Search results for: sentence extraction

Authors: Vaibhav V. Dixit, Shubham Ajay Karwa

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Diabetic foot ulcers speak to a critical medical problem. Right now, clinicians and medical caretakers primarily construct their injury evaluation in light of visual examination of wound size and mending status, while the patients themselves rarely have a chance to play a dynamic part. Henceforth, love quantitative and practical examination technique that empowers the patients and their parental figures to take a more dynamic part in every day wound care possibly can quicken wound recuperating, spare travel cost and diminish human services costs. Considering the commonness of cell phones with a high-determination computerized camera, evaluating wounds by breaking down pictures of ceaseless foot ulcers is an alluring choice. In this paper, we propose a novel injury picture examination framework actualized using feature extraction and color segmentation. Here we are using the Normalized minimum distance classifier for classifying the output.

Keywords: diabetic, Gabor wavelet, normalized minimum distance classifier, quantiable parameters

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Authors: Jarek Krajewski, Andre Wittenborn, Martin Sauerland

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This abstract describes a promising approach for estimating post-traumatic stress disorder (PTSD) based on prosodic speech characteristics. It illustrates the validity of this method by briefly discussing results from an Arabic refugee sample (N= 47, 32 m, 15 f). A well-established standardized self-report scale “Reaction of Adolescents to Traumatic Stress” (RATS) was used to determine the ground truth level of PTSD. The speech material was prompted by telling about autobiographical related sadness inducing experiences (sampling rate 16 kHz, 8 bit resolution). In order to investigate PTSD-induced speech changes, a self-developed set of 136 prosodic speech features was extracted from the .wav files. This set was adapted to capture traumatization related speech phenomena. An artificial neural network (ANN) machine learning model was applied to determine the PTSD level and reached a correlation of r = .37. These results indicate that our classifiers can achieve similar results to those seen in speech-based stress research.

Keywords: speech prosody, PTSD, machine learning, feature extraction

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Authors: J. Marie Hicks

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The art of the poetic conjoins meaning and symbolism with imagery and rhythm. Perhaps the reader might read this opening sentence as 'The art of the poetic combines meaning and symbolism with imagery and rhythm,' which holds a similar message, but is not quite the same. The reader understands that these factors are combined in this literary form, but to gain a sense of the conjoining of these factors, the reader is forced to consider that these aspects of poetry are not simply combined, but actually adjoin, abut, skirt, or touch in the poetic form. This alternative word choice is an example of substitutional inference. Poetry is, ostensibly, a literary form where language is used precisely or creatively to evoke specific images or emotions for the reader. Often, the reader can predict a coming rhyme or descriptive word choice in a poem, based on previous rhyming pattern or earlier imagery in the poem. However, there are instances when the poet uses an unexpected word choice to create multiple meanings and connections. In these cases, the reader is presented with an unusual phrase or image, requiring that they think about what that image is meant to suggest, and their mind also suggests the word they expected, creating a second, overlying image or meaning. This is what is meant by the term 'substitutional inference.' This is different than simply using a double entendre, a word or phrase that has two meanings, often one complementary and the other disparaging, or one that is innocuous and the other suggestive. In substitutional inference, the poet utilizes an unanticipated word that is either visually or phonetically similar to the expected word, provoking the reader to work to understand the poetic phrase as written, while unconsciously incorporating the meaning of the line as anticipated. In other words, by virtue of a word substitution, an inference of the logical word choice is imparted to the reader, while they are seeking to rationalize the word that was actually used. There is a substitutional inference of meaning created by the alternate word choice. For example, Louise Bogan, 4th Poet Laureate of the United States, used substitutional inference in the form of homonyms, malapropisms, and other unusual word choices in a number of her poems, lending depth and greater complexity, while actively engaging her readers intellectually with her poetry. Substitutional inference not only adds complexity to the potential interpretations of Bogan’s poetry, as well as the poetry of others, but provided a method for writers to infuse additional meanings into their work, thus expressing more information in a compact format. Additionally, this nuancing enriches the poetic experience for the reader, who can enjoy the poem superficially as written, or on a deeper level exploring gradations of meaning.

