Search results for: microscopic features

Authors: Shuo Liu, Dan Liu

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In the field of named entity recognition, most of the research has been conducted around simple entities. However, for nested named entities, which still contain entities within entities, it has been difficult to identify them accurately due to their boundary ambiguity. In this paper, a hierarchical recognition model is constructed based on the grammatical structure and semantic features of Chinese text for boundary calculation based on lexical features. The analysis is carried out at different levels in terms of granularity, semantics, and lexicality, respectively, avoiding repetitive work to reduce computational effort and using the semantic features of words to calculate the boundaries of entities to improve the accuracy of the recognition work. The results of the experiments carried out on web-based microblogging data show that the model achieves an accuracy of 86.33% and an F1 value of 89.27% in recognizing nested named entities, making up for the shortcomings of some previous recognition models and improving the efficiency of recognition of nested named entities.

Keywords: coarse-grained, nested named entity, Chinese natural language processing, word embedding, T-SNE dimensionality reduction algorithm

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Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: feature generation, feature learning, genetic algorithm, music information retrieval

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Authors: Naser Safdarian, Nader Jafarnia Dabanloo

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In this paper we used four features i.e. Q-wave integral, QRS complex integral, T-wave integral and total integral as extracted feature from normal and patient ECG signals to detection and localization of myocardial infarction (MI) in left ventricle of heart. In our research we focused on detection and localization of MI in standard ECG. We use the Q-wave integral and T-wave integral because this feature is important impression in detection of MI. We used some pattern recognition method such as Artificial Neural Network (ANN) to detect and localize the MI. Because these methods have good accuracy for classification of normal and abnormal signals. We used one type of Radial Basis Function (RBF) that called Probabilistic Neural Network (PNN) because of its nonlinearity property, and used other classifier such as k-Nearest Neighbors (KNN), Multilayer Perceptron (MLP) and Naive Bayes Classification. We used PhysioNet database as our training and test data. We reached over 80% for accuracy in test data for localization and over 95% for detection of MI. Main advantages of our method are simplicity and its good accuracy. Also we can improve accuracy of classification by adding more features in this method. A simple method based on using only four features which extracted from standard ECG is presented which has good accuracy in MI localization.

Keywords: ECG signal processing, myocardial infarction, features extraction, pattern recognition

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Authors: Khader S. Al-Aidmat, Venus W. Samawi

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Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

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Authors: Chieh-Fu Chang, Wan-Hsin Hsieh

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We have proposed a novel scheme— iterative word-extension (IWE) to enhance the cliff effect of Reed-Solomon codes regarding the error performance at a specific Eb/N0. The scheme can be readily extended to block codes and the important properties of IWE are further investigated here. In order to select proper block codes specifying the desired cliff Eb/N0, the associated features of IWE are explored. These properties and features grant IWE ability to enhance security regarding the received Eb/N0 in physical layer so that IWE scheme can cooperate with the traditional presentation layer approach — cryptography, to meet the secure requirements in diverse applications. The features and feasibility of IWE scheme in satellite communication are finally discussed.

Keywords: security, IWE, cliff effect, space communications

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Authors: Vesna Kirandziska, Nevena Ackovska, Ana Madevska Bogdanova

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The problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued.

Keywords: emotion recognition, facial recognition, signal processing, machine learning

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Authors: Narmina Mammadova

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In modern linguistics, the comparative study of languages is becoming increasingly popular, the typology and comparison of languages that have different structures is expanding and deepening. Of particular interest is the study of phraseological units, which makes it possible to identify the specific features of the compared languages in all their national identity. This paper gives a brief analysis of the comparative study of somatic phraseological units (SFU) of the Spanish and Turkish languages with the component "hand" in the semantic aspect; identification of equivalents, analogs and non-equivalent units, as well as a description of methods of translation of non-equivalent somatic phraseological units. Comparative study of the phraseology of unrelated languages is of particular relevance since it allows us to identify both general, universal features and differential and specific features characteristic of a particular language. Based on the results of the generalization of the study, it can be assumed that phraseological units containing a somatic component have a high interlingual phraseological activity, which contributes to an increase in the degree of interlingual equivalence.

