Search results for: natural features

Authors: Agim Kukelii, Gevorg Sargsyan

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This study, focusing on the base regional area (county level), estimates the effect of natural disaster damages on aggregate personal income, aggregate wages, wages per worker, aggregate employment, and aggregate income transfer. The study further estimates the dynamics of personal income, employment, and wages under natural disaster shocks. Southeast Texas, located at the center of Golf Coast, is hit by meteorological and hydrological caused natural disasters yearly. On average, there are more than four natural disasters per year that cane an estimated damage average of 2.2% of real personal income. The study uses the panel data method to estimate the average effect of natural disasters on the area’s economy (personal income, wages, employment, and income transfer). It also uses Panel Vector Autoregressive (PVAR) model to study the dynamics of macroeconomic variables under natural disaster shocks. The study finds that the average effect of natural disasters is positive for personal income and income transfer and is negative for wages and employment. The PVAR and the impulse response function estimates reveal that natural disaster shocks cause a decrease in personal income, employment, and wages. However, the economy’s variables bounce back after three years. The novelty of this study rests on several aspects. First, this is the first study to investigate the effects of natural disasters on macroeconomic variables at a regional level. Second, the study uses direct measures of natural disaster damages. Third, the study estimates that the time that the local economy takes to absorb the natural disaster damages shocks is three years. This is a relatively good reaction to the local economy, therefore, adding to the “resiliency” hypothesis. The study has several implications for policymakers, businesses, and households. First, this study serves to increase the awareness of local stakeholders that natural disaster damages do worsen, macroeconomic variables, such as personal income, employment, and wages beyond the immediate damages to residential and commercial properties, physical infrastructure, and discomfort in daily lives. Second, the study estimates that these effects linger on the economy on average for three years, which would require policymakers to factor in the time area need to be on focus.

Keywords: natural disaster damages, macroeconomics effects, PVAR, panel data

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Authors: C. Pacheco, A. Cipriano

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A new concept of response system is proposed for filling the gap that exists in reducing vulnerability during immediate response to natural disasters. Real Time Early Response Systems (RTERSs) incorporate real time information as feedback data for closing control loop and for generating real time situation assessment. A review of the state of the art works that fit the concept of RTERS is presented, and it is found that they are mainly focused on manmade disasters. At the same time, in response phase of natural disaster management many works are involved in creating early warning systems, but just few efforts have been put on deciding what to do once an alarm is activated. In this context a RTERS arises as a useful tool for supporting people in their decision making process during natural disasters after an event is detected, and also as an innovative context for applying well-known automation technologies and automatic control concepts and tools.

Keywords: disaster management, emergency response system, natural disasters, real time

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Authors: Adrian-Gabriel Chifu, Sebastien Fournier

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One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

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Authors: Sreekanth T. G., Kishorekumar S., Sowndhariya Kumar J., Karthick R., Shanmugasuriyan S.

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Composites are increasingly being used in industries due to their unique properties, such as high specific stiffness and specific strength, higher fatigue and wear resistances, and higher damage tolerance capability. Composites are prone to failures or damages that are difficult to identify, locate, and characterize due to their complex design features and complicated loading conditions. The lack of understanding of the damage mechanism of the composites leads to the uncertainties in the structural integrity and durability. Delamination is one of the most critical failure mechanisms in laminated composites because it progressively affects the mechanical performance of fiber-reinforced polymer composite structures over time. The identification and severity characterization of delamination in engineering fields such as the aviation industry is critical for both safety and economic concerns. The presence of delamination alters the vibration properties of composites, such as natural frequencies, mode shapes, and so on. In this study, numerical analysis and experimental analysis were performed on delaminated and non-delaminated glass fiber reinforced polymer (GFRP) plate, and the numerical and experimental analysis results were compared, and error percentage has been found out.

Keywords: composites, delamination, natural frequency, mode shapes

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Authors: Chang Hsueh-Sheng, Chen Tzu-Ling

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Earthquake is an unpredictable natural disaster and intensive earthquakes have caused serious impacts on social-economic system, environmental and social resilience. Conventional ways to mitigate earthquake disaster are to enhance building codes and advance structural engineering measures. However, earthquake-induced ground damage such as liquefaction, land subsidence, landslide happen on places nearby earthquake prone or poor soil condition areas. Therefore, this study uses spatial statistical analysis to explore the spatial pattern of damaged buildings. Afterwards, principle components analysis (PCA) is applied to categorize the similar features in different kinds of clustered patterns. The results show that serious landslide prone area, close to fault, vegetated ground surface and mudslide prone area are common in those highly damaged buildings. In addition, the oldest building might not be directly referred to the most vulnerable one. In fact, it seems that buildings built between 1974 and 1989 become more fragile during the earthquake. The incorporation of both spatial statistical analyses and PCA can provide more accurate information to subsidize retrofit programs to enhance earthquake resistance in particular areas.

Keywords: earthquake disaster, spatial statistic analysis, principle components analysis (pca), clustered patterns

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Authors: Pattaranut Eakwaropas, Khemjira Jarmkom, Warachate Khobjai, Surachai Techaoei

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The aim of this study is to improve Pang-Rum (PR) hardness by adding natural binders. PR is one of Thai tradition aroma products. In the past, it was used for aesthetic propose on face and body with good odor. Nowadays, PR is not popular and going to be disappeared. Five natural materials, i.e. agar, rice flour, glutinous flour, corn starch, and tapioca starch were selected to use as binders. Binders were dissolved with boiled water into concentration 5% and 10% w/w except agar that was prepared 0.5% and 1% w/w. PR with and without binder were formulated. Physical properties, i.e. weight, shape, color, and hardness were evaluated. PR with 10% of corn starch solution had suitable hardness (14.2±0.9 kg) and the best appearance. In the future, it would be planned to study about odor and physical stability for decorated product development.

Keywords: aromatic water, hardness, natural binder, pang-rum

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Authors: Ghada E. Esheba, Ghadeer F. Alharthi, Duaa A. Alhejaili, Rawan E. Hudairy, Wafaa A. Altaezi, Raghad M. Alhejaili

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Background: Inflammatory bowel disease (IBD) consists of two specific gastrointestinal disorders: ulcerative colitis (UC) and Crohn's disease (CD). Despite their distinct natures, these two diseases share many similar etiologic, clinical and pathological features, as a result, their accurate differential diagnosis may sometimes be difficult. Correct diagnosis is important because surgical treatment and long-term prognosis differ from UC and CD. Aim: This study aims to study the characteristic clinicopathological features which help in the differential diagnosis between UC and CD, and assess the disease activity in ulcerative colitis. Materials and methods: This study was carried out on 50 selected cases. The cases included 27 cases of UC and 23 cases of CD. All the cases were examined using H& E and immunohistochemically for bcl-2 expression. Results: Characteristic features of UC include: decrease in mucous content, irregular or villous surface, crypt distortion, and cryptitis, whereas the main cardinal histopathological features seen in CD were: epitheloid granuloma, transmural chronic inflammation, absence of mucin depletion, irregular surface, or crypt distortion. 3 cases of UC were found to be associated with dysplasia. UC mucosa contains fewer Bcl-2+ cells compared with CD mucosa. Conclusion: This study using multiple parameters such clinicopathological features and Bcl-2 expression as studied by immunohistochemical stain, helped to gain an accurate differentiation between UC and CD. Furthermore, this work spotted the light on the activity and different grades of UC which could be important for the prediction of relapse.

