Search results for: content independent features

Authors: Raj Kumari Bahl, Sotirios Sabanis

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In this paper, we are concerned with the valuation of the first Catastrophic Mortality Bond that was launched in the market namely the Swiss Re Mortality Bond 2003. This bond encapsulates the behavior of a well-defined mortality index to generate payoffs for the bondholders. Pricing this bond is a challenging task. We adapt the payoff of the terminal principal of the bond in terms of the payoff of an Asian put option and present an approach to derive model-independent bounds exploiting comonotonic theory. We invoke Jensen’s inequality for the computation of lower bounds and employ Lagrange optimization technique to achieve the upper bound. The success of these bounds is based on the availability of compatible European mortality options in the market. We carry out Monte Carlo simulations to estimate the bond price and illustrate the strength of these bounds across a variety of models. The fact that our bounds are model-independent is a crucial breakthrough in the pricing of catastrophic mortality bonds.

Keywords: mortality bond, Swiss Re Bond, mortality index, comonotonicity

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Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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Authors: Hyeongdo Jeong, Jong Kook Lee

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Granule morphology and microstructure were affected by slurry viscosity, chemical composition, particle size and spray drying process. In this study, we investigated granule morphology of zirconia powder with solid content on two-fluid spray drying. Zirconia granules after spray drying show sphere-like shapes with a diameter of 40-70 μm at low solid contents (30 or 40 wt%) and specific surface area of 5.1-5.6 m²/g. But a donut-like shape with a few cracks were observed on zirconia granules prepared from the slurry of high solid content (50 wt %), green compacts after cold isostatic pressing under the pressure of 200 MPa have the density of 2.1-2.2 g/cm³ and homogeneous fracture surface by complete destruction of granules. After the sintering at 1500 °C for 2 h, all specimens have relative density of 96.2-98.3 %. With increasing a solid content from 30 to 50 wt%, grain size increased from 0.3 to 0.6 μm, but relative density was inversely decreased from 98.3 to 96.2 %.

Keywords: zirconia, solid content, granulation, spray drying

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Authors: Jihan Abdulazeez Ahmed, Adnan Mohsin Abdulazeez Brifcani

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This paper suggests a new internal architecture of holon based on feature selection model using the combination of Bees Algorithm (BA) and Artificial Neural Network (ANN). BA is used to generate features while ANN is used as a classifier to evaluate the produced features. Proposed system is applied on the Wine data set, the statistical result proves that the proposed system is effective and has the ability to choose informative features with high accuracy.

Keywords: artificial neural network, bees algorithm, feature selection, Holon

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Authors: Cate MacMillan, Nicholas J. Stevens, Johanna Rosier, Steven Boyd

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Choosing where to live is an important decision for anybody, however, this decision is more complex if you are an adult with intellectual disability. Our research asked adults with intellectual disability, parents and carers and disability, housing and built environment decision makers what they considered important in deciding where to live. If medical advances continue to improve the longevity of adults with intellectual disability, many of these adults will outlive their parents. With appropriate community support, and in appropriately designed neighbourhoods, many will be able to live independently. Our research suggests that the key to achieving independent living as an adult with intellectual disability is not so much about the house but the type of neighbourhood and its design. This paper presents the results of interviews and details a practical approach which will better inform urban development decision-makers in establishing safe, inclusive and accessible neighbourhood design.

Keywords: inclusion, independent living, intellectual disability, neighbourhoods, systems thinking, urban design and planning

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Authors: Reema Alghamdi, Rasees Aleisa, Layan Sukkar

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The primary objective of this research is to conduct an examination of the Flo menstrual cycle application. We do that by evaluating the user experience and their satisfaction with integrated AI features. The study seeks to gather data from primary resources, primarily through surveys, to gather different insights about the application, like its usability functionality in addition to the overall user satisfaction. The focus of our project will be particularly directed towards the impact and user perspectives regarding the integration of artificial intelligence features within the application, contributing to an understanding of the holistic user experience.