Keywords: poetic inference, poetic word play, substitutional inference, word substitution

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Authors: Lee Myung-Won, Kwak Keun-Chang

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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.

Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation

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Authors: Rajkumar Ghosh

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Water scarcity is a significant challenge in urban areas, even in smart cities (Lucknow, Bangalore, Jaipur, etc.) where efficient resource management is prioritized. The depletion of groundwater resources in Gomti Nagar, Lucknow, Uttar Pradesh, India is particularly severe, posing a significant challenge for sustainable development in the region. This study focuses on addressing the water shortage by investigating the effectiveness of rooftop rainwater harvesting systems (RTRWHs) as a sustainable approach to bridge the gap between groundwater recharge and extraction. The aim of this study is to assess the effectiveness of RTRWHs in reducing aquifer depletion and addressing the water scarcity issue in the Gomti Nagar region. The research methodology involves the utilization of RTRWHs as the primary method for collecting rainwater. RTRWHs will be implemented in residential and commercial buildings to maximize the collection of rainwater. Data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. Statistical analysis and modelling techniques were employed to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. The study reveals that the installation of RTRWHs in the Gomti Nagar region has a positive impact on addressing the water scarcity issue. Currently, RTRWHs cover only a small percentage of the total rainfall collected in the region. However, when RTRWHs are installed in all buildings, their influence on increasing water availability and reducing aquifer depletion will be significantly greater. The study also highlights the significant water imbalance in the region, emphasizing the urgent need for sustainable water management practices. This research contributes to the theoretical understanding of sustainable water management systems in smart cities. By highlighting the effectiveness of RTRWHs in reducing aquifer depletion, it emphasizes the importance of implementing such systems in urban areas. Data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. The collected data were then analysed using statistical analysis and modelling techniques to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. The findings of this study demonstrate that the implementation of RTRWHs can effectively mitigate the water scarcity crisis in Gomti Nagar. By reducing aquifer depletion and bridging the gap between groundwater recharge and extraction, RTRWHs offer a sustainable solution to the region's water scarcity challenges. Widespread adoption of RTRWHs in all buildings and integration into urban planning and development processes are crucial for efficient water management in smart cities like Gomti Nagar. These findings can serve as a basis for policymakers, urban planners, and developers to prioritize and incentivize the installation of RTRWHs as a potential solution to the water shortage crisis.

Keywords: water scarcity, urban areas, smart cities, resource management, groundwater depletion, rooftop rainwater harvesting systems, sustainable development, sustainable water management, mitigating water scarcity

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Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Wu Yufeng, Gu Yifan, Wang Hengguang, Gongyu, Zuo Tieyong

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Indium is one the scarce resources which can be only used less than 30 years, and more than 70% of the indium is used for the production of the LCD. The benefit of recycling Indium from waste LCD is large. Take the LCD-TV for example, the yield of which was close to 90 million units in 2010. If it was available to recycle the indium effectively, the yield of the secondary-indium could reach up to 110 metric ton, which accounted for one third of the primary indium production in China. And compared with the dispersion and long process extraction of the primary indium resources, secondary indium concentrates in the waste LCD, the exploitation has great economic and environmental benefits. However, the potential benefits were indefinite, resulting in China’s government did not pay enough attention to the indium recycling industry. In our study, an estimation model was constructed to analyze the potential of the indium in the waste LCD. The different types of LCD were detected to find out the content of indium. Then, the potential of the indium in the waste LCD was estimated in China. Furthermore, the pollution emissions of the product process of the primary and secondary indium was analyzed respectively to calculate the economic and environmental benefits of the indium recycling from the waste LCD in China.

Keywords: indium recycling, waste liquid crystal displays, benefits, China

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Authors: Ruomeng Xiao, Zhulin Zong, Longfa Yang

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Aiming at the problem that the target signal is difficult to detect under the strong ground clutter environment, this paper proposes a clutter suppression algorithm based on the combination of singular value decomposition and the Mallat fast wavelet algorithm. The method first carries out singular value decomposition on the radar echo data matrix, realizes the initial separation of target and clutter through the threshold processing of singular value, and then carries out wavelet decomposition on the echo data to find out the target location, and adopts the discard method to select the appropriate decomposition layer to reconstruct the target signal, which ensures the minimum loss of target information while suppressing the clutter. After the verification of the measured data, the method has a significant effect on the target extraction under low SCR, and the target reconstruction can be realized without the prior position information of the target and the method also has a certain enhancement on the output SCR compared with the traditional single wavelet processing method.

Keywords: clutter suppression, singular value decomposition, wavelet transform, Mallat algorithm, low SCR

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Authors: K. Fellah, H. Benmehdi, A. Amrouche, H. Malainine, F. Memmou, H. Dalile, W. Siata

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This work aims to evaluate the antioxidant of flavonoids extracted from the leaves of Prunus persica L. A phytochemical screening allowed us to highlight the different phytochemicals present in the leaves of the studied plant. The selective extraction of flavonoids gave yields of 0.71, 1.5, and 4.8% for the fractions ethyl ether, ethyl acetate and n- butanol, respectively. The reading of the antioxidant activity of different extracts of flavonoids by HPLTC method revealed positive reaction (yellow spots) on the TLC plates sprayed with DPPH. Using the DPPH method, the fractions of flavonoids (bunanol, ethyl acetate and Diethyl ether) showed a potent scavenging activity with IC50 = 0.22; 0.27 and 0.76 mg / ml, respectively. Furthermore, our findings revealed the extracts under study exhibited higher reducing potential which depends upon extract concentration. These results obtained from this investigation confirm that the Prunus persica remains a major resource of bioactive molecules.

Keywords: Prunus persica L., phytochemical study, flavonoids, antioxidant activity, TLC bioautographic, FRAP, DPPH

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Authors: Janine Just, Kerstin Meints

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The research aims to compare vocabulary size and grammatical development between US American English- and British English-speaking children at age 2;0. As there is evidence that precocious children with large vocabularies develop grammar skills earlier than their typically developing peers, it was investigated if this also holds true across varieties of English. Thus, if US American children start to produce words earlier than their British counterparts, this could mean that US children are also at an advantage in the early developmental stages of acquiring grammar. This research employs a British English adaptation of the MacArthur-Bates CDI Words and Sentences (Lincoln Toddler CDI) to compare vocabulary and also grammar scores with the updated US Toddler CDI norms. At first, the Lincoln TCDI was assessed for its concurrent validity with the Preschool Language Scale (PLS-5 UK). This showed high correlations for the vocabulary and grammar subscales between the tests. In addition, the frequency of the Toddler CDI’s words was also compared using American and British English corpora of adult spoken and written language. A paired-samples t-test found a significant difference in word frequency between the British and the American CDI demonstrating that the TCDI’s words were indeed of higher frequency in British English. We then compared language and grammar scores between US (N = 135) and British children (N = 96). A two-way between groups ANOVA examined if the two samples differed in terms of SES (i.e. maternal education) by investigating the impact of SES and country on vocabulary and sentence complexity. The two samples did not differ in terms of maternal education as the interaction effects between SES and country were not significant. In most cases, scores were not significantly different between US and British children, for example, for overall word production and most grammatical subscales (i.e. use of words, over- regularizations, complex sentences, word combinations). However, in-depth analysis showed that US children were significantly better than British children at using some noun categories (i.e. people, objects, places) and several categories marking early grammatical development (i.e. pronouns, prepositions, quantifiers, helping words). However, the effect sizes were small. Significant differences for grammar were found for irregular word forms and progressive tense suffixes. US children were more advanced in their use of these grammatical categories, but the effect sizes were small. In sum, while differences exist in terms of vocabulary and grammar ability, favouring US children, effect sizes were small. It can be concluded that most British children are ‘catching up’ with their US American peers at age 2;0. Implications of this research will be discussed.

Keywords: first language acquisition, grammar, parent report instrument, vocabulary

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Authors: E. Younsi, H. Andriamboavonjy, A. David, S. Dokou, B. Lemrabet

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Software and time optimization are very important factors in financial markets, which are competitive fields, and emergence of new computer tools further stresses the challenge. In this context, any improvement of technical indicators which generate a buy or sell signal is a major issue. Thus, many tools have been created to make them more effective. This worry about efficiency has been leading in present paper to seek best (and most innovative) way giving largest improvement in these indicators. The approach consists in attaching a signature to frequent market configurations by application of frequent patterns extraction method which is here most appropriate to optimize investment strategies. The goal of proposed trading algorithm is to find most accurate signatures using back testing procedure applied to technical indicators for improving their performance. The problem is then to determine the signatures which, combined with an indicator, outperform this indicator alone. To do this, the FP-Tree algorithm has been preferred, as it appears to be the most efficient algorithm to perform this task.

Keywords: quantitative analysis, back-testing, computational models, apriori algorithm, pattern recognition, data mining, FP-tree

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Authors: Hanan Moawad, Naglaa M. Abd EL-Rahman

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Erwinia carotovora var. carotovora is the main cause of soft rot in potatoes. Hyphaene thebaica was studied for biocontrol of E. carotovora which inhibited growth of E. carotovora on solid medium, a comparative study of classical and ultrasound-assisted extractions of Hyphaene thebaica fruit. The use of ultrasound decreased significant the total time of treatment and increase the total amount of crude extract. The crude extract was subjected to determine the in vitro, by a bioassay technique revealed that the treatment of paper disks with ultrasound extraction of Hyphaene thebaica reduced the growth of pathogen and produced inhibition zones up to 38mm in diameter. The antioxidant activity of ultrasound-ethanolic extract of Doum fruits (Hyphaene thebaica) was determined. Data obtained showed that the extract contains the secondary metabolites such as Tannins, Saponin, Flavonoids, Phenols, Steroids, Terpenoids, Glycosides and Alkaloids.

Keywords: ultrasound, classical extract, biological control, Erwinia carotovora, Hyphaene thebaica

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Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

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The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

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Authors: Navab Karimi, Tohid Alizadeh

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An intelligent vision-based system was designed to measure the quality and purity of raisins. A machine vision setup was utilized to capture the images of bulk raisins in ranges of 5-50% mixed pure-impure berries. The textural features of bulk raisins were extracted using Grey-level Histograms, Co-occurrence Matrix, and Local Binary Pattern (a total of 108 features). Genetic Algorithm and neural network regression were used for selecting and ranking the best features (21 features). As a result, the GLCM features set was found to have the highest accuracy (92.4%) among the other sets. Followingly, multiple feature combinations of the previous stage were fed into the second regression (linear regression) to increase accuracy, wherein a combination of 16 features was found to be the optimum. Finally, a Support Vector Machine (SVM) classifier was used to differentiate the mixtures, producing the best efficiency and accuracy of 96.2% and 97.35%, respectively.

Keywords: sun-dried organic raisin, genetic algorithm, feature extraction, ann regression, linear regression, support vector machine, south azerbaijan.

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Authors: Juliane P. De Oliveira, Carlos H. Dos Santos, Marcia Shoji, Maria E. C. Ferreira, Natalia U. Yamaguchi

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The construction sector is considered a major generator of environmental impacts due to the high consumption of natural resources and waste generation. Thus, this article aims to evaluate the performance of a concrete produced by the partial and total replacement of natural coarse aggregate by recycled coarse aggregate, derived from the concrete residue of buildings and demolitions. The study was made by comparing the compressive strength and absorption of three different concrete traces, keeping the water/cement factor of 0.60 and changing only the proportions of recycled coarse aggregate between 0%, 50% and 100%. Traces 50% and 100% obtained good results by comparing the actual specific mass, because the material used is lighter to the natural coarse aggregate. It was concluded that the concrete produced with recycled aggregates, even with inferior results, can be used where it is not needed a structural function, giving an adequate destination to the construction and demolition waste and consequently reducing the extraction and consumption of natural resources.

Keywords: green concrete, recycled aggregate, recycling, sustainable development

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Authors: Binger Lu

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It remains unclear whether second language (L2) speakers could use discourse context cues to predict upcoming information as native speakers do during online comprehension. Some researchers propose that L2 learners may have a reduced ability to generate predictions during discourse processing. At the same time, there is evidence that discourse-level cues are weighed more heavily in L2 processing than in L1. Previous studies showed that L1 prediction is sensitive to the global validity of predictive cues. The current study aims to explore whether and to what extent L2 learners can dynamically and strategically adjust their prediction in accord with the global validity of predictive cues in L2 discourse comprehension as native speakers do. In a self-paced reading experiment, Chinese native speakers (N=128), C-E bilinguals (N=128), and English native speakers (N=128) read high-predictable (e.g., Jimmy felt thirsty after running. He wanted to get some water from the refrigerator.) and low-predictable (e.g., Jimmy felt sick this morning. He wanted to get some water from the refrigerator.) discourses in two-sentence frames. The global validity of predictive cues was manipulated by varying the ratio of predictable (e.g., Bill stood at the door. He opened it with the key.) and unpredictable fillers (e.g., Bill stood at the door. He opened it with the card.), such that across conditions, the predictability of the final word of the fillers ranged from 100% to 0%. The dependent variable was reading time on the critical region (the target word and the following word), analyzed with linear mixed-effects models in R. C-E bilinguals showed reliable prediction across all validity conditions (β = -35.6 ms, SE = 7.74, t = -4.601, p< .001), and Chinese native speakers showed significant effect (β = -93.5 ms, SE = 7.82, t = -11.956, p< .001) in two of the four validity conditions (namely, the High-validity and MedLow conditions, where fillers ended with predictable words in 100% and 25% cases respectively), whereas English native speakers didn’t predict at all (β = -2.78 ms, SE = 7.60, t = -.365, p = .715). There was neither main effect (χ^²(3) = .256, p = .968) nor interaction (Predictability: Background: Validity, χ^²(3) = 1.229, p = .746; Predictability: Validity, χ^²(3) = 2.520, p = .472; Background: Validity, χ^²(3) = 1.281, p = .734) of Validity with speaker groups. The results suggest that prediction occurs in L2 discourse processing but to a much less extent in L1, witha significant effect in some conditions of L1 Chinese and anull effect in L1 English processing, consistent with the view that L2 speakers are more sensitive to discourse cues compared with L1 speakers. Additionally, the pattern of L1 and L2 predictive processing was not affected by the global validity of predictive cues. C-E bilinguals’ predictive processing could be partly transferred from their L1, as prior research showed that discourse information played a more significant role in L1 Chinese processing.

Keywords: bilingualism, discourse processing, global validity, prediction, self-paced reading

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Authors: Ali Abdrhman M. Ukasha

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Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression-salt- peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption

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Authors: Adenike Boyo Olasunkanmi Kesinro, Henry Boyo, Surukite Oluwole

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Utilizing solar energy in producing electricity can minimize environmental pollution generated by fossil fuel in producing electricity. Our research was base on the extraction of dye from Roystonea regia fruit by using methanol as solvent. The dye extracts were used as sensitizers in Dye-sensitized solar cell (DSSCs). Study was done on the electrical properties from the extracts of Roystonea regia fruit as Dye-sensitized solar cell (DSSCs). The absorptions of the extracts and extracts with dye were determined at different wavelengths (350-1000nm). Absorption peak was observed at 1.339 at wavelength 400nm. The obtained values for methanol extract Roystonea regia extract are, Imp = 0.015mA, Vmp = 12.0mV, fill factor = 0.763, Isc= 0.018 mA and Voc = 13.1 mV and efficiency of 0.32%. .The phytochemical screening was taken and it was observed that Roystonea regia extract contained less of anthocyanin compared to flavonoids. The nanostructured dye sensitized solar cell (DSSC) will provide economically credible alternative to present day silicon p–n junction photovoltaic.