Keywords: Linguoculturology, Turkish, Spanish, language picture of the world, phraseological units, semantic microfield

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Authors: Jessemyn Modiini, Timothy Lynar, Elena Sitnikova

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We present a novel enhanced compartmental model for malware spread analysis in cyber security. This paper applies cyber security data features to epidemiological compartmental models to model the infectious potential of malware. Compartmental models are most efficient for calculating the infectious potential of a disease. In this paper, we discuss and profile epidemiologically relevant data features from a Domain Name System (DNS) dataset. We then apply these features to epidemiological compartmental models to network traffic features. This paper demonstrates how epidemiological principles can be applied to the novel analysis of key cybersecurity behaviours and trends and provides insight into threat modelling above that of kill-chain analysis. In applying deterministic compartmental models to a cyber security use case, the authors analyse the deficiencies and provide an enhanced stochastic model for cyber epidemiology. This enhanced compartmental model (SUEICRN model) is contrasted with the traditional SEIR model to demonstrate its efficacy.

Keywords: cybersecurity, epidemiology, cyber epidemiology, malware

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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Authors: Ritesh K. Shukla

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Degradation of biological samples in terms of macromolecules (DNA, RNA, and protein) are the major challenges in the forensic investigation which misleads the result interpretation. Currently, there are no precise methods available to circumvent this problem. Therefore, at the preliminary level, some methods are urgently needed to solve this issue. In this order, Comet assay is one of the most versatile, rapid and sensitive molecular biology technique to assess the DNA degradation. This technique helps to assess DNA degradation even at very low amount of sample. Moreover, the expedient part of this method does not require any additional process of DNA extraction and isolation during DNA degradation assessment. Samples directly embedded on agarose pre-coated microscopic slide and electrophoresis perform on the same slide after lysis step. After electrophoresis microscopic slide stained by DNA binding dye and observed under fluorescent microscope equipped with Komet software. With the help of this technique extent of DNA degradation can be assessed which can help to screen the sample before DNA fingerprinting, whether it is appropriate for DNA analysis or not. This technique not only helps to assess degradation of DNA but many other challenges in forensic investigation such as time since deposition estimation of biological fluids, repair of genetic material from degraded biological sample and early time since death estimation could also be resolved. With the help of this study, an attempt was made to explore the application of well-known molecular biology technique that is Comet assay in the field of forensic science. This assay will open avenue in the field of forensic research and development.

Keywords: comet assay, DNA degradation, forensic, molecular biology

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Authors: Anita, Sari Septiani Tangke, Rusdina Bte Ladju, Nasrum Massi

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New diagnostic tools are urgently needed to interrupt the transmission of tuberculosis and multidrug-resistant tuberculosis. The microscopic-observation drug-susceptibility (MODS) assay is a rapid, accurate and simple liquid culture method to detect multidrug-resistant tuberculosis (MDR-TB). MODS were evaluated to determine a lower and same concentration of isoniazid and rifampin for detection of MDR-TB. Direct drug-susceptibility testing was performed with the use of the MODS assay. Drug-sensitive control strains were tested daily. The drug concentrations that used for both isoniazid and rifampin were at the same concentration: 0.16, 0.08 and 0.04μg per milliliter. We tested 56 M. tuberculosis clinical isolates and the control strains M. tuberculosis H37RV. All concentration showed same result. Of 53 M. tuberculosis clinical isolates, 14 were MDR-TB, 38 were susceptible with isoniazid and rifampin, 1 was resistant with isoniazid only. Drug-susceptibility testing was performed with the use of the proportion method using Mycobacteria Growth Indicator Tube (MGIT) system as reference. The result of MODS assay using lower concentration was significance (P<0.001) compare with the reference methods. A lower and same concentration of isoniazid and rifampin can be used to detect MDR-TB. Operational cost and application can be more efficient and easier in resource-limited environments. However, additional studies evaluating the MODS using lower and same concentration of isoniazid and rifampin must be conducted with a larger number of clinical isolates.