Keywords: Crohn's disease, dysplasia, inflammatory bowel disease, ulcerative colitis

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Authors: Choo Fatt Foo

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The Five Aggregates is core to Buddhism teaching. According to Buddhism, human beings and all sentient beings are made up of nothing but the Five Aggregates. If that is the case, the Five Aggregates must be found in all natural sciences. So far, there has not been any systematic connection between the Five Aggregates and natural sciences. This study aims at identifying traces of the Five Aggregates in various levels of natural sciences and pointing possible directions for future research. The following areas are briefly explored to identify the connection with the Five Aggregates: physics, chemistry, organic chemistry, DNA, cell, and human body and brain. Traces of the Five Aggregates should be found in each level of this hierarchy of natural sciences for human and sentient beings to be said to be made up of the Five Aggregates. This study proposes a hierarchical structure of nature cutting every level with the Five Aggregates and the Four Great Elements as its basis. The structure proposed by this study would revolutionize how we look at nature. Hopefully, better understanding of sciences in this manner will steer the application of scientific methods and technology towards a brighter future with compassion and tolerance.

Keywords: the five aggregates, Buddhism, four great elements, physics, calabi-yau manifold

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Authors: Samera Salimpour Abkenar

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In traditional dyeing of natural fibers with natural dyes, metal salts are commonly used to increase color stability. This method always carries the risk of environmental pollution (contamination of arable soils and fresh groundwater) due to the release of dyeing effluents containing large amounts of metal. Therefore, researchers are always looking for new methods to obtain a green dyeing system. In this research, the use of the enzymatic dyeing method to prevent environmental pollution with metals and reduce production costs has been proposed. After degumming and bleaching, raw silk fabrics were dyed with natural dyes (Madder and Sumac) by three methods (pre-mordanting with a metal salt, one-step enzymatic dyeing, and two-step enzymatic dyeing). Results show that silk dyed with natural dyes by the enzymatic method has higher color strength and colorfastness than the pretreated with a metal salt. Also, the amount of remained dyes in the dyeing wastewater is significantly reduced by the enzymatic method. It is found that the enzymatic dyeing method leads to improvement of dye absorption, color strength, soft hand, no change in color shade, low production costs (due to low dyeing temperature), and a significant reduction in environmental pollution.

Keywords: eco-friendly, natural dyes, silk, traditional dyeing

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Authors: Skiker Kaoutar, Mounir Maouene

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Neuroimaging studies indicate that a large fronto-parieto-temporal network support nouns and their features, with some areas store semantic knowledge (visual, auditory, olfactory, gustatory,…), other areas store lexical representation and other areas are implicated in general semantic processing. However, it is not well understood how this fronto-parieto-temporal network can be modulated by different semantic tasks and different semantic relations between nouns. In this study, we combine a behavioral semantic network, functional MRI studies involving object’s related nouns and brain network studies to explain how different semantic tasks and different semantic relations between nouns can modulate the activity within the brain network of nouns and their features. We first describe how nouns and their features form a large scale brain network. For this end, we examine the connectivities between areas recruited during the processing of nouns to know which configurations of interaction areas are possible. We can thus identify if, for example, brain areas that store semantic knowledge communicate via functional/structural links with areas that store lexical representations. Second, we examine how this network is modulated by different semantic tasks involving nouns and finally, we examine how category specific activation may result from the semantic relations among nouns. The results indicate that brain network of nouns and their features is highly modulated and flexible by different semantic tasks and semantic relations. At the end, this study can be used as a guide to help neurosientifics to interpret the pattern of fMRI activations detected in the semantic processing of nouns. Specifically; this study can help to interpret the category specific activations observed extensively in a large number of neuroimaging studies and clinical studies.

Keywords: nouns, features, network, category specificity

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Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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Authors: Ayad Dalloo, Sulaf Dalloo

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Electrocardiogram (ECG) recording is prone to complications, on analysis by physicians, due to noise and artifacts, thus creating ambiguity leading to possible error of diagnosis. Such drawbacks may be overcome with the advent of high resolution Methods, such as Discrete Wavelet Analysis and Digital Signal Processing (DSP) techniques. This ECG signal analysis is implemented in three stages: ECG preprocessing, features extraction and classification with the aim of realizing high resolution ECG diagnosis and improved detection of abnormal conditions in the heart. The preprocessing stage involves removing spurious artifacts (noise), due to such factors as muscle contraction, motion, respiration, etc. ECG features are extracted by applying DSP and suggested sloping method techniques. These measured features represent peak amplitude values and intervals of P, Q, R, S, R’, and T waves on ECG, and other features such as ST elevation, QRS width, heart rate, electrical axis, QR and QT intervals. The classification is preformed using these extracted features and the criteria for cardiovascular diseases. The ECG diagnostic system is successfully applied to 12-lead ECG recordings for 12 cases. The system is provided with information to enable it diagnoses 15 different diseases. Physician’s and computer’s diagnoses are compared with 90% agreement, with respect to physician diagnosis, and the time taken for diagnosis is 2 seconds. All of these operations are programmed in Matlab environment.

