Search results for: self-learning methods

Authors: Mehdi Ghatei, Masoomeh Lorestani

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Upstream Tailings Storage Facilities (TSFs) may experience slope instabilities due to soil liquefaction, especially in regions known to be seismically active. In this study, liquefaction susceptibility of an upstream-raised TSF in Western Australia was assessed using two different approaches. The first approach assessed liquefaction susceptibility using Cone Penetration Tests with pore pressure measurement (CPTu) as described by the National Centre for Earthquake Engineering Research (NCEER). This assessment was based on the four CPTu tests that were conducted on the perimeter embankment of the TSF. The second approach used the Finite Element (FE) method with application of an equivalent linear model to predict the undrained cyclic behavior, the pore water pressure and the liquefaction of the materials. The tailings parameters were estimated from the CPTu profiles and from the laboratory tests. The cyclic parameters were estimated from the literature where test results of similar material were available. The results showed that there was a good agreement, in the liquefaction susceptibility of the tailings material, between the NCEER and FE methods with equivalent linear model.

Keywords: liquefaction , CPTU, NCEER, finite element method, equivalent linear model

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Authors: M. O. Bayram, H. B. Gencdal, N. O. Fercan, B. Basbug

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Liquid limit, which is used as a measure of soil strength, can be detected by Casagrande and fall-cone testing methods. The two methods majorly diverge from each other in terms of operator dependency. The Casagrande method that is applied according to ASTM D4318-17 standards may give misleading results, especially if the calibration process is not performed well. To reveal the effect of calibration for drop height and amount of soil paste placement in the Casagrande cup, a series of tests were carried out by multipoint method as it is specified in the ASTM standards. The tests include the combination of 6 mm, 8 mm, 10 mm, and 12 mm drop heights and under-filled, half-filled, and full-filled Casagrande cups by kaolinite samples. It was observed that during successive tests, the drop height of the cup deteriorated; hence the device was recalibrated before and after each test to provide the accuracy of the results. Besides, the tests by under-filled and full-filled samples for higher drop heights revealed lower liquid limit values than the lower drop heights revealed. For the half-filled samples, it was clearly seen that the liquid limit values didn’t change at all as the drop height increased, and this explains the function of standard specifications.

Keywords: calibration, casagrande cup method, drop height, kaolinite, liquid limit, placing form

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Authors: Ganfeng Yu, Yuefeng Ma, Shanliang Yang

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The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work.

Keywords: text information retrieval, natural language processing, new word discovery, information extraction

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Authors: Wenjie Wu, Peng Cheng, Zehua Zhang, Fei Luo, Feng Wu, Min Zhong, Jianzhong Xu

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Background: There has been limited research into the therapeutic efficacy of rapid diagnosis of spinal tuberculosis complicated with pulmonary tuberculosis. We attempted to discover whether the utilization of a DNA microarray assay to detect multidrug-resistant spinal tuberculosis complicated with pulmonary tuberculosis can improve clinical outcomes. Methods: A prospective study was conducted from February 2006 to September 2015. One hundred and forty-three consecutive culture–confirmed, clinically and imaging diagnosed MDR-TB patients with spinal tuberculosis complicated by pulmonary tuberculosis were enrolled into the study. The initial time to treatment for MDR-TB, the method of infection control, radiological indicators of spinal tubercular infectious foci, culture conversion, and adverse drug reactions were compared with the standard culture methods. Results: Of the total of 143 MDR-TB patients, 68 (47.6%) were diagnosed by conventional culture methods and 75 (52.4%) following the implementation of detection using the DNA microarray. Patients in the microarray group began rational use of the second-line drugs schedule more speedily than sufferers in the culture group (17.3 vs. 74.1 days). Among patients were admitted to a general tuberculosis ward, those from the microarray group spent less time in the ward than those from the culture group (7.8 vs. 49.2 days). In those patients with six months follow-up (n=134), patients in the microarray group had a higher rate of sputum negativity conversion at six months (89% vs. 73%). In the microarray group, the rate of drug adverse reactions was significantly lower (22.2% vs. 67.7%). At the same time, they had a more obvious reduction of the area with spinal tuberculous lesions in radiological examinations (77% vs. 108%). Conclusions: The application of the CapitalBio™ DNA Microarray assay caused noteworthy clinical advances including an earlier time to begin MDR-TB treatment, increased sputum culture conversion, improved infection control measures and better radiographical results

Keywords: tuberculosis, multidrug-resistant, tuberculous spondylitis, DNA microarray, clinical outcomes

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Authors: A. Fettahoglu

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Theory of viscoelasticity is used by many researchers to represent behavior of many materials such as pavements on roads or bridges. Several researches used analytical methods and rheology to predict the material behaviors of simple models. Today, more complex engineering structures are analyzed using Finite Element Method, in which material behavior is embedded by means of three dimensional viscoelastic material laws. As a result, structures of unordinary geometry and domain like pavements of bridges can be analyzed by means of Finite Element Method and three dimensional viscoelastic equations. In the scope of this study, rheological models embedded in ANSYS, namely, generalized Maxwell elements and Prony series, which are two methods used by ANSYS to represent viscoelastic material behavior, are presented explicitly. Subsequently, a practical problem, which has an analytical solution given in literature, is used to verify the applicability of viscoelasticity tool embedded in ANSYS. Finally, amount of error in the results of ANSYS is compared with the analytical results to indicate the influence of used method and time step size.

Keywords: generalized Maxwell model, finite element method, prony series, time step size, viscoelasticity

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Authors: Arsalan Jabbar, Wajiha Javed, Nelofer Mehboob, Zahid Memon

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Introduction: There are multiple social, individual and cultural factors that influence an individual’s decision to adopt family planning methods especially among non-users in patriarchal societies like Pakistan.Non-users, if targeted efficiently, can contribute significantly to country’s CPR. A research study showed that non-users if convinced to adopt lactational amenorrhea method can shift to long-term methods in future. Research shows that if non-users are targeted efficiently a 59% reduction in unintended pregnancies in Saharan Africa and South-Central and South-East Asia is anticipated. Methods: We did secondary data analysis on Pakistan Demographic Heath Survey (2012-13) dataset. Use of contraception (never-use/ever-use) was the outcome variable. At univariate level Chi-square/Fisher Exact test was used to assess relationship of baseline covariates with contraception use. Then variables to be incorporated in the model were checked for multi-collinearity, confounding, and interaction. Then binary logistic regression (with an urban-rural stratification) was done to find the relationship between contraception use and baseline demographic and social variables. Results: The multivariate analyses of the study showed that younger women (≤ 29 years) were more prone to be never users as compared to those who were > 30 years and this trend was seen in urban areas (AOR 1.92, CI 1.453-2.536) as well as rural areas (AOR 1.809, CI 1.421-2.303). While looking at regional variation, women from urban Sindh (AOR 1.548, CI 1.142-2.099) and urban Balochistan (AOR 2.403, CI 1.504-3.839) had more never users as compared to other urban regions. Women in the rich wealth quintile were more never users and this was seen both in urban and rural localities (urban (AOR 1.106 CI .753-1.624); rural areas (AOR 1.162, CI .887-1.524)) even though these were not statistically significant. Women idealizing more children(> 4) are more never users as compared to those idealizing less children in both urban (AOR 1.854, CI 1.275-2.697) and rural areas (AOR 2.101, CI 1.514-2.916). Women who never lost a pregnancy were more inclined to be non-users in rural areas (AOR 1.394, CI 1.127-1.723) .Women familiar with only traditional or no method had more never users in rural areas (AOR 1.717, CI 1.127-1.723) but in urban areas it wasn’t significant. Women unaware of Lady Health Worker’s presence in their area were more never users especially in rural areas (AOR 1.276, CI 1.014-1.607). Women who did not visit any care provider were more never users (urban (AOR 11.738, CI 9.112-15.121) rural areas (AOR 7.832, CI 6.243-9.826)). Discussion/Conclusion: This study concluded that government, policy makers and private sector family planning programs should focus on the untapped pool of never users (younger women from underserved provinces, in higher wealth quintiles, who desire more children.). We need to make sure to cover catchment areas where there are less LHWs and less providers as ignorance to modern methods and never been visited by an LHW are important determinants of never use. This all is in sync with previous literate from similar developing countries.

Keywords: contraception, demographic and health survey, family planning, never users

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Authors: Kimberley Kennedy

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The major findings of this study discuss the importance of understanding and applying Systems thinking concepts to ensure an effective Project-Based Learning environment. A pilot project study of a major pedagogical change was conducted over a five year period with the goal to give students real world, hands-on learning experiences and the opportunity to apply what they had learned over the past two years of their business program. The first two weeks of the fifteen week semester utilized teaching methods of lectures, guest speakers and design thinking workshops to prepare students for the project work. For the remaining thirteen weeks of the semester, the students worked with actual business owners and clients on projects and challenges. The first three years of the five year study focused on student feedback to ensure a quality learning experience and continuous improvement process was developed. The final two years of the study, examined the conceptual understanding and perception of learning and teaching by faculty using Project-Based Learning pedagogy as compared to lectures and more traditional teaching methods was performed. Relevant literature was reviewed and data collected from program faculty participants who completed pre-and post-semester interviews and surveys over a two year period. Systems thinking concepts were applied to better understand the challenges for faculty using Project-Based Learning pedagogy as compared to more traditional teaching methods. Factors such as instructor and student fatigue, motivation, quality of work and enthusiasm were explored to better understand how to provide faculty with effective support and resources when using Project-Based Learning pedagogy as the main teaching method. This study provides value by presenting generalizable, foundational knowledge by offering suggestions for practical solutions to assure student and teacher engagement in Project-Based Learning courses.

Keywords: continuous improvement, project-based learning, systems thinking, teacher engagement

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Authors: Auteleyeva Laura, Maikanov Balgabai, Smagulova Ayana

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In order to find and select detoxification methods, patent and information research was conducted, as a result of which 68 patents for inventions were found, among them from the near abroad - 14 (Russia), from far abroad: China – 27, USA - 6, South Korea–1, Germany - 2, Mexico – 4, Yugoslavia – 7, Austria, Taiwan, Belarus, Denmark, Italy, Japan, Canada for 1 security document. Aflatoxin B₁ in various nuts was determined by two methods: enzyme immunoassay "RIDASCREEN ® FAST Aflatoxin" with determination of optical density on a microplate spectrophotometer RIDA®ABSORPTION 96 with RIDASOFT® software Win.NET (Germany) and the method of high-performance liquid chromatography (HPLC Corporation Water, USA) according to GOST 307112001. For experimental contamination of nuts, the cultivation of strain A was carried out. flavus KWIK-STIK on the medium of Chapek (France) with subsequent infection of various nuts (peanuts, peanuts with shells, badam, walnuts with and without shells, pistachios).Based on our research, we have selected 2 detoxification methods: method 1 – combined (5% citric acid solution + microwave for 640 W for 3 min + UV for 20 min) and a chemical method with various leaves of plants: Artemisia terra-albae, Thymus vulgaris, Callogonum affilium, collected in the territory of Akmola region (Artemisia terra-albae, Thymus vulgaris) and Western Kazakhstan (Callogonum affilium). The first stage was the production of ethanol extracts of Artemisia terraea-albae, Thymus vulgaris, Callogonum affilium. To obtain them, 100 g of vegetable raw materials were taken, which was dissolved in 70% ethyl alcohol. Extraction was carried out for 2 hours at the boiling point of the solvent with a reverse refrigerator using an ultrasonic bath "Sapphire". The obtained extracts were evaporated on a rotary evaporator IKA RV 10. At the second stage, the three samples obtained were tested for antimicrobial and antifungal activity. Extracts of Thymus vulgaris and Callogonum affilium showed high antimicrobial and antifungal activity. Artemisia terraea-albae extract showed high antimicrobial activity and low antifungal activity. When testing method 1, it was found that in the first and third experimental groups there was a decrease in the concentration of aflatoxin B1 in walnut samples by 63 and 65%, respectively, but these values also exceeded the maximum permissible concentrations, while the nuts in the second and third experimental groups had a tart lemon flavor; When testing method 2, a decrease in the concentration of aflatoxin B1 to a safe level was observed by 91% (0.0038 mg/kg) in nuts of the 1st and 2nd experimental groups (Artemisia terra-albae, Thymus vulgaris), while in samples of the 2nd and 3rd experimental groups, a decrease in the amount of aflatoxin in 1 to a safe level was observed.

Keywords: nuts, aflatoxin B1, my, mycotoxins

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Authors: B. Waked Najar

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Since the spread of Covid- 19, Israel and other countries suffer from lockdowns and social distance, which impose different kinds of restrictions. On the one side, many organization closed and unemployment increased, bringing about economic problems and distress. On the other side, family ties were damaged due to inability to sustain close relations with some family members and too frequent interactions with others. Unfortunately, conflicts within families, controlling behavior and domestic violence appear more often. Purpose: to examine the phenomenon of domestic violence and its expansion during the Covid-19 crisis, to propose and classify strategies of dealing with it, including encouragement of public systems providing more information and support to domestic violence victims. Methodology: the author strives to reveal methods of supporting domestic violence victims through public and private treatment organizations. The author interviewed battered women and families who experienced violence during the Covid-19 crisis. Findings: victims of domestic violence often feel isolated and helpless. It is a real challenge to track and support them, especially in the traditional minorities’ communities. Research limitations: Many families refused to be interviewed because they did not want to be exposed to the community, especially religious families. Originality: research is aimed to examine a phenomenon of domestic violence during the Covid-19 crisis and methods of help and support the victims, which is not a common theme of research during the pandemic.

Keywords: violence, coronavirus, domestic violence, influence

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Authors: Tayyab Hassan, Talha Rehman, Qasim Abdul Aziz, Ahmad Salman

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The constant monitoring of blood glucose level is necessary for maintaining health of patients and to alert medical specialists to take preemptive measures before the onset of any complication as a result of diabetes. The current clinical monitoring of blood glucose uses invasive methods repeatedly which are uncomfortable and may result in infections in diabetic patients. Several attempts have been made to develop non-invasive techniques for blood glucose measurement. In this regard, the existing methods are not reliable and are less accurate. Other approaches claiming high accuracy have not been tested on extended dataset, and thus, results are not statistically significant. It is a well-known fact that acetone concentration in breath has a direct relation with blood glucose level. In this paper, we have developed the first of its kind, reliable and high accuracy breath analyzer for non-invasive blood glucose measurement. The acetone concentration in breath was measured using MQ 138 sensor in the samples collected from local hospitals in Pakistan involving one hundred patients. The blood glucose levels of these patients are determined using conventional invasive clinical method. We propose a linear regression classifier that is trained to map breath acetone level to the collected blood glucose level achieving high accuracy.

Keywords: blood glucose level, breath acetone concentration, diabetes, linear regression

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Authors: Dzatur Rizqi Fathienah Syarifuddin, Isharyah Sunarno, Eddy Hartono, Siti Maisuri T. Chalid

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Introduction: The potential impact of coronavirus disease 2019 (COVID-19) on the health of expectant mothers and fetuses has strained attention. Pregnant women are considered a vulnerable category to respiratory infections. Moreover, several inflammatory cytokines are 2-100 times more abundant in COVID-19 with cytokine storms than in normal individuals; interleukin 6 (IL-6) exhibits much higher elevations. Investigating potential relationships between IL-6 serum levels and the severity of COVID-19 symptoms in pregnant women is the aim of this study. Material and Methods: Sixty-two eligible pregnant women were divided into a positive COVID-19 group (n=31) and a negative COVID-19 group (n=31) in this cross-sectional study. The research subjects were selected using consecutive sampling. The IL-6 was measured from a vein blood specimen using ELISA methods. Results: The COVID-19 positive group had a higher median IL-6 serum level (45.35 (35.15- 153.99) vs. 38.86 ± 11.43 (15.02-59.52), p=0.03) than the negative group. On the other hand, the IL-6 serum level had comparable value according to the COVID-19 symptoms severity (88.35 ± 36.14 ng/mL vs. 51.09 ± 25.48 ng/mL vs. 56.02 ± 33.20 ng/mL in moderate symptoms, mild symptoms, and asymptomatic, respectively; p=0.152). Conclusion: Although the IL-6 serum levels are not related to COVID-19 symptoms severity, an elevated of this biomarker was found in pregnant women with affected diagnoses.

Keywords: interleukin-6, pregnancy, COVID-19, several inflammatory

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Authors: Hen Friman, Alex Schechter, Yeshayahu Nitzan, Rivka Cahan

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The treatment of aromatic hydrocarbons in wastewater resulting from oil spills and chemical manufactories is becoming a key concern in many modern countries. Benzene, ethylbenzene, toluene and xylene (BETX) contaminate groundwater as well as soil. These compounds have an acute effect on human health and are known to be carcinogenic. Conventional removal of these toxic materials involves separation and burning of the wastes, however, the cost of chemical treatment is very high and energy consuming. Bioremediation methods for removal of toxic organic compounds constitute an attractive alternative to the conventional chemical or physical techniques. Bioremediation methods use microorganisms to reduce the concentration and toxicity of various chemical pollutants Toluene is biodegradable both aerobically and anaerobically, it can be growth inhibitory to microorganisms at elevated concentrations, even to those species that can use it as a substrate. In this research culture of Pseudomonas putida was grown in bath bio-reactor (BBR) with toluene 100 mg/l as a single carbon source under constant voltage of 125 mV, 250 mV and 500 mV. The culture grown in BBR reached to 0.8 OD660nm while the control culture that grown without external voltage reached only to 0.6 OD660nm. The residual toluene concentration after 147 h, in the BBR operated under external voltage (125 mV) was 22 % on average, while in the control BBR it was 81 % on average.

Keywords: bioremediation, aromatic hydrocarbons, BETX, toluene, pseudomonas putida

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Authors: Levi Corallo

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Typed language made by humans on computers and cell phones has made a significant distinction from previous modes of written language exchanges. While acronyms remain one of the most predominant markings of typed language, another and perhaps more recent revolution in the way humans communicate has been with the use of symbols or glyphs, primarily Emojis—globally introduced on the iPhone keyboard by Apple in 2008. This paper seeks to analyze the use of symbols in typed communication from both a linguistic and machine learning perspective. The Unicode system will be explored and methods of encoding will be juxtaposed with the current machine and human perception. Topics in how typed symbol usage exists in conversation will be explored as well as topics across current research methods dealing with Emojis like sentiment analysis, predictive text models, and so on. This study proposes that sequential analysis is a significant feature for analyzing unicode characters in a corpus with machine learning. Current models that are trying to learn or translate the meaning of Emojis should be starting to learn using bi- and tri-grams of Emoji, as well as observing the relationship between combinations of different Emoji in tandem. The sociolinguistics of an entire new vernacular of language referred to here as ‘typed language’ will also be delineated across my analysis with unicode glyphs from both a semantic and technical perspective.

Keywords: unicode, text symbols, emojis, glyphs, communication

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Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

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Authors: Pranjali Avinash Yadav-Deshmukh

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Remarkable development of the Internet along with the new technological innovation, such as high-speed systems and affordable large storage space have led to a tremendous increase in the amount and accessibility to digital records. For any person, studying of all these data is tremendously time intensive, so there is a great need to access effective multi-document summarization (MDS) systems, which can successfully reduce details found in several records into a short, understandable summary or conclusion. For semantic representation of textual details in ontology area, as a theoretical design, our system provides a significant structure. The stability of using the ontology in fixing multi-document summarization problems in the sector of catastrophe control is finding its recommended design. Saliency ranking is usually allocated to each phrase and phrases are rated according to the ranking, then the top rated phrases are chosen as the conclusion. With regards to the conclusion quality, wide tests on a selection of media announcements are appropriate for “Jammu Kashmir Overflow in 2014” records. Ontology centered multi-document summarization methods using “NLP centered extraction” outshine other baselines. Our participation in recommended component is to implement the details removal methods (NLP) to enhance the results.

Keywords: disaster management, extraction technique, k-means, multi-document summarization, NLP, ontology, sentence extraction

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Authors: Tamara Matevosyan

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In this globalized world, intercultural communication is becoming essential for understanding communication among people, for developing understanding of cultures, to appreciate the opportunities and challenges that each culture presents to people. Moreover, it plays an important role in developing an ideal personification to understand different behaviors in different cultures. Native speakers assimilate sociolinguistic knowledge in natural conditions, while it is a great problem for language learners, and in this context feature films reveal cultural peculiarities and involve students in real communication. As we know nowadays the key role of language learning is the development of intercultural competence as communicating with someone from a different cultural background can be exciting and scary, frustrating and enlightening. Intercultural competence is important in FL learning classroom and here feature films can perform as essential tools to develop this competence and overcome the intercultural gap that foreign students face. Current proposal attempts to reveal the correlation of the given culture and language through feature films. To ensure qualified, well-organized and practical classes on Intercultural Communication for language learners a number of methods connected with movie watching have been implemented. All the pre-watching, while watching and post-watching methods and techniques are aimed at developing students’ communicative competence. The application of such activities as Climax, Role-play, Interactive Language, Daily Life helps to reveal and overcome mistakes of cultural and pragmatic character. All the above-mentioned activities are directed at the assimilation of the language vocabulary with special reference to the given culture. The study dwells into the essence of culture as one of the core concepts of intercultural communication. Sometimes culture is not a priority in the process of language learning which leads to further misunderstandings in real life communication. The application of various methods and techniques with feature films aims at developing students’ cultural competence, their understanding of norms and values of individual cultures. Thus, feature film activities will enable learners to enlarge their knowledge of the particular culture and develop a fundamental insight into intercultural communication.

Keywords: climax, intercultural competence, interactive language, role-play

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Authors: M. Kislu Noman, Syed Mohammed Shamsul Islam, Shahriar Hassan, Raihana Pervin

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With the increasing rate of wireless devices and high bandwidth operations, wireless networking and communications are becoming over crowded. To cope with such crowdy and messy situation, massive MIMO is designed to work with hundreds of low costs serving antennas at a time as well as improve the spectral efficiency at the same time. TDD has been used for gaining beamforming which is a major part of massive MIMO, to gain its best improvement to transmit and receive pilot sequences. All the benefits are only possible if the channel state information or channel estimation is gained properly. The common methods to estimate channel matrix used so far is LS, MMSE and a linear version of MMSE also proposed in many research works. We have optimized these methods using genetic algorithm to minimize the mean squared error and finding the best channel matrix from existing algorithms with less computational complexity. Our simulation result has shown that the use of GA worked beautifully on existing algorithms in a Rayleigh slow fading channel and existence of Additive White Gaussian Noise. We found that the GA optimized LS is better than existing algorithms as GA provides optimal result in some few iterations in terms of MSE with respect to SNR and computational complexity.

Keywords: channel estimation, LMMSE, LS, MIMO, MMSE

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Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

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With gravity load reduction in the structural and non-structural components, the lightweight construction will be achieved as well as the improvement of efficiency and functional specifications. The advantages of lightweight construction can be examined in two levels. The first is the mass reduction of load bearing structure which results in increasing internal useful space and the other one is the mass reduction of building which decreases the effects of seismic load as a result. In order to achieve this goal, the essential building materials specifications and also optimum load bearing geometry of structural systems and elements have to be considered, so lightweight materials selection particularly with lightweight aggregate for building components will be the first step of lightweight construction. In the next step, in addition to selecting the prominent samples of Iran's traditional architecture, the process of these works improvement is analyzed through the viewpoints of structural efficiency and lightweighting and also the practical methods of lightweight construction have been extracted. The optimum design of load bearing geometry of structural system has to be considered not only in the structural system elements, but also in their composition and the selection of dimensions, proportions, forms and optimum orientations, can lead to get a maximum materials efficiency for loads and stresses bearing.

Keywords: gravity load, lightweighting structural system, load bearing geometry, seismic behavior

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Authors: Clinton Chidiebere Anyanwu

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Secondary education is a vital part of a virtuous circle of economic growth within the context of a globalised knowledge economy. The teaching of Business Education entails teaching learners the essentials, rudiments, assumptions, and methods of business. Hence, it was deemed necessary for the study to investigate technology integration in Business Education. Drawing from the theoretical frameworks of technological pedagogical content knowledge (TPACK), and unified theory of acceptance and use of technology (UTAUT), the study observes teachers’ level of technology use in Business Education classrooms. Using a mixed-methods sequential explanatory design, probability, and purposive sampling, the majority of participants were found to be not integrating technology to an acceptable level and a small percentage was. After an analysis of constructs from UTAUT, some of this could be attributed to the lack of facilitating conditions in the teaching and learning of Business Education. The implication of the study findings is that poor investment in technology integration in secondary schools in Nigeria affects pedagogical implementations and effective teaching and learning of Business Education subjects. The study concludes that if facilitating conditions and professional development are considered to address the shortfalls in terms of TPACK, technology integration will become a reality in secondary schools in Nigeria.

Keywords: business education, secondary education, technology integration, TPACK, UTAUT

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Authors: Houari Boumediene University of Science, Technology.

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"Various methods are typically used in the dynamic analysis of transversely vibrating beams. To achieve this, numerical methods are used to solve the general eigenvalue problem. The equations of equilibrium, which describe the motion, are derived from a fourth-order differential equation. Our study is based on the finite element method, and the results of the investigation are the vibration frequencies obtained using the Jacobi method. Two types of elementary mass matrices are considered: one representing a uniform distribution of mass along the element and the other consisting of concentrated masses located at fixed points whose number increases progressively with equal distances at each evaluation stage. The beams studied have different boundary constraints, representing several classical situations. Comparisons are made for beams where the distributed mass is replaced by n concentrated masses. As expected, the first calculation stage involves determining the lowest number of beam parts that gives a frequency comparable to that obtained from the Rayleigh formula. The obtained values are then compared to theoretical results based on the assumptions of the Bernoulli-Euler theory. These steps are repeated for the second type of mass representation in the same manner."

Keywords: finite element method, bernouilli eulertheory, structural analysis, vibration analysis, rayleigh quotient

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Authors: Rita Magdalena, N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Sofia Saidah, Bima Sakti

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Vessel segmentation of retinal fundus is important for biomedical sciences in diagnosing ailments related to the eye. Segmentation can simplify medical experts in diagnosing retinal fundus image state. Therefore, in this study, we designed a software using MATLAB which enables the segmentation of the retinal blood vessels on retinal fundus images. There are two main steps in the process of segmentation. The first step is image preprocessing that aims to improve the quality of the image to be optimum segmented. The second step is the image segmentation in order to perform the extraction process to retrieve the retina’s blood vessel from the eye fundus image. The image segmentation methods that will be analyzed in this study are Morphology Operation, Discrete Wavelet Transform and combination of both. The amount of data that used in this project is 40 for the retinal image and 40 for manually segmentation image. After doing some testing scenarios, the average accuracy for Morphology Operation method is 88.46 % while for Discrete Wavelet Transform is 89.28 %. By combining the two methods mentioned in later, the average accuracy was increased to 89.53 %. The result of this study is an image processing system that can segment the blood vessels in retinal fundus with high accuracy and low computation time.

Keywords: discrete wavelet transform, fundus retina, morphology operation, segmentation, vessel

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Authors: Robert Cazar, Nathaly Maza

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Energy drinks and sports drinks are quite popular among young adults and teenagers worldwide. Some concerns regarding their health effects – particularly those of the energy drinks - have been raised based on scientific findings. Differentiating between these two types of drinks by means of their chemical properties seems to be an instructive task. Chemometrics provides the most appropriate strategy to do so. In this study, a discrimination analysis of the energy and sports drinks has been carried out applying chemometric methods. A set of eleven samples of available commercial brands of drinks – seven energy drinks and four sports drinks – were collected. Each sample was characterized by eight chemical variables (carbohydrates, energy, sugar, sodium, pH, degrees Brix, density, and citric acid). The data set was standardized and examined by exploratory chemometric techniques such as clustering and principal component analysis. As a preliminary step, a variable selection was carried out by inspecting the variable correlation matrix. It was detected that some variables are redundant, so they can be safely removed, leaving only five variables that are sufficient for this analysis. They are sugar, sodium, pH, density, and citric acid. Then, a hierarchical clustering `employing the average – linkage criterion and using the Euclidian distance metrics was performed. It perfectly separates the two types of drinks since the resultant dendogram, cut at the 25% similarity level, assorts the samples in two well defined groups, one of them containing the energy drinks and the other one the sports drinks. Further assurance of the complete discrimination is provided by the principal component analysis. The projection of the data set on the first two principal components – which retain the 71% of the data information – permits to visualize the distribution of the samples in the two groups identified in the clustering stage. Since the first principal component is the discriminating one, the inspection of its loadings consents to characterize such groups. The energy drinks group possesses medium to high values of density, citric acid, and sugar. The sports drinks group, on the other hand, exhibits low values of those variables. In conclusion, the application of chemometric methods on a data set that features some chemical properties of a number of energy and sports drinks provides an accurate, dependable way to discriminate between these two types of beverages.

Keywords: chemometrics, clustