a billing system routing charges through a third-party vendor, further enhancing financial management flexibility. To address state licensure concerns, a patient location verification process has been integrated through legal counsel and compliance authorities' guidance. The TeleEM workflow is designed to terminate if the patient is not physically located within licensed regions at the time of the virtual connection, alleviating legal uncertainties. A distinctive and pivotal feature of TeleEM is the introduction of the TeleEmergency Medicine Care Team Assistant (TeleCTA) role. TeleCTAs collaborate closely with TeleEM Physicians, leading to enhanced service activation, streamlined coordination, and workflow and data efficiencies. In the last year, more than 800 TeleEM sessions have been conducted, of which 680 were initiated by internal acute care and critical access hospitals, as evidenced by quantitative research. Without this service, many of these cases would have necessitated patient transfers. Barriers to success were examined through thorough medical record review and data analysis, which identified inaccuracies in documentation leading to activation delays, limitations in billing capabilities, and data distortion, as well as the intricacies of managing varying workflows and device setups. TeleEM represents a transformative advancement in emergency medical care that nurtures collaboration and innovation. Not only has advanced the delivery of emergency medicine care virtual technology through focus group participation with key stakeholders, rigorous attention to legal and financial considerations, and the implementation of robust documentation tools and the TeleCTA role, but it’s also set the stage for overcoming geographic limitations. TeleEM assumes a notable position in the field of telemedicine by enhancing patient outcomes and expanding access to emergency medical care while mitigating licensure risks and ensuring compliant billing.

Keywords: emergency medicine, TeleEM, rural healthcare, telemedicine

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Authors: Alam Ali, Ashok Kumar Pathak

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Nowadays, copulas have attracted significant attention for modeling multivariate observations, and the foremost feature of copula functions is that they give us the liberty to study the univariate marginal distributions and their joint behavior separately. The copula parameter apprehends the intrinsic dependence among the marginal variables, and it can be estimated using parametric, semiparametric, or nonparametric techniques. This work aims to compare the coverage rates between an Elliptical and an Archimedean family of copulas via a fully parametric estimation technique.

Keywords: elliptical copula, archimedean copula, estimation, coverage rate

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Authors: Luo Jiaoyang, Yu Hongyang

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In this paper, we explore a method that can be used in the working scene of intelligent industrial robots to confirm the identity information of operators to ensure that the robot executes instructions in a sufficiently safe environment. This approach uses three information modalities, namely visible light, depth, and sound. We explored a variety of fusion modes for the three modalities and finally used the joint feature learning method to improve the performance of the model in the case of noise compared with the single-modal case, making the maximum noise in the experiment. It can also maintain an accuracy rate of more than 90%.

Keywords: multimodal, kinect, machine learning, distance image

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Authors: Sombol Mokhles

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Tackling climate change requires expanding networking opportunities between a diverse range of cities to accelerate climate actions. Existing climate city networks have limitations in actively engaging “ordinary” cities in networking processes between cities, as they encourage a few powerful cities to be followed by the many “ordinary” cities. To reimagine the networking opportunities between cities beyond global cities, this paper incorporates “cosmopolitan comparison” to expand our knowledge of a diverse range of cities using a data-driven approach. Through a cosmopolitan perspective, a framework is presented on how to utilise large data to expand knowledge of cities beyond global cities to reimagine the existing hierarchical networking practices. The contribution of this framework is beyond urban climate governance but inclusive of different fields which strive for a more inclusive and cosmopolitan comparison attentive to the differences across cities.

Keywords: cosmopolitan city comparison, data-driven approach, climate city networking, urban climate governance

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Authors: Naomi Grigoryan, Alexandros Loutsioli Daskalakis, Anna Elisse Uy, Yihe Huang, Aude Laurent (Webanck)

Abstract:

In response to the building and construction sectors accounting for a third of all energy demand and emissions, the European Union has placed new laws and regulations in the construction sector that emphasize material circularity, energy efficiency, biodiversity, and social impact. Existing design tools assess sustainability in early-stage design for products or buildings; however, there is no standardized methodology for measuring the circularity performance of building components. Existing assessment methods for building components focus primarily on carbon footprint but lack the comprehensive analysis required to design for circularity. The research conducted in this paper covers the parameters needed to assess sustainability in the design process of architectural products such as doors, windows, and facades. It maps a framework for a tool that assists designers with real-time sustainability metrics. Considering the life cycle of building components such as façades, windows, and doors involves the life cycle stages applied to product design and many of the methods used in the life cycle analysis of buildings. The current industry standards of sustainability assessment for metal building components follow cradle-to-grave life cycle assessment (LCA), track Global Warming Potential (GWP), and document the parameters used for an Environmental Product Declaration (EPD). Developed by the Ellen Macarthur Foundation, the Material Circularity Indicator (MCI) is a methodology utilizing the data from LCA and EPDs to rate circularity, with a "value between 0 and 1 where higher values indicate a higher circularity+". Expanding on the MCI with additional indicators such as the Water Circularity Index (WCI), the Energy Circularity Index (ECI), the Social Circularity Index (SCI), Life Cycle Economic Value (EV), and calculating biodiversity risk and uncertainty, the assessment methodology of an architectural product's impact can be targeted more specifically based on product requirements, performance, and lifespan. Broadening the scope of LCA calculation for products to incorporate aspects of building design allows product designers to account for the disassembly of architectural components. For example, the Material Circularity Indicator for architectural products such as windows and facades is typically low due to the impact of glass, as 70% of glass ends up in landfills due to damage in the disassembly process. The low MCI can be combatted by expanding beyond cradle-to-grave assessment and focusing the design process on disassembly, recycling, and repurposing with the help of real-time assessment tools. Design for Disassembly and Urban Mining has been integrated within the construction field on small scales as project-based exercises, not addressing the entire supply chain of architectural products. By adopting more comprehensive sustainability metrics and incorporating uncertainty calculations, the sustainability assessment of building components can be more accurately assessed with decarbonization and disassembly in mind, addressing the large-scale commercial markets within construction, some of the most significant contributors to climate change.

Keywords: architectural products, early-stage design, life cycle assessment, material circularity indicator

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Authors: Jyoti Bharti, Navneet Manjhi, M. K.Gupta, Bimi Jain

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A reliable gait features are required to extract the gait sequences from an images. In this paper suggested a simple method for gait identification which is based on moments. Moment values are extracted on different number of frames of gray scale and silhouette images of CASIA database. These moment values are considered as feature values. Fuzzy logic and nearest neighbour classifier are used for classification. Both achieved higher recognition.

Keywords: gait, fuzzy logic, nearest neighbour, recognition rate, moments

Procedia PDF Downloads 758

Authors: I. Khabbazi, R. Ghasemi

Abstract:

This paper presents a combination of both robust nonlinear controller and nonlinear controller for a class of nonlinear 4Y Octorotor UAV using Back-stepping and sliding mode controller. The robustness against internal and external disturbance and decoupling control are the merits of the proposed paper. The proposed controller decouples the Octorotor dynamical system. The controller is then applied to a 4Y Octorotor UAV and its feature will be shown.

Keywords: sliding mode, backstepping, decoupling, octorotor UAV

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Authors: Ming Chian Yew, Ming Kun Yew, Lip Huat Saw, Tan Ching Ng, Rajkumar Durairaj, Jing Han Beh

Abstract:

This paper analyzes the fire protection performance, char formation and heat release characteristics of the thin film intumescent coatings that incorporate waste eggshell (ES) as a nano bio-filler. In this study, the Bunsen burner and the fire propagation (BS 476: Part 6) tests of coatings were measured. Experiments on the samples were also tested to evaluate their fire behavior using a cone calorimeter according to ISO 5660-1 specifications. On exposure, the samples B, C and D had been certified to be Class 0 due to the fire propagation indexes of the samples were less than 12. Samples B and D showed a significant reduction in total heat rate (B=11.6 MJ/m² and D=12.0 MJ/m²) and uniform char structures with the addition of 3.30 wt.% and 2.75 wt.% ES nano bio-filler, respectively. As a result, ES nano bio-filler composition good to slow down the fire expanding and demonstrate better fire protection due to its positive synergistic effect with flame retardant ingredients on physical and chemical reactions in fire protection.

Keywords: cone calorimeter, eggshell, fire protection, heat release rate, intumescent coating

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Authors: B. I. Zhumagaliyev, L. Sh. Balgabayeva, G. S. Nabiyeva, B. A. Tulegenova, P. Oralkhan, B. S. Kalenova, S. S. Akhmetov

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The article describes an approach to build competence in research of Bachelor and Master, which is now an important feature of modern specialist in the field of engineering. Provides an example of methodical teaching methods with the research aspect, is including the formulation of the problem, the method of conducting experiments, analysis of the results. Implementation of methods allows the student to better consolidate their knowledge and skills at the same time to get research. Knowledge on the part of the media requires some training in the subject area and teaching methods.

Keywords: professional competence, model of it-specialties, teaching methods, educational technology, decision making

Procedia PDF Downloads 437

Authors: E. A. Asabina, V. I. Pet'kov, P. A. Mayorov, A. V. Markin, N. N. Smirnova, A. M. Kovalskii, A. A. Usenko

Abstract:

The purpose of this work was to synthesize and investigate phase formation, structure and thermophysical properties of the phosphates M_0.5+xM'_xZr_2–x(PO₄)₃ (M – Cd, Sr, Pb; M' – Mg, Co, Mn). The compounds were synthesized by sol-gel method. The results showed formation of limited solid solutions of NZP/NASICON type. The crystal structures of triple phosphates of the compositions MMg_0.5Zr_1.5(PO₄)₃ were refined by the Rietveld method using XRD data. Heat capacity (8–660 K) of the phosphates Pb_0.5+xMg_xZr_2-x(PO₄)₃ (x = 0, 0.5) was measured, and reversible polymorphic transitions were found at temperatures, close to the room temperature. The results of Rietveld structure refinement showed the polymorphism caused by disordering of lead cations in the cavities of NZP/NASICON structure. Thermal expansion (298−1073 K) of the phosphates MMg_0.5Zr_1.5(PO₄)₃ was studied by XRD method, and the compounds were found to belong to middle and low-expanding materials. Thermal diffusivity (298–573 K) of the ceramic samples of phosphates slightly decreased with temperature increasing. As was demonstrated, the studied phosphates are characterized by the better thermophysical characteristics than widespread fire-resistant materials, such as zirconia and etc.

Keywords: NASICON, NZP, phosphate, structure, synthesis, thermophysical properties

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Authors: Roni Naor-Hofri

Abstract:

This paper shows how self-inflicted pain enabled the expression of love for God among Christian monastic ascetics in medieval central Europe. As scholars have shown, being in a state of pain leads to a change in or destruction of language, an essential feature of the self. The author argues that this transformation allows the self to transcend its boundaries as an object, even if only temporarily and in part. The epistemic achievement of love for God, a non-object, would not otherwise have been possible. To substantiate her argument, the author shows that the self’s transformation into a non-object enables the imitation of God: not solely in the sense of imitatio Christi, of physical and visual representations of God incarnate in the flesh of His son Christ, but also in the sense of the self’s experience of being a non-object, just like God, the target of the self’s love.

Keywords: love for God , pain, philosophy, religion

Procedia PDF Downloads 244