Keywords: period, women health, machine learning, AI features, menstrual cycle

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Authors: Ágnes Bogárdi-Mészöly, Takeshi Hashimoto, Shohei Yokoyama, Hiroshi Ishikawa

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The spread of Web 2.0 has caused user-generated content explosion. Users can tag resources to describe and organize them. Tag clouds provide rough impression of relative importance of each tag within overall cloud in order to facilitate browsing among numerous tags and resources. The goal of our paper is to enrich visualization of tag clouds. A font distribution algorithm has been proposed to calculate a novel metric based on frequency and content, and to classify among classes from this metric based on power law distribution and percentages. The suggested algorithm has been validated and verified on the tag cloud of a real-world thesis portal.

Keywords: tag cloud, font distribution algorithm, frequency-based, content-based, power law

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Authors: S. Kongtun-Janphuk, S. Niwitpong Jr., J. Saengsai

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Low-sugar snack bars were formulated with 3 main formulas depending on the main ingredient, which were peanut-green bean-sesame, apple, and prune. The most acceptable formula of each group was obtained by sensory evaluation using a nine-point hedonic scale. The moisture content, total ash, protein, fat and fiber were analyzed by the standard methods of AOAC. The peanut-mung bean-sesame snack bar showed the highest protein content (88.32%) and total fat (0.48%) with the lowest of fiber content (0.01%) while the prune formula showed the lowest protein content (71.91%) and total fat (0.21%) with the highest of fiber content (0.03%). This result indicated that the prune formula could be used as diet food to assist in weight loss program.

Keywords: low-sugar snack bar, diet food, nutrition analysis, food formulation

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Authors: Mehul Srivastava, Sharma Tushar Ravikant, Mridul Krishn Mishra

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In structural design, the evaluation of safety and probability failure of structure is of significant importance, mainly when the variables are random. On real structures, structural reliability can be evaluated obtaining an implicit limit state function. The structural reliability limit state function is obtained depending upon the statistically independent variables. In the analysis of reliability, we considered the statistically independent random variables to be the load intensity applied and the depth or height of the beam member considered. There are many approaches for structural reliability problems. In this paper Extreme Learning Machine technique and First Order Second Moment Method is used to determine the reliability indices for the same set of variables. The reliability index obtained using ELM is compared with the reliability index obtained using FOSM. Higher the reliability index, more feasible is the method to determine the reliability.

Keywords: reliability, reliability index, statistically independent, extreme learning machine

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Authors: Sanjeeb Kumar Mohanty

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Content Based Instruction (CBI) in English Language Teaching (ELT) basically helps English as Second Language (ESL) learners of English. At the same time, it fosters multidisciplinary style of learning by promoting collaborative learning style. It is an approach to teaching ESL that attempts to combine language with interdisciplinary learning for bettering language proficiency and facilitating content learning. Hence, the basic purpose of CBI is that language should be taught in conjunction with academic subject matter. It helps in establishing the content as well as developing language competency. This study aims at supporting the potential values of interdisciplinary approach in promoting English Language Learning (ELL) by teaching writing skills to a small group of learners and discussing the findings with the teachers from various disciplines in a workshop. The teachers who are oriented, they use the same approach in their classes collaboratively. The inputs from the learners as well as the teachers hopefully raise positive consciousness with regard to the vast benefits that Content Based Instruction can offer in advancing the language competence of the learners.

Keywords: content based instruction, interdisciplinary approach, writing skills, collaborative approach

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Authors: Pravina Gurjar, Bothiraja Pour, Vijay Kumbhar, Ganesh Dama