Keywords: isoniazid, MODS assay, MDR-TB, rifampin

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Authors: Michael Steve Lopez Bernabe

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Political news coverage of tabloid sheets as one of the print media molds or influences public opinions and perceptions. In this study, Critical Discourse Analysis was employed to 30 political news taken from major tabloid sheets in the Philippines in order to determine the linguistics features and other features characterizing the political news in tabloids such as discursive styles, news topics or contexts, journalistic roles and news sources. The political underpinnings through framing were also explored in the study. The results revealed that the linguistics features of the news coverage include moods and modalities (morphology), passivity and transitivity, nominalization, appositives and embedding (syntax), and pre-modifications, the use of verbs and omissions (grammatical features). The discursive features were direct or indirect speech; cohesion; endophora and classifications. In terms of news sources were politicians, experts, and journalists; and the tabloid perform the journalistic roles such as an intervention, watchdog, loyal-facilitator, service, infotainment and civic. The news was also evident of different political underpinnings such as game or strategic framing, conflict framing, human interest framing, attrition of responsibility framing, morality framing, economic consequences framing and issue framing.

Keywords: critical discourse analysis, political news, applied linguistics, Philippines, tabloid sheets

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Authors: Chady El Hachem, Pan Ye, Kamilia Abahri, Rachid Bennacer

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Considered as a building construction material, and regarding its environmental benefits, wood fiber insulation is the material of interest in this work. The definition of adequate elementary representative volume that guarantees reliable understanding of the hygrothermal macroscopic phenomena is very critical. At the microscopic scale, when subjected to hygric solicitations, fibers undergo local dimensionless variations. It is therefore necessary to master this behavior, which affects the global response of the material. This study consists of an experimental procedure using the non-destructive method, X-ray tomography, followed by morphological post-processing analysis using ImageJ software. A refine investigation took place in order to identify the representative elementary volume and the sufficient resolution for accurate structural analysis. The second part of this work was to evaluate the microscopic hygric behavior of the studied material. Many parameters were taken into consideration, like the evolution of the fiber diameters, distribution along the sorption cycle and the porosity, and the water content evolution. In addition, heat transfer simulations based on the energy equation resolution were achieved on the real structure. Further, the problematic of representative elementary volume was elaborated for such heterogeneous material. Moreover, the material’s porosity and its fibers’ thicknesses show very big correlation with the water content. These results provide the literature with very good understanding of wood fiber insulation’s behavior.

Keywords: hygric behavior, morphological characterization, wood fiber insulation material, x-ray tomography

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Authors: K. Subermaniam, Q. H. M. Saad, S. N. A. Bakhtiar, J. A. Hamid, F. Z .J. Sidek, F. Othman

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Objective: To investigate the effects of virgin coconut oil (VCO) on histomorphometric changes in the aorta and heart of thermoxidized palm oil-fed rats. Methods: Thirty two male Sprague-Dawley rats were divided into four groups: control group fed with normal diet; 5 times heated palm oil-fed group (5HPO) fortified with 15% w/w of 5HPO; VCO group supplemented with 1.42 ml/kg of VCO; and 5HPO + VCO group. The treatment lasted for four months. Upon sacrifice, aortic and heart tissues were processed for light microscopic studies. Results: Light microscopic studies showed thickened intima and media of the aorta in two out of eight rats in the 5HPO group only, while the rest of the rats did not show any thickening of either the intima or media of the aorta. Intima media area (IMA) in the VCO, 5HPO and 5HPO+VCO was significantly increased compared to the control group. Circumferential wall tension (CWT) and tensile stress (TS) in the aorta of 5HPO showed significant increase compared to the other groups. Cardiomyofibre width in 5HPO group showed significant increase in size compared to the control, VCO and 5HPO+VCO groups. Cardiomyofibre nuclear size in the 5HPO group decreased in size significantly compared to the control, VCO and 5HPO+VCO groups. Conclusion: VCO supplementation at a dose of 1.42 ml/kg showed protectives effect on the aorta and heart of thermoxidized palm oil fed rats.