Keywords: methanol, ethanol, titanium dioxide, roystonea regia fruit, dye-sensitized solar cell

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Authors: Salmin K. Alshalmani, Nada H. Zobi, Ismaeel H. Bozakouk

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Marine organisms are potentially prolific sources of highly bio active secondary metabolites that might represent useful leads in the development of new pharmaceutical agents. The Libyan marine biodiversity including macroalgae remains partially unexplored in term of their potential bio activities. The phytochemical analysis of the alcoholic extracts of some commonly occurring seaweed Cystoseira compressa, enteromorpha intestinals, corallina, and Ulva lactuca and their evaluated for antibacterial activity by well diffusion assay were studied. Four different solvents namely water, ethanol 99 %, methanol 99 %, and methylated spirit 95 % were used for extraction. The phytochemical analysis revealed the presence of carbohydrates, steroids, tannin & phenols, saponins, proteins, and glycosides. The extracts were subjected for study of antibacterial activity. The zone of inhibition ranged between 8 to 16 mm in aqueous extract and up to 16 mm in methanol extract. The maximum activity (16 mm) was recorded from methanol extract of Ulva lactuca against Staphylococcus aureus and, minimum activity (8mm) recorded by Cystoseira compressa against S. aureus.

Keywords: macroalgae, phytochemicals, antibacterial activity, methanolic extract

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Authors: Rohaya Abdul Wahab, Raja Mohd Fuad Tengku Aziz, Nazaliza Othman, Sharifah Saleh, Nabihah Razali, Muhammad Al Baqir Zinal Abidin, Md Hanif Md Nasir

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This paper will discuss how we optimize our physical verification flow in our IC Design Department having various rule decks from multiple foundries. Our ultimate goal is to achieve faster time to tape-out and avoid schedule delay. Currently the physical verification runtimes and memory usage have drastically increased with the increasing number of design rules, design complexity and the size of the chips to be verified. To manage design violations, we use a number of solutions to reduce the amount of violations needed to be checked by physical verification engineers. The most important functions in physical verifications are DRC (design rule check), LVS (layout vs. schematic) and XRC (extraction). Since we have a multiple number of foundries for our design tape-outs, we need a flow that improve the overall turnaround time and ease of use of the physical verification process. The demand for fast turnaround time is even more critical since the physical design is the last stage before sending the layout to the foundries.

Keywords: physical verification, DRC, LVS, XRC, flow, foundry, runset

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Authors: Mariam Khaled, Noha Farag, Ghada Mohamed Abdel Salam, Khaled Abu-Aisha, Mohamed El-Azizi