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Andrographolide (AG), a bioactive phytoconstituent, has a wider range of pharmacological action. However, due to the intestinal degradation, shows low oral bioavailability. The aim of the present work was to develop Floating In-situ gelling Gastro retentive System (FISGS) for AG in order to enhance its site specific absorption and minimize pH dependent hydrolysis in alkaline environment. Further to increase its therapeutic efficacy for peptic ulcer disease caused by H. pyroli. Gellan based floating in situ gelling system of AG were prepared by using sodium citrate and calcium carbonate. The 32 factorial designs was used to study the effect of gellan and calcium carbonate concentration (independent variables) on dependent variable such as viscosity, floating lag time and drug release. Developed system was evaluated for drug content, floating lag time, viscosity, and drug release studies. Drug content, viscosity, and floating lag time was found to be 81-99%, 67-117 Cps, and 3-5 sec, respectively. The obtained system showed good in vitro floating ability for more than 12 h using 0.1 N HCl as dissolution medium with initial burst release followed by the controlled zero order drug release up to 24 hrs. In vivo testing of FISGS of AG to rats demonstrated significant antiulcer activity that were evaluated by various parameters like pH, volume, total acidity, millimole equivalent of H+ ions/30 min, and protein content of gastric content. The densities of all the formulation batches were found to be near about 0.9 and floating duration above 12 hr. It was observed that with the increase in conc. of gellan there was increase in the viscosity of formulation but all formulations were in optimum range. The drug content of optimized batch was found to be 99.23. In histopathology study of stomach, the villi at the mucosal surface, the intercellular junction, the intestinal lumen were intact; no destruction of the epithelium, and submucosal gland in formulation treated and control group animals as compared to pure drug AG and standard ranitidine. Gellan-based in situ gastro retentive floating system could be advantageous in terms of increased bioavailability of AG to maintain an effective drug conc. in gastric fluid as well as in serum for longer period of time.

Keywords: andrographolide, floating drug delivery, in situ gelling system, gastroretentive system

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Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

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In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

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Authors: Hoda M. Eid, Abir Nachar, Farah Thong, Gary Sweeney, Pierre S. Haddad

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Caffeic acid methyl ester (CAME) and caffeic ethyl esters (CAEE) were previously reported to potently stimulate glucose uptake in cultured C2C12 skeletal muscle cells via insulin-independent mechanisms involving the activation of adenosine monophosphate-activated protein kinase (AMPK). In the present study, we investigated the effect of the two compounds on the translocation of glucose transporter GLUT4 in L6 skeletal muscle cells. The cells were treated with the optimum non-toxic concentration (50 µM) of either CAME or CAEE for 18 h. Levels of GLUT4myc at the cell surface were measured by O-phenylenediamine dihydrochloride (OPD) assay. The effects of CAME and CAEE on GLUT1 and GLUT4 protein content were also measured by western immunoblot. Our results show that CAME and CAEE significantly increased glucose uptake, GLUT4 translocation and GLUT4 protein content. Furthermore, the effect of the two CA esters on two insulin-sensitive cell lines: H4IIE rat hepatoma and 3T3-L1 adipocytes were investigated. CAME and CAEE reduced the enzymatic activity of the key hepatic gluconeogenic enzyme glucose-6-phosphatase in a concentration-dependent manner. In addition, they exerted a concentration-dependent antiadipogenic effect on 3T3-L1 cells. Mitotic clonal expansion (MCE), a prerequisite for adipocytes differentiation was also concentration-dependently inhibited. The two compounds abrogated lipid droplet accumulation, blocked MCE and maintained cells in fibroblast-like state when applied at the maximum non-toxic concentration (100 µM). In addition, the expression of the early key adipogenic transcription factors CCAAT enhancer-binding protein beta (C/EBP-β) and the master regulator of adipogenesis peroxisome-proliferator-activated receptor gamma (PPAR-γ) were inhibited. We, therefore, conclude that CAME and CAEE exert pleiotropic benefits in several insulin-sensitive cell lines through insulin-independent mechanisms involving AMPK, hence they may treat obesity, diabetes and other metabolic diseases.

Keywords: type 2 diabetes mellitus, insulin resistance, GLUT4, Akt, AMPK.

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Authors: Suwarno, M. Helmi Prakoso

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Mineral oil is commonly used for high voltage transformer insulation. The insulation quality of mineral oil is affecting the operation process of high voltage transformer. There are many contaminations which could decrease the insulation quality of mineral oil. One of them is water. This research talks about the effect of water content on dielectric properties, physic properties, and partial discharge pattern on mineral oil. Samples were varied with 10 varieties of water content value. And then all samples were tested to measure the dielectric properties, physic properties, and partial discharge pattern. The result of this research showed that an increment of water content value would decrease the insulation quality of mineral oil.