Keywords: aorta, heart, histomorphometric changes, thermoxidized palm oil, virgin coconut oil

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Authors: Shameel Pervez, Saad Aziz Durrani, Ibatsam Khokhar

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Pectinase is an enzyme that breaks down pectin, a compound responsible for structural integrity of the plant. Pectin is difficult to break down mechanically and the cost is very high, that is why many industries including food industries use pectinase enzyme produced by microbes for pectin breakdown. Apple (Malus domestica) is an important fruit in terms of market value. Every year, millions of apples are wasted due to post-harvest rot caused by fungi. Fungi are natural decomposers of our ecosystem and are infamous for post-harvest rot of apple fruit but at the same time they are prized for their high production of valuable extracellular enzymes such as pectinase. In this study, fungi belonging to different genus were isolated from rotten apples. Rotten samples of apple were picked from different markets of Lahore. After surface sterilization, the rotten parts were cut into small pieces and placed onto MEA media plates for three days. Afterwards, distinct colonies were picked and purified by sub-culturing. The isolates were identified to genus level through the study of basic colony morphology and microscopic features. The isolates were then subjected to screening for pectinase activity on MS media to compare pectinase production and were then subsequently tested for pathogenic activity through wound suspension method to evaluate the pathogenic activity of isolates in comparison with their pectinolytic activity. A total of twelve fungal strains were isolates from rotten apples. They were belonging to genus Penicillium, Alternaria, Paecilomyces and Rhizopus. Upon screening for pectinolytic activity, isolates Pen 1, Pen 4, and Rz showed high pectinolytic activity and were further subjected to DNA isolation and partial sequencing for species identification. The results of partial sequencing were combined with in-depth study of morphological features revealing Pen 1 as Penicillium janthinellum, Pen 4 as Penicillium griseofulvum, and Rz as Rhizopus microsporus. Pathogenic activity of all twelve isolates was evaluated. Penicillium spp. were highly pathogenic and destructive and same was the case with Paecilomyces sp. and Rhizopus sp. However, Alternaria spp. were found to be more consistent in their pathogenic activity, on all types of apples.

Keywords: apple, pectinase, fungal pathogens, penicillium, rhizopus

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

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

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

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Authors: Skiker Kaoutar, Mounir Maouene

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

Keywords: nouns, features, network, category specificity

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Authors: Ayad Dalloo, Sulaf Dalloo

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

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

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

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

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

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Authors: Vladimíra Kňazovická, Mária Dovičičová, Miroslava Kačániová, Margita Čanigová

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The aim of the study was to test the storage of bee pollen at room temperature and in cold store, and to describe microorganisms originated from it. Fresh bee pollen originating in West Slovakia was collected in May 2010. It was tested for presence of particular microbial groups using dilution plating method, and divided into two parts with different storage (in cold store and at room temperature). Microbial analyses of pollen were repeated after one year of storage. Several bacterial strains were isolated and tested using Gram staining, for catalase and fructose-6-phosphate-phosphoketolase presence, and by rapid ID 32A (BioMérieux, France). Micromycetes were identified at genus level. Fresh pollen contained coliform bacteria, which were not detected after one year of storage in both ways. Total plate count (TPC) of aerobes and anaerobes and of yeasts in fresh bee pollen exceeded 5.00 log CFU/g. TPC of aerobes and anaerobes decreased below 2.00 log CFU/g after one year of storage in both ways. Count of yeasts decreased to 2.32 log CFU/g (at room temperature) and to 3.66 log CFU/g (in cold store). Microscopic filamentous fungi decreased from 3.41 log CFU/g (fresh bee pollen) to 1.13 log CFU/g (at room temperature) and to 1.89 log CFU/g (in cold store). In fresh bee pollen, 12 genera of micromycetes were identified in the following order according to their relative density: Penicillium > Mucor > Absidia > Cladosporium, Fusarium > Alternaria > Eurotium > Aspergillus, Rhizopus > Emericella > Arthrinium and Mycelium sterilium. After one year at room temperature, only three genera were detected in bee pollen (Penicillium > Aspergillus, Mucor) and after one year in cold store, seven genera were detected (Mucor > Penicillium, Emericella > Aspergillus, Absidia > Arthrinium, Eurotium). From the plates designated for anaerobes, eight colonies originating in fresh bee pollen were isolated. Among them, a single yeast isolate occurred. Other isolates were G+ bacteria, with a total of five rod shaped. In three out of these five, catalase was absent and fructose-6-phosphate-phosphoketolase was present. Bacterial isolates originating in fresh pollen belonged probably to genus Bifidobacterium or relative genera, but their identity was not confirmed unequivocally. In general, cold conditions are suitable for maintaining the natural properties of foodstuffs for a longer time. Slight decrease of microscopic fungal number and diversity was recorded in cold temperatures compared with storage at room temperature.

Keywords: bacteria, bee product, microscopic fungi, biosystems engineering

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Authors: Jeevan Jyoti, Bhanu Pratap Singh, S. R. Dhakate

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In the present study, multiwalled carbon nanotubes (MWCNTs) and reduced graphene oxide (RGO) were synthesized by chemical vapor deposition and Improved Hummer’s method, respectively and their composite with acrylonitrile butadiene styrene (ABS) were prepared by twin screw co rotating extrusion technique. The electromagnetic interference (EMI) shielding effectiveness of graphene oxide carbon nanotube (GCNTs) hybrid composites was investigated and the results were compared with EMI shielding of carbon nanotube (CNTs) and reduced graphene oxide (RGO) in the frequency range of 12.4-18 GHz (Ku-band). The experimental results indicate that the EMI shielding effectiveness of these composites is achieved up to –21 dB for 10 wt. % loading of GCNT loading. The mechanism of improvement in EMI shielding effectiveness is discussed by resolving their contribution in absorption and reflection loss. The main reason for such a high improved shielding effectiveness has been attributed to the significant improvement in the electrical conductivity of the composites. The electrical conductivity of these GCNT/ABS composites was increased from 10-13 S/cm to 10-7 S/cm showing the improvement of the 6 order of the magnitude. Scanning electron microscopic (SEM) and high resolution transmission electron microscopic (HRTEM) studies showed that the GCNTs were uniformly dispersed in the ABS polymer matrix. GCNTs form a network throughout the polymer matrix and promote the reinforcement.

Keywords: ABS, EMI shielding, multiwalled carbon nanotubes, reduced graphene oxide, graphene, oxide-carbon nanotube (GCNTs), twin screw extruder, multiwall carbon nanotube, electrical conductivity

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Authors: Priti S. Tidke, Chandragouda R. Patil

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The present study was designed to investigate the effect of Magnesia phosphorica, a biochemical medicine on urine screeing, biochemical, histopathological, and electron microscopic images in ethylene glycol induced nepholithiasis in rats.Male Wistar albino rats were divided into six groups and were orally administered saline once daily (IR-sham and IR-control) or Magnesia phosphorica 100 mg/kg twice daily for 24 days.The effect of various dilutions of biochemical Mag phos3x, 6x, 30x was determined on urine output by comparing the urine volume collected by keeping individual animals in metabolic cages. Calcium oxalate urolithiasis and hyperoxaluria in male Wistar rats was induced by oral administration of 0.75% Ethylene glycol p.o. daily for 24 days. Simultaneous administration of biochemical 3x, 6x, 30xMag phos (100mg/kg p.o. twice a day) along with ethylene glycol significantly decreased calcium oxalate, urea, creatinine, Calcium, Magnesium, Chloride, Phosphorus, Albumin, Alkaline Phosphatase content in urine compared with vehicle-treated control group.After the completion of treatment period animals were sacrificed, kidneys were removed and subjected to microscopic examination for possible stone formation. Histological estimation of kidney treated with biochemical Mag phos (3x, 6x, 30xMag phos 100 mg/kg, p.o.) along with ethylene glycol inhibited the growth of calculi and reduced the number of stones in kidney compared with control group. Biochemical Mag phos of 3x dilution and its crude equivalent also showed potent diuretic and antiurolithiatic activity in ethylene glycol induced urolithiasis. A significant decrease in the weight of stones was observed after treatment in animals which received biochemical Mag phos of 3x dilution and its crude equivalent in comparison with control groups. From this study, it can be proposed that the 3x dilution of biochemical Mag phos exhibits a significant inhibitory effect on crystal growth, with the improvement of kidney function and substantiates claims on the biological activity of twelve tissue remedies which can be proved scientifically through laboratory animal studies.

Keywords: Mag phos, Magnesia phosphorica, ciochemic medicine, urolithiasis, kidney stone, ethylene glycol

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Authors: Saeid Eshghi, Neeraj Saxena, Abdulmajeed Alsultan

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Carbon dioxide (CO₂) alongside other gas emissions in the atmosphere cause a greenhouse effect, resulting in an increase of the average temperature of the planet. Transportation vehicles are among the main contributors of CO₂ emission. Stationary vehicles with initiated motors produce more emissions than mobile ones. Intersections with traffic lights that force the vehicles to become stationary for a period of time produce more CO₂ pollution than other parts of the road. This paper focuses on analyzing the CO₂ produced by the traffic flow at Anzac Parade Road - Barker Street intersection in Sydney, Australia, before and after the implementation of Light rail transport (LRT). The data are gathered during the construction phase of the LRT by collecting the number of vehicles on each path of the intersection for 15 minutes during the evening rush hour of 1 week (6-7 pm, July 04-31, 2018) and then multiplied by 4 to calculate the flow of vehicles in 1 hour. For analyzing the data, the microscopic simulation software “VISSIM” has been used. Through the analysis, the traffic flow was processed in three stages: before and after implementation of light rail train, and one during the construction phase. Finally, the traffic results were input into another software called “EnViVer”, to calculate the amount of CO₂ during 1 h. The results showed that after the implementation of the light rail, CO₂ will drop by a minimum of 13%. This finding provides an evidence that light rail is a sustainable mode of transport.

Keywords: carbon dioxide, emission modeling, light rail, microscopic model, traffic flow

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

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

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

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Authors: Rita Darmayanti

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

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

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

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

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

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Authors: Dennis Okora Amima Ondieki

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Fertility transition has been identified to be affected by numerous factors. This research aimed to investigate the most real factors affecting fertility transition in Kenya. These factors were firstly extracted from the literature convened into demographic features, social, and economic features, social-cultural features, reproductive features and modernization features. All these factors had 23 factors identified for this study. The data for this study was from the Kenya Demographic and Health Surveys (KDHS) conducted in 1999-2003 and 2003-2008/9. The data was continuous, and it involved the mean birth order for the ten periods. Principal component analysis (PCA) was utilized using 23 factors. Principal component analysis conveyed religion, region, education and marital status as the real factors. PC scores were calculated for every point. The identified principal components were utilized as forecasters in the multiple regression model, with the fertility level as the response variable. The four components were found to be affecting fertility transition differently. It was found that fertility is affected positively by factors of region and marital and negatively by factors of religion and education. These four factors can be considered in the planning policy in Kenya and Africa at large.

Keywords: fertility transition, principal component analysis, Kenya demographic health survey, birth order

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Authors: P. S. Jagadeesh Kumar, Yang Yung, Wenli Hu

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Speech emotion classification is a dominant research field in finding a sturdy and profligate classifier appropriate for different real-life applications. This effort accentuates on classifying different emotions from speech signal quarried from the features related to pitch, formants, energy contours, jitter, shimmer, spectral, perceptual and temporal features. Tensor deep stacking neural networks were supported to examine the factors that influence the classification success rate. Facial electromyography signals were composed of several forms of focuses in a controlled atmosphere by means of audio-visual stimuli. Proficient facial electromyography signals were pre-processed using moving average filter, and a set of arithmetical features were excavated. Extracted features were mapped into consistent emotions using bilinear mapping. With facial electromyography signals, a database comprising diverse emotions will be exposed with a suitable fine-tuning of features and training data. A success rate of 92% can be attained deprived of increasing the system connivance and the computation time for sorting diverse emotional states.

Keywords: speech emotion classification, tensor deep stacking neural networks, facial electromyography, bilinear mapping, audio-visual stimuli

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Authors: Tatiana V. Raudina, Sergey P. Kulizhskiy

Abstract:

A large part of Russia is located in permafrost areas. These areas are widely used because there are concentrated valuable natural resources. Therefore to explore of cryosols it is important due to the significant increase of anthropogenic stress as well as the problem of global climate change. In the north of Western Siberia permafrost phenomena is widespread. Permafrost as a factor of soil formation and cryogenesis as a process have a great impact on the soil formation of these areas. Based on the research results of permafrost-affected soils tundra landscapes formed in the central part of the Tazovskiy Peninsula in cryogenic conditions, data were obtained which characterize the morphological features of soils. The specificity of soil cover distribution and manifestation of soil-forming processes within the study area are noted. Permafrost features such as frost cracking, cryoturbation, thixotropy, movement of humus are formed. The formation of these features is increased with the development of the territory. As a consequence, there is a change in the components of the environment and the destruction of the soil cover.

Keywords: gleyed and nongleyed soils, permafrost, soil cryogenesis (pedocryogenesis), soil-forming macroprocesses

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Authors: M. Fayez Al Homsi, Reem Al Homsi

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Renal disease is a major cause of morbidity and mortality. Glomerular diseases make a small portion of the renal disease. Lupus glomerulonephritis (GN) is the commonest among the GN of systemic diseases. More than a hundred and eighty-eight consecutive renal biopsies are performed and evaluated for clinically suspected glomerular diseases over a period of two years. As in a standard practice after receiving the ultrasound-guided renal biopsies, the fresh biopsy is divided to three parts, one part is frozen for immunofluorescence evaluation, the second part is placed in 4% glutaraldehyde for electron microscopic evaluation, and the third part is placed in 10% buffered formalin for light microscopic evaluation. Primary glomerular diseases are detected in 83 biopsies; glomerulonephritis (GN) of systemic diseases are identified in 88, glomerular lesions in vascular diseases in 3, glomerular lesions in metabolic diseases in 7, hereditary nephropathies in 2, end-stage kidney in 2, and glomerular lesions in transplantation in 3 biopsies. Among the primary lesions, focal segmental glomerulosclerosis (28) and mesangial proliferative GN (26) were the most common. Lupus GN (67) and Ig A nephropathy (20) were the most common of the GN of systemic diseases. Lupus nephritis biopsies included one biopsy diagnosed as class 1 (normal), 17 biopsies class 2 (mesangial proliferation), 5 biopsies class 3 (focal proliferative GN), 39 biopsies class 4 diffuse proliferative GN), 3 biopsies class 5 (membranous GN), and 2 biopsies class 6 (crescentic GN). Lupus GN is the most common among GN of systemic diseases. While diabetes is very common here, diabetic GN (3 biopsies) is not as common as might one expects. Most likely this is due to sampling and reluctance on part of nephrologists and patients in sampling the kidney in diabetes mellitus.

Keywords: diabetes, glomerulonephritis, lupus, mesangial proliferation, nephropathy

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