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Gastric and colorectal cancers are among the most frequent causes of cancer-associated mortalities in Africa. They have been considered as a global public health concern, as nearly one million new cases are reported per year. IL-1β is a pro-inflammatory cytokine-produced by activated macrophages and monocytes- and a member of the IL-1 family. The inactive IL-1β precursor is cleaved and activated by caspase-1 enzyme, which itself is activated by the assembly of intracellular structures defined as NLRP3 (Nod Like receptor P3) inflammasomes. Activated IL-1β stimulates the Interleukin-1 receptor type-1 (IL-1R1), which is responsible for the initiation of a signal transduction pathway leading to cell proliferation. It has been proven that the IL-1β gene is a highly polymorphic gene in which single nucleotide polymorphisms (SNPs) may affect its expression. It has been previously reported that SNPs including base transitions between C and T at positions, -511 (C-T; dbSNP: rs16944) and -31 (C-T; dbSNP: rs1143627), from the transcriptional start site, contribute to the pathogenesis of gastric and colorectal cancers by affecting IL-1β levels. Altered production of IL-1β due to such polymorphisms is suspected to stimulate an amplified inflammatory response and promote Epithelial Mesenchymal Transition leading to malignancy. Allele frequency distribution of the IL-1β-31 and -511 SNPs, in different populations, and their correlation to the incidence of gastric and colorectal cancers, has been intriguing to researchers worldwide. The current study aims to investigate allele distributions of the IL-1β SNPs among gastric and colorectal cancers Egyptian patients. In order to achieve to that, 89 Biopsy and surgical specimens from the antrum and corpus mucosa of chronic gastritis subjects and gastric and colorectal carcinoma patients was collected for DNA extraction followed by restriction fragment length polymorphism polymerase chain reaction (RFLP-PCR). The amplified PCR products of IL-1β-31C > T and IL-1β-511T > C were digested by incubation with the restriction endonuclease enzymes ALu1 and Ava1. Statistical analysis was carried out to determine the allele frequency distribution in the three studied groups. Also, the effect of the IL-1β -31 and -511 SNPs on nuclear factor binding was analyzed using Fluorescence Electrophoretic Mobility Shift Assay (EMSA), preceded by nuclear factor extraction from gastric and colorectal tissue samples and LPS stimulated monocytes. The results of this study showed that a significantly higher percentage of Egyptian gastric cancer patients have a homozygous CC genotype at the IL-1β-31 position and a heterozygous TC genotype at the IL-1β-511 position. Moreover, a significantly higher percentage of the colorectal cancer patients have a homozygous CC genotype at the IL-1β-31 and -511 positions as compared to the control group. In addition, the EMSA results showed that IL-1β-31C/T and IL-1β-511T/C SNPs do not affect nuclear factor binding. Results of this study suggest that the IL-1β-31 C/T and IL-1β-511 T/C may be correlated to the incidence of gastric cancer in Egyptian patients; however, similar findings couldn’t be proven in the colorectal cancer patients group for the IL-1β-511 T/C SNP. This is the first study to investigate IL-1β -31 and -511 SNPs in the Egyptian population.

Keywords: colorectal cancer, Egyptian patients, gastric cancer, interleukin-1β, single nucleotide polymorphisms

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Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.

Abstract:

Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.

Keywords: image processing, python, convolution neural network (CNN), machine learning

Procedia PDF Downloads 70

Authors: Ali A. Ukasha

Abstract:

Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression, salt and peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption

Procedia PDF Downloads 490

Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

Abstract:

Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

Procedia PDF Downloads 454

Authors: M. Heysem Arslan, Ikilem Gocek, U. Kivanc Sahin

Abstract:

Natural dyestuff, extracted from Juglans Regia L., a kind of walnut, was used to dye 100% cotton gabardine fabric. The main goal of this study was to enhance dyeing process of cotton fabric with Juglans Regia L. dyestuff in terms of color fastness values by designing and developing a mordant application process. Within the context of this study, different mordants such as tannic acid, gallic acid, ascorbic acid, potassium sodium tartrate tetrahydrate, calcium carbonate, iron (II) sulphate heptahydrate, aluminum potassium sulphate dodecahydrate and their combinations were applied in the mordanting processes. Spectrophotometric analysis, color fastness to washing and color fastness to light tests were carried out on the fabric samples. In this study, it was shown that by using the right combination of mordants with a proper application process, it is possible to improve color fastness values of cotton fabric samples dyed with natural dyestuff.

Keywords: extraction, Juglans Regia L., mordanting process, natural dyestuff

Procedia PDF Downloads 300

Authors: T. Nalowa, L. Foncha, S. Eposi

Abstract:

Prostate enlargement, prostate cancer are major global health problems affecting many men as they advance in age. It is highly recommended to encourage older men to get Prostate Specific Antigen test screening frequently. Conventional treatments like radiation, chemotherapy are associated with many side effects. And this situation is a call for concern. Traditional medicine is affordable, easily prepared with little or no side effects and it contains many phytochemicals. The study aims to find the cure for prostate cancer and prostate enlargement by extracting products from plant tissues of specific herbs to determine anti-inflammatory, anti-cancer, and anti-hematuria properties. Descriptive statistical analysis was applied to describe the data process. The commonly used method of preparation was extraction. Overall, 40 patients were classified based on their medical conditions on their underlying user report. Rural communities in Fako are rich sources of plants with medicinal properties. The used plants consequently provide basic information and aid to investigate the cure of prostate cancer and prostate enlargement, with great significance.

Keywords: cancer, enlargement, metastases, prostate

Procedia PDF Downloads 64

Authors: Fadilah Fadilah, Rochmadi Rochmadi, Siti Syamsiah, Djagal W. Marseno

Abstract:

Glucomannan can be found in the tuber of porang together with starch and proteinaceous components which were regarded as impurities. An enzymatic process for obtaining higher glucomannan content from Porang flour have been conducted. Papain was used for hydrolysing proteinaceous components in Porang flour which was conducted after a simultaneous extraction of glucomannan and enzymatic starch hydrolysis. Three variables affecting the rate were studied, i.e. temperature, the amount of enzyme and the stirring speed. The ninhydrin method was used to determine degree of protein hydrolysis. Results showed that the rising of degree of hydrolysis were fast in the first ten minutes of the reaction and then proceeded slowly afterward. The optimum temperature for hydrolysis was 60 ^oC. Increasing the amount of enzyme showed a remarkable effect to degree of hydrolysis, but the stirring speed had no significant effect. This indicated that the reaction controlled the rate of hydrolysis.

Keywords: degree of hydrolysis, ninhydrin, papain, porang flour, proteinaceous components

Procedia PDF Downloads 242

Authors: Yu Hung Chiang, Hei Chia Wang

Abstract:

Nowadays, tourism has become a part of life. Before reserving hotels, customers need some information, which the most important source is online reviews, about hotels to help them make decisions. Due to the dramatic growing of online reviews, it is impossible for tourists to read all reviews manually. Therefore, designing an automatic review analysis system, which summarizes reviews, is necessary for them. The main purpose of the system is to understand the opinion of reviews, which may be positive or negative. In other words, the system would analyze whether the customers who visited the hotel like it or not. Using sentiment analysis methods will help the system achieve the purpose. In sentiment analysis methods, the targets of opinion (here they are called the feature) should be recognized to clarify the polarity of the opinion because polarity of the opinion may be ambiguous. Hence, the study proposes an unsupervised method using Part-Of-Speech pattern and multi-lexicons sentiment analysis to summarize all reviews. We expect this method can help customers search what they want information as well as make decisions efficiently.

Keywords: text mining, sentiment analysis, product feature extraction, multi-lexicons

Procedia PDF Downloads 326

Authors: Ximena Castillo, Jaime Pizarro

Abstract:

This research describes the development of a very cheap mesoporous silica material similar to hexagonal mesoporous silica (HMS) and using a silicate extract as precursor. This precursor is obtained from cheap fly ash by an easy calcination process at 850 °C and a green extraction with water. The obtained mesoporous fly ash material had a surface area of 282 m2 g-1 and a pore size of 5.7 nm. It was functionalized with ethylene diamino moieties via the well-known SAMMS method, followed by a DRIFT analysis that clearly showed the successful functionalization. An excellent adsorbent was obtained for the adsorption of sulfate anions by the solid’s modification with copper forming a copper-ethylenediamine complex. The adsorption of sulfates was studied in a batch system ( experimental conditions: pH=8.0; 5 min). The kinetics data were adjusted according to a pseudo-second order model with a high coefficient of linear regression at different initial concentrations. The adsorption isotherm that best fitted the experimental data was the Freundlich model. The maximum sulfate adsorption capacity of this very cheap fly ash based adsorbent was 146.1 mg g-1, 3 times greater than the values reported in literature and commercial adsorbent materials.

Keywords: fly ash, mesoporous materials, SAMMS, sulfate

Procedia PDF Downloads 169