Keywords: dielectric properties, high voltage transformer, mineral oil, water content

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Authors: Mohammed Albahttiti, Eliana Aguilar

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A push for sustainability in the concrete industry is increasing. Cow manure itself is becoming a problem and having the potential solution to use it in concrete as a cementitious replacement would be an ideal solution. For cow manure ash to become a well-rounded substitute, it would have to meet the right criteria to progress in becoming a more popular idea in the concrete industry. This investigation primarily focuses on how the replacement of cow manure ash affects the air content and air void distribution in concrete. In order to assess these parameters, the Super Air Meter (SAM) was used to test concrete in this research. In addition, multiple additional tests were performed, which included the slump test, temperature, and compression test. The strength results of the manure ash in concrete were promising. The manure showed compression strength results that are similar to that of the other supplementary cementitious materials tested. On the other hand, concrete samples made with cow manure ash showed 2% air content loss and an increasing SAM number proportional to cow manure content starting at 0.38 and increasing to 0.8. In conclusion, while the use of cow manure results in loss of air content, it results in compressive strengths similar to other supplementary cementitious materials.

Keywords: air content, biomass ash, cow manure ash, super air meter, supplementary cementitious materials

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Authors: Lidia N. Hernández-Piña, Carlos R. Jaimez-González

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Interoperability in distributed systems is an important feature that refers to the communication of two applications written in different programming languages. This paper presents a serializer and a de-serializer of PHP objects to and from XML, which is an independent library written in the PHP programming language. The XML generated by this serializer is independent of the programming language, and can be used by other existing Web Objects in XML (WOX) serializers and de-serializers, which allow interoperability with other object-oriented programming languages.

Keywords: interoperability, PHP object serialization, PHP to XML, web objects in XML, WOX

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Authors: Irfan Ahmad Afip

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This main research objective is to accurately identify the possibility for a Leptospirosis outbreak severity of a certain area based on its input features into a multivariate regression model. The research question is the possibility of an outbreak in a specific area being influenced by this feature, such as social demographics and hydrometeorological extremes. If the occurrence of an outbreak is being subjected to these features, then the epidemic severity for an area will be different depending on its environmental setting because the features will influence the possibility and severity of an outbreak. Specifically, this research objective was three-fold, namely: (a) to identify the relevant multivariate features and visualize the patterns data, (b) to develop a multivariate regression model based from the selected features and determine the possibility for Leptospirosis outbreak in an area, and (c) to compare the predictive ability of multivariate regression model and machine learning algorithms. Several secondary data features were collected locations in the state of Negeri Sembilan, Malaysia, based on the possibility it would be relevant to determine the outbreak severity in the area. The relevant features then will become an input in a multivariate regression model; a linear regression model is a simple and quick solution for creating prognostic capabilities. A multivariate regression model has proven more precise prognostic capabilities than univariate models. The expected outcome from this research is to establish a correlation between the features of social demographic and hydrometeorological with Leptospirosis bacteria; it will also become a contributor for understanding the underlying relationship between the pathogen and the ecosystem. The relationship established can be beneficial for the health department or urban planner to inspect and prepare for future outcomes in event detection and system health monitoring.

Keywords: geographical information system, hydrometeorological, leptospirosis, multivariate regression

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Authors: Xiaopeng Shang, Xin YU, Jun CHANG

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Calcium barium sulphoaluminate (CBSA), derived from calcium sulphoaluminate(CSA), has excellent cementitious properties. In this study, the sintering system of CBSA with a theoretical stoichiometric Ca3BaAl6SO16 was investigated. Rietveld refinement was performed using TOPAS 4.2 software to quantitatively calculate the content of CBSA and the actual ionic site occupancy of Ba2+. The results indicate that the contents of Ca4-xBaxAl6SO16 increases with increasing sintering temperature in the 1200℃-1400℃ ranges. When sintered at 1400℃ for 180min, the content of CBSA reaches 88.4%. However, CBSA begins to decompose at 1440℃ and the content of which decreases. The replacement rate of Ba2+ was also enlarged by increasing sintering temperature and prolonged sintering time. Sintering at 1400℃ for 180min is considered as the optimum when replacement rate of Ba2+ and the content of CBSA were taken into account. Ca3.2Ba0.8Al6SO16 with a content of 88.4% was synthesized.