Keywords: ECG diagnostic system, QRS detection, ECG baseline removal, cardiovascular diseases

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

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Authors: Seynabou Toure, Oumar Diop, Kidiyo Kpalma, Amadou S. Maiga

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Color and texture are the two most determinant elements for perception and recognition of the objects in an image. For this reason, color and texture analysis find a large field of application, for example in image classification and segmentation. But, the pioneering work in texture analysis was conducted on grayscale images, thus discarding color information. Many grey-level texture descriptors have been proposed and successfully used in numerous domains for image classification: face recognition, industrial inspections, food science medical imaging among others. Taking into account color in the definition of these descriptors makes it possible to better characterize images. Color texture is thus the subject of recent work, and the analysis of color texture images is increasingly attracting interest in the scientific community. In optical remote sensing systems, sensors measure separately different parts of the electromagnetic spectrum; the visible ones and even those that are invisible to the human eye. The amounts of light reflected by the earth in spectral bands are then transformed into grayscale images. The primary natural colors Red (R) Green (G) and Blue (B) are then used in mixtures of different spectral bands in order to produce RGB images. Thus, good color texture discrimination can be achieved using RGB under controlled illumination conditions. Some previous works investigate the effect of using different color space for color texture classification. However, the selection of the best performing color space in land-sea segmentation is an open question. Its resolution may bring considerable improvements in certain applications like coastline detection, where the detection result is strongly dependent on the performance of the land-sea segmentation. The aim of this paper is to present the results of a study conducted on different color spaces in order to show the best-performing color space for land-sea segmentation. In this sense, an experimental analysis is carried out using five different color spaces (RGB, XYZ, Lab, HSV, YCbCr). For each color space, the Haar wavelet decomposition is used to extract different color texture features. These color texture features are then used for Fusion of Over Segmentation (FOOS) based classification; this allows segmentation of the land part from the sea one. By analyzing the different results of this study, the HSV color space is found as the best classification performance while using color and texture features; which is perfectly coherent with the results presented in the literature.

Keywords: classification, coastline, color, sea-land segmentation

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Authors: Hossein Arfaeinia, Ahmad Jonidi Jafari, Sina Dobaradaran, Sadegh Niazi, Mojtaba Ehsanifar, Amir Zahedi

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Street dust and surface soil samples were collected from very heavy, heavy, medium and low traffic areas and natural site in Tehran, Iran. These samples were analyzed for some physical–chemical features, total and chemical speciation of selected metals and metalloids (Zn, Al, Sr, Pb, Cu, Cr, Cd, Co, Ni, and V) to study the effect of traffic on their mobility and accumulation in the environment. The pH, electrical conductivity (EC), carbonates and organic carbon (OC) values were similar in soil and dust samples from similar traffic areas. The traffic increases EC contents in dust/soil matrixes but has no effect on concentrations of metals and metalloids in soil samples. Rises in metal and metalloids levels with traffic were found in dust samples. Moreover, the traffic increases the percentage of acid soluble fraction and Fe and Mn oxides associated fractions of Pb and Zn. The mobilization of Cu, Zn, Pb, Cr in dust samples was easier than in soil. The speciation of metals and metalloids except Cd is mainly affected by physicochemical features in soil, although total metals and metalloids affected the speciation in dust samples (except chromium and nickel).

Keywords: street dust, surface soil, traffic, metals, metalloids, chemical speciation

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Authors: Junaid Kameran Ahmed

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A laminated plate composite of graphite/epoxy has been analyzed dynamically in the present work by using a quadratic element (8-node diso-parametric), and by depending on 1^st order shear deformation theory, every node in this element has 6-degrees of freedom (displacement in x, y, and z axis and twist about x, y, and z axis). The dynamic analysis in the present work covered parametric studies on a composite laminated plate (square plate) to determine its effect on the natural frequency of the plate. The parametric study is represented by set of changes (plate thickness, number of layers, support conditions, layer orientation), and the plates have been simulated by using ANSYS package 12. The boundary conditions considered in this study, at all four edges of the plate, are simply supported and fixed boundary condition. The results obtained from ANSYS program show that the natural frequency for both fixed and simply supported increases with increasing the number of layers, but this increase in the natural frequency for the first five modes will be neglected after 10 layers. And it is observed that the natural frequency of a composite laminated plate will change with the change of ply orientation, the natural frequency increases and it will be at maximum with angle 45 of ply for simply supported laminated plate, and maximum natural frequency will be with cross-ply (0/90) for fixed laminated composite plate. It is also observed that the natural frequency increase is approximately doubled when the thickness is doubled.

Keywords: laminated plate, orthotropic plate, square plate, natural frequency (free vibration), composite (graphite / epoxy)

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Authors: Sanpachai Huvanandana, Settapong Malisuwan, Soparwan Tongyuak, Prust Pannachet, Anong Phoepueak, Navneet Madan

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Many regions of Thailand are prone to flooding due to tropical climate. A commonly increasing precipitation in this continent results in risk of flooding. Many efforts have been implemented such as drainage control system, multiple dams, and irrigation canals. In order to decide where the drainages, dams, and canal should be appropriately located, the flooding risk area should be determined. This paper is aimed to identify the appropriate features that can be used to classify the flooding risk area in Thailand. Several features have been analyzed and used to classify the area. Non-supervised clustering techniques have been used and the results have been compared with ten years average actual flooding area.

Keywords: flood area clustering, geographical information system, flood features

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Authors: Zuzanna Miodonska, Michal Krecichwost, Pawel Badura

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Sigmatism (lisping) is a speech disorder in which sibilant consonants are mispronounced. The diagnosis of this phenomenon is usually based on the auditory assessment. However, the progress in speech analysis techniques creates a possibility of developing computer-aided sigmatism diagnosis tools. The aim of the study is to statistically verify whether specific acoustic features of sibilant sounds may be related to pronunciation correctness. Such knowledge can be of great importance while implementing classifiers and designing novel tools for automatic sibilants pronunciation evaluation. The study covers analysis of various speech signal measures, including features proposed in the literature for the description of normative sibilants realization. Amplitudes and frequencies of three fricative formants (FF) are extracted based on local spectral maxima of the friction noise. Skewness, kurtosis, four normalized spectral moments (SM) and 13 mel-frequency cepstral coefficients (MFCC) with their 1st and 2nd derivatives (13 Delta and 13 Delta-Delta MFCC) are included in the analysis as well. The resulting feature vector contains 51 measures. The experiments are performed on the speech corpus containing words with selected sibilant sounds (/ʃ, ʒ/) pronounced by 60 preschool children with proper pronunciation or with natural pathologies. In total, 224 /ʃ/ segments and 191 /ʒ/ segments are employed in the study. The Mann-Whitney U test is employed for the analysis of stigmatism and normative pronunciation. Statistically, significant differences are obtained in most of the proposed features in children divided into these two groups at p < 0.05. All spectral moments and fricative formants appear to be distinctive between pathology and proper pronunciation. These metrics describe the friction noise characteristic for sibilants, which makes them particularly promising for the use in sibilants evaluation tools. Correspondences found between phoneme feature values and an expert evaluation of the pronunciation correctness encourage to involve speech analysis tools in diagnosis and therapy of sigmatism. Proposed feature extraction methods could be used in a computer-assisted stigmatism diagnosis or therapy systems.

Keywords: computer-aided pronunciation evaluation, sigmatism diagnosis, speech signal analysis, statistical verification

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Authors: Mohamed Ayoub

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We perform computational investigation using density functional theory, B3LYP with aug-cc-pVTZ basis set followed by natural bond orbital analysis (NBO), which provides best single “natural Lewis structure” (NLS) representation of chosen wavefunction (Ψ) with natural resonance theory (NRT) to provide an analysis of molecular electron density in terms of resonance structures (RS) and weights (w). We selected for the study a wide range of gas phase dimers (B…HA), with hydrogen bond dissociation energies (ΔEB…H) that span more than two orders of magnitude. We demonstrate that charge transfer from a donor Lewis-type NBO (nB:) to an acceptor non-Lewis-type NBO (σHA*) is the primary cause for H-bonding not classical electrostatic (dipole-dipole or ionic). We provide a variety of structure, and spectroscopic descriptors to support the conclusion, such as IR frequency shift (ΔνHA), H-bond penetration distance (ΔRB..H), bond order (bB..H), charge-transfer (CTB→HA) and the corresponding donor-acceptor stabilization energy (ΔE(2)).

Keywords: natural bond orbital, hydrogen bonding, electron donor, electron acceptor

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Authors: Jitka Hroudova, Jiri Zach

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The majority of contemporary insulation materials commonly used in the building industry is made from non-renewable raw materials; furthermore, their production often brings high energy costs. A long-term trend as far as sustainable development is concerned has been the reduction of energy and material demands of building material production. One of the solutions is the possibility of using easily renewable natural raw material sources which are considerably more ecological and their production is mostly less energy-consuming compared to the production of normal insulations (mineral wool, polystyrene). The paper describes the results of research focused on the development of thermal and acoustic insulation materials based on natural fibres intended for floor constructions. Given the characteristic open porosity of natural fibre materials, the hygrothermal behaviour of the developed materials was studied. Especially the influence of relative humidity and temperature on thermal insulation properties was observed.

Keywords: Green thermal and acoustic insulating materials, natural fibres, technical hemp, flax, floor construction

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Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

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Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

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Authors: H. S. Aljabeili, E. A. Abd El-Hady, M. M. Abd El-Razik, M. Abd Elgadir

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The aim of the study is determining the quality characteristics of produced curing and dried camel meat contained some medicinal plants of thyme, rosemary, clove and ginger as natural preservatives. Camel meat samples were sliced and divided into five batches, one batch recorded as control sample was treated by the curing mixture (2.5%) contained the following ingredients: black pepper 1 gm, cumin 0.4 gm, spices mixture 0.5 gm, dried onion 3 gm, dried garlic 0.5 gm and salt 2 gm. To evaluate the effect of different natural preservatives sources of thyme, rosemary, clove and ginger, 3.0% of the aforementioned natural preservatives was mixed with the aforementioned curing mixture and used for curing the four batches of sliced camel meat. After curing process, cured sliced camel meat (control and treated with the natural preservatives) were conducting to drying process at 35 ± 3 °C for 36 h in a drying cabinet. The quality characteristics of prepared dried camel meat were evaluated such as chemical composition, microbiological characteristics and sensory characteristics. Based on the microbiological and sensory characteristics, it could be suggested that the selected medicinal plants specially thyme and rosemary could be used as natural preservatives for preparing semi dry camel meat without negative effects.

Keywords: curing, dried camel meat, medicinal plants, natural preservatives, quality characteristics

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Authors: Sumaira Zafar, Arjumand Zaidi

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During past few years, several floods have adversely affected the areas along lower Indus River. Besides other climate related anomalies, rapidly increasing urbanization and blockage of natural drains due to siltation or encroachments are two other critical causes that may be responsible for these disasters. Due to flat topography of river Indus plains and blockage of natural waterways, drainage of storm water takes time adversely affecting the crop health and soil properties of the area. Government of Sindh is taking a keen interest in revival of natural drainage network in the province and has initiated this work under Sindh Irrigation and Drainage Authority. In this paper, geospatial techniques are used to analyze landuse/land-cover changes of Larkana district over the past three decades (1980-present) and their impact on natural drainage system. Satellite derived Digital Elevation Model (DEM) and topographic sheets (recent and 1950) are used to delineate natural drainage pattern of the district. The urban landuse map developed in this study is further overlaid on drainage line layer to identify the critical areas where the natural floodwater flows are being inhibited by urbanization. Rainfall and flow data are utilized to identify areas of heavy flow, whereas, satellite data including Landsat 7 and Google Earth are used to map previous floods extent and landuse/cover of the study area. Alternatives to natural drainage systems are also suggested wherever possible. The output maps of natural drainage pattern can be used to develop a decision support system for urban planners, Sindh development authorities and flood mitigation and management agencies.

Keywords: geospatial techniques, satellite data, natural drainage, flood, urbanization

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Authors: Kamel A. Elshorbagy, Mohamed A. Hussein, Rola S. Afify

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Natural gas pressure reduction is typically achieved using pressure reducing valves, where isenthalpic expansion takes place with considerable amount of wasted energy in an irreversible throttling process of the gas. Replacing gas-throttling process by an expansion process in a turbo expander (TE) converts the pressure of natural gas into mechanical energy transmitted to a loading device (i.e. an electric generator). This paper investigates the performance of a turboexpander system for power recovery at natural gas pressure reduction stations. There is a considerable temperature drop associated with the turboexpander process. Essential preheating is required, using gas fired boilers, to avoid undesirable effects of a low outlet temperature. Various system configurations were simulated by the general flow sheet simulator HYSYS and factors affecting the overall performance of the systems were investigated. Power outputs and fuel requirements were found using typical gas flow variation data. The simulation was performed for two case studies in which real input data are used. These case studies involve a domestic (commercial) and an industrial natural gas pressure reduction stations in Egypt. Economic studies of using the turboexpander system in both of the two natural gas pressure reduction stations are conducted using precise data obtained through communication with several companies working in this field. The results of economic analysis, for the two case studies, prove that using turboexpander systems in Egyptian natural gas reduction stations can be a successful project for energy conservation.

Keywords: natural gas, power recovery, reduction stations, turboexpander systems

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Authors: Xinyu Gong, Zhilin Li, Xintao Liu

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Maps are a means of communication. Cartographic language involves established theories of natural language for understanding maps. “Cartographic words’, or “map symbols”, are crucial elements of cartographic language. Personalized mapping is increasingly popular, with growing demands for customized map-making by the general public. Automated symbol-making and customization play a key role in personalized mapping. However, formal representations for the automated construction of map symbols are still lacking. In natural language, the process of word and sentence construction can be formalized. Through the analogy between natural language and graphical language, formal representations of natural language construction can be used as a reference for constructing cartographic language. We selected Chinese character structures (i.e., S

Keywords: personalized mapping, Chinese character, cartographic language, map symbols

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Authors: Anes Enakoa, Yawei Liang

Abstract:

Question Answering (QA) system is one of the most important and demanding tasks in the field of Natural Language Processing (NLP). In QA systems, the answer generation task generates a list of candidate answers to the user's question, in which only one answer is correct. Answer selection is one of the main components of the QA, which is concerned with selecting the best answer choice from the candidate answers suggested by the system. However, the selection process can be very challenging especially in Arabic due to its particularities. To address this challenge, an approach is proposed to answer questions with multiple answer choices for Arabic QA systems based on Textual Entailment (TE) recognition. The developed approach employs a Support Vector Machine that considers lexical, semantic and syntactic features in order to recognize the entailment between the generated hypotheses (H) and the text (T). A set of experiments has been conducted for performance evaluation and the overall performance of the proposed method reached an accuracy of 67.5% with C@1 score of 80.46%. The obtained results are promising and demonstrate that the proposed method is effective for TE recognition task.

Keywords: information retrieval, machine learning, natural language processing, question answering, textual entailment

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Authors: Raymon Maac, Michael Arthus Muega, Joyce Ann Calingasan, Elva Maureen Gorospe

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Critical pedagogy is known for its advocacy of humanistic and liberating education. Its far-reaching approach helps students to understand and analyze their own situations and the realities happening in their society. However, this pedagogy together with its promising features is not well-known in the Philippines. This paper determines the place of critical pedagogy in the new values education curriculum and analyzes its features in the K-12 Values Education curriculum and textbook. The study examines the position of critical pedagogy in the Philippine K-12 Values Education curriculum by closely studying and comparing their features; and scrutinizes the Grade 8 Values Education textbook specifically modules 4, 8, 10 and 13 which comprises 25% of the total 16 modules. The said modules are concerned with the role of the family in the preservation of social justice, which is one of the objectives of critical pedagogy. The findings in this research were based on the pieces of evidence gathered from the curriculum and textbook itself. Based on the evaluation done, the study found out that the ideas of critical pedagogy were the same with that of the objectives of K-12 Values Education Curriculum. Due to this, values education teachers can utilize critical pedagogy in their subject. In addition, the K-12 Values Education curriculum exhibits some of the features of critical pedagogy such as authentic student empowerment and critical thinking. Lastly, some features of critical pedagogy are also evident in some of the general parts and recommended activities in the K-12 Values Education textbook while other activities need to be fully developed by both teacher and students to reflect the genuine critical pedagogy.

Keywords: authentic student empowerment, critical pedagogy, critical thinking, liberating education

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Authors: I. Graur, V. Bria, C. Muntenita

Abstract:

Recent ecological interests have resulted in scientific concerns regarding natural-organic powder composites. Because natural-organic powders are cheap and biodegradable, green composites represent a substantial contribution in polymer science area. The aim of this study is to point out the effect of natural-organic powder resulting from the grinding of pine needles used as a modifying agent for Epiphen epoxy resin and is focused on friction coefficient behavior. A pin-on-disc setup is used for friction coefficient experiments. Epiphen epoxy resin was used with the different ratio of organic powder from the grinding of pine needles. Because of the challenges of natural organic powder, more and more companies are looking at organic composite materials.

Keywords: epoxy, friction coefficient, organic powder, pine needles

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Authors: Rita Darmayanti

Abstract:

This study aims at investigating the discourse pattern and structure of research article abstracts. The characteristics of the language used in abstracts written by non-native English-speaking (NNES) novice researchers are mainly examined in terms of rhetorical moves and the degree of variability of the rhetorical features as indicated by the structure of clauses and the linguistic features of the text. To this end, 20 abstracts written by undergraduate students of the accounting department at the State Polytechnic of Malang in 2018-2019 were employed as the data of this study. Findings showed that the most frequently used pattern of the rhetorical move is I(Introduction)-P(Purpose)-M(Method)-Pr(Product or Result)-C(Conclusion) with the significant use of active sentence and present and past tense. The findings of the study are projected to be utilized for evaluating the quality of students’ abstracts and generating a pedagogical proposal of ESP writing course or at least providing a critical review of current practices in ESP program intended for non-native English students at tertiary level.

Keywords: rhetorical features, rhetorical moves, non-native English-speaking novice researchers, research abstract

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Authors: Alanod Alqasim, Yasmine Iskandarani, Sita Algethami, Jawaher alzughaiby

Abstract:

This study focuses on the usage of AI (Artificial Intelligence) systems and features on the Instagram application and how it influences user experience and satisfaction. The aim is to evaluate the techniques and current capabilities, restrictions, and potential future directions of AI in an Instagram application. Following a concise explanation of the core concepts underlying AI usage on Instagram. To answer this question, 19 randomly selected users were asked to complete a 9-question survey on their experience and satisfaction with the app's features (Filters, user preferences, translation tool) and authenticity. The results revealed that there were three prevalent allegations. These declarations include that Instagram has an extremely attractive user interface; secondly, Instagram creates a strong sense of community; and lastly, Instagram has an important influence on mental health.

Keywords: AI (Artificial Intelligence), instagram, features, satisfaction, experience

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