Keywords: calcium barium sulphoaluminate, sintering system, Ba2+ replacement rate, Rietveld refinement

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Authors: Ekaterina Semenova

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The article explores the issue of website owners’ liability for the illicit content. Whilst various issues of secondary liability of internet access providers for the illicit content have been widely discussed in the law doctrine, the liability of website owners has attracted less attention. Meanwhile, the website blocking injunctions influence website owners’ rights most, since website owners have the interest to keep their website online, rather than internet access providers. The discussion of internet access providers’ liability overshadows the necessity to protect the website owners’ rights to due process and proportionality of blocking injunctions. The analysis of Russian website blocking regulation and case law showed that the protection of website owners’ rights depends on the kind of illicit content: some content induces automatic blocking injunctions without prior notice of website owners and any opportunity to appeal, while other content does not invoke automatic blocking and provides an opportunity for the website owner to avoid or appeal an injunction. Comparative analysis of website blocking regulations in European countries reveals different approaches to the proportionality of website blocking and website owner’s rights protection. Based on the findings of the study, we conclude that the global trend to impose website blocking injunctions on wide range of illicit content without due process of law interferes with the rights of website owners.

Keywords: illicit content, liability, Russia, website blocking

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Authors: Martina Katalin Szabó, Bernadett Lipóczi, Csenge Guba, István Uveges

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In this study, an exhaustive analysis was carried out about the historical development of negative emotive intensifiers in the Hungarian language via NLP methods. Intensifiers are linguistic elements which modify or reinforce a variable character in the lexical unit they apply to. Therefore, intensifiers appear with other lexical items, such as adverbs, adjectives, verbs, infrequently with nouns. Due to the complexity of this phenomenon (set of sociolinguistic, semantic, and historical aspects), there are many lexical items which can operate as intensifiers. The group of intensifiers are admittedly one of the most rapidly changing elements in the language. From a linguistic point of view, particularly interesting are a special group of intensifiers, the so-called negative emotive intensifiers, that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g.borzasztóanjó ’awfully good’, which means ’excellent’). Despite their special semantic features, negative emotive intensifiers are scarcely examined in literature based on large Historical corpora via NLP methods. In order to become better acquainted with trends over time concerning the intensifiers, The exhaustively analysed a specific historical corpus, namely the Magyar TörténetiSzövegtár (Hungarian Historical Corpus). This corpus (containing 3 millions text words) is a collection of texts of various genres and styles, produced between 1772 and 2010. Since the corpus consists of raw texts and does not contain any additional information about the language features of the data (such as stemming or morphological analysis), a large amount of manual work was required to process the data. Thus, based on a lexicon of negative emotive intensifiers compiled in a previous phase of the research, every occurrence of each intensifier was queried, and the results were stored in a separate data frame. Then, basic linguistic processing (POS-tagging, lemmatization etc.) was carried out automatically with the ‘magyarlanc’ NLP-toolkit. Finally, the frequency and collocation features of all the negative emotive words were automatically analyzed in the corpus. Outcomes of the research revealed in detail how these words have proceeded through grammaticalization over time, i.e., they change from lexical elements to grammatical ones, and they slowly go through a delexicalization process (their negative content diminishes over time). What is more, it was also pointed out which negative emotive intensifiers are at the same stage in this process in the same time period. Giving a closer look to the different domains of the analysed corpus, it also became certain that during this process, the pragmatic role’s importance increases: the newer use expresses the speaker's subjective, evaluative opinion at a certain level.

Keywords: historical corpus analysis, historical linguistics, negative emotive intensifiers, semantic changes over time

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Authors: Fawaz S. Al-Anzi, Dia AbuZeina

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Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

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Authors: Anita Singh, Richa Naula, Manoj Raghav

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Nutrient rich and high-yielding varieties of fenugreek can be developed by using genotypes which are naturally high in nutrients. Gene banks harbour scanty germplasm collection of Trigonella spp. and a very little background information about its genetic diversity. The extent of genetic diversity in a specific breeding population depends upon the genotype included in it. The present investigation aims at the estimation of macronutrient (phosphorus by spectrophotometer and potassium by flame photometer), micronutrients, namely, iron, zinc, manganese, and copper from seeds of fenugreek genotypes using atomic absorption spectrophotometer, protein by Rapid N Cube Analyser and Steroidal Saponins. Twenty-eight genotypes of fenugreek along with two standard checks, namely, Pant Ragini and Pusa Early Bunching were collected from different parts of India, and nutrient contents of each genotype were determined at G. B. P. U. A. & T. Laboratory, Pantnagar. Highest potassium content was observed in PFG-35 (1207 mg/100g). PFG-37 and PFG-20 were richest in phosphorus, iron and manganese content among all the genotypes. The lowest zinc content was found in PFG-26 (1.19 mg/100g), while the maximum zinc content was found in PFG- 28 (4.43 mg/100g). The highest content of copper was found in PFG-26 (1.97 mg/100g). PFG-39 has the highest protein content (29.60 %). Significant differences were observed in the steroidal saponin among the genotypes. Saponin content ranged from 0.38 g/100g to 1.31 g/100g. Steroidal Saponins content was found the maximum in PFG-36 (1.31 g/100g) followed by PFG-17 (1.28 g/100g). Therefore, the genotypes which are rich in nutrient and oil content can be used for plant biofortification, dietary supplements, and herbal products.

Keywords: genotypes, macronutrients, micronutrient, protein, seeds

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Authors: Khatuna Buskivadze

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The aim of the present study is to investigate the sociolinguistic and classroom functions and frequency of Teacher’s Code Switching (CS) in the Content and Language Integrated (CLIL) Lesson. Nowadays, Georgian society struggles to become the part of the European world, the English language itself plays a role in forming new generations with European values. Based on our research conducted in 2019, out of all 114 private schools in Tbilisi, full- programs of CLIL are taught in 7 schools, while only some subjects using CLIL are conducted in 3 schools. The goal of the former research was to define the features of Content and Language Integrated learning (CLIL) methodology within the process of teaching English on the Example of Georgian private high schools. Taking the Georgian reality and cultural features into account, the modified version of the questionnaire, based on the classification of using CS in ESL Classroom proposed By Ferguson (2009) was used. The qualitative research revealed students’ and teacher’s attitudes towards teacher’s code-switching in CLIL lesson. Both qualitative and quantitative research were conducted: the observations of the teacher’s lessons (Recording of T’s online lessons), interview and the questionnaire among Math’s T’s 20 high school students. We came to the several conclusions, some of them are given here: Math’s teacher’s CS behavior mostly serves (1) the conversational function of interjection; (2) the classroom functions of introducing unfamiliar materials and topics, explaining difficult concepts, maintaining classroom discipline and the structure of the lesson; The teacher and 13 students have negative attitudes towards using only Georgian in teaching Math. The higher level of English is the more negative is attitude towards using Georgian in the classroom. Although all the students were Georgian, their competence in English is higher than in Georgian, therefore they consider English as an inseparable part of their identities. The overall results of the case study of teaching Math (Educational discourse) in one of the private schools in Tbilisi will be presented at the conference.

Keywords: attitudes, bilingualism, code-switching, CLIL, conversation analysis, interactional sociolinguistics.

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Authors: Sajjad Akbar, Rabia Bashir

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With the growth of the number of users, the Internet usage has evolved. Due to its key design principle, there is an incredible expansion in its size. This tremendous growth of the Internet has brought new applications (mobile video and cloud computing) as well as new user’s requirements i.e. content distribution environment, mobility, ubiquity, security and trust etc. The users are more interested in contents rather than their communicating peer nodes. The current Internet architecture is a host-centric networking approach, which is not suitable for the specific type of applications. With the growing use of multiple interactive applications, the host centric approach is considered to be less efficient as it depends on the physical location, for this, Information Centric Networking (ICN) is considered as the potential future Internet architecture. It is an approach that introduces uniquely named data as a core Internet principle. It uses the receiver oriented approach rather than sender oriented. It introduces the naming base information system at the network layer. Although ICN is considered as future Internet architecture but there are lot of criticism on it which mainly concerns that how ICN will manage the most relevant content. For this Web Content Mining(WCM) approaches can help in appropriate data management of ICN. To address this issue, this paper contributes by (i) discussing multiple ICN approaches (ii) analyzing different Web Content Mining approaches (iii) creating a new Internet architecture by merging ICN and WCM to solve the data management issues of ICN. From ICN, Content-Centric Networking (CCN) is selected for the new architecture, whereas, Agent-based approach from Web Content Mining is selected to find most appropriate data.

Keywords: agent based web content mining, content centric networking, information centric networking

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Authors: Martina Katalin Szabó, István Üveges

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In this paper, the usage of negative emotive words is examined on the basis of a large Hungarian twitter-database via NLP methods. The data is analysed from a gender point of view, as well as changes in language usage over time. The term negative emotive word refers to those words that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g. rohadt jó ’damn good’) or a sentiment expression with positive polarity despite their negative prior polarity (e.g. brutális, ahogy ez a férfi rajzol ’it’s awesome (lit. brutal) how this guy draws’. Based on the findings of several authors, the same phenomenon can be found in other languages, so it is probably a language-independent feature. For the recent analysis, 67783 tweets were collected: 37818 tweets (19580 tweets written by females and 18238 tweets written by males) in 2016 and 48344 (18379 tweets written by females and 29965 tweets written by males) in 2021. The goal of the research was to make up two datasets comparable from the viewpoint of semantic changes, as well as from gender specificities. An exhaustive lexicon of Hungarian negative emotive intensifiers was also compiled (containing 214 words). After basic preprocessing steps, tweets were processed by ‘magyarlanc’, a toolkit is written in JAVA for the linguistic processing of Hungarian texts. Then, the frequency and collocation features of all these words in our corpus were automatically analyzed (via the analysis of parts-of-speech and sentiment values of the co-occurring words). Finally, the results of all four subcorpora were compared. Here some of the main outcomes of our analyses are provided: There are almost four times fewer cases in the male corpus compared to the female corpus when the negative emotive intensifier modified a negative polarity word in the tweet (e.g., damn bad). At the same time, male authors used these intensifiers more frequently, modifying a positive polarity or a neutral word (e.g., damn good and damn big). Results also pointed out that, in contrast to female authors, male authors used these words much more frequently as a positive polarity word as well (e.g., brutális, ahogy ez a férfi rajzol ’it’s awesome (lit. brutal) how this guy draws’). We also observed that male authors use significantly fewer types of emotive intensifiers than female authors, and the frequency proportion of the words is more balanced in the female corpus. As for changes in language usage over time, some notable differences in the frequency and collocation features of the words examined were identified: some of the words collocate with more positive words in the 2nd subcorpora than in the 1st, which points to the semantic change of these words over time.

Keywords: gender differences, negative emotive words, semantic changes over time, twitter

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Authors: Priyanka Sharma

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The women voter turnout in India is increasing. The rising female voter turnout is explained in part by men intimidating women in the household to vote. Women are more likely than men to be guided before voting. What is perhaps more significant is that the gender gap has shrunk significantly over the years. However, there are layers and categories of women voters in India. Some women are much more likely than the average woman to follow advice. Against this backdrop, this paper investigates the variation among women voters during the national elections of 2019 in India. The central question of this research paper is whether or not the development of greater political opinion among women would offset guided voting and allow them to emerge as more independent voters. So the independent variable of the study is Indian women’s opinion on politics, and the dependent variable is their voting behavior. The methodology used in this paper is both quantitative and qualitative. This study investigated and examined Lokniti’s election survey data. The sample size used in this survey is 11568. The analysis of this study has revealed that there is a considerable impact of women having a political opinion on their voting behavior. The Bivariate analysis of the variables states that 83% of Indian women who have opinions on political issues do not seek advice while going to vote. This proves the hypothesis of this paper that women with an opinion on politics are more likely to be independent voters. To check the statistical significance of the finding, a chi-square test was done and the p-value found is 0.009737, which shows it is statistically significant. Furthermore, a regression test has been done by controlling certain variables like age, educational qualification, caste, and financial position of the women to probe the influence on the dependent variable. The findings provide worthwhile insights into the relationship between these control variables and the women voting behavior in India.

Keywords: dependent voter, independent voter, political opinion, voting behavior, women voter

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Authors: Jerry Hu

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Let G = (V, E) with V = {1, 2, ..., k} be a graph, the k positive integers a₁, a₂, ..., ak are G-wise relatively prime if (aᵢ, aⱼ ) = 1 for {i, j} ∈ E. We use an inductive approach to give an asymptotic formula for the number of k-tuples of integers that are G-wise relatively prime. An exact formula is obtained for the probability that k positive integers are G-wise relatively prime. As a corollary, we also provide an exact formula for the probability that k positive integers have exactly r relatively prime pairs.

Keywords: graph, independent set, G-wise relatively prime, probability

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Authors: Emon Chairote, Panatda Jannoey, Griangsak Chairote

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A strain of Monascus purpureus CMU001 was used to prepared red yeast rice from Thai glutinous rice Korkor 6 (RD 6). Adding of different amounts of histidine (156, 312, 625, and 1250 mg in 100 g of rice grains)) under aerobic and air limitation (air-lock) condition were used in solid fermentation. Determination of the yield as well as monacolin K content was done. Citrinin content was also determined in order to confirm the safety use of prepared red yeast rice. It was found that under air-lock condition with 1250 mg of histidine addition gave the highest yield of 37.40 g of dried red yeast rice prepared from 100 g of rice. Highest 5.72 mg content of monacolin K was obtained under air-lock condition with 312 mg histidine addition. In the other hand, citrinin content was found to be less than 24462 ng/g of all dried red yeast rice samples under the experimental methods used in this work.

Keywords: red yeast rice, Thai glutinous rice, monacolin K., citrinin

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Authors: Anna Perrone, Federico Martinelli

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Olive fruit is well-known for the high content in secondary metabolites with high interest at nutritional, nutraceutical, antioxidant, and healthy levels. The content of secondary metabolites in olive at harvest may be affected by different water regimes, with significant effects on olive oil composition and quality and, consequently, on its healthy and nutritional features. In this work, a summary of several research studies dealing with the biosynthesis of healthy and nutraceutical metabolites of the secondary metabolism in olive fruit will be reported. The phytochemical findings have been correlated with the expression of key genes involved in polyphenol, terpenoid, and carotenoid biosynthesis and metabolism in response to different development stages and water regimes. Flavonoids were highest in immature fruits, while anthocyanins increased at ripening. In epicarp tissue, this was clearly associated with an up-regulation of the UFGT gene. Olive fruits cultivated under different water regimes were analyzed by metabolomics. This method identified several hundred metabolites in the ripe mesocarp. Among them, 46 were differentially accumulated in the comparison between rain-fed and irrigated conditions. Well-known healthy metabolites were more abundant at a higher level of water regimes. Increased content of polyphenols was observed in the rain-fed fruit; particularly, anthocyanin concentration was higher at ripening. Several secondary metabolites were differentially accumulated between different irrigation conditions. These results showed that these metabolic approaches could be efficiently used to determine the effects of agronomic treatments on olive fruit physiology and, consequently, on nutritional and healthy properties of the obtained extra-virgin olive oil.

Keywords: olea europea, anthocyanins, polyphenols, water regimes

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Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis

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Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.

Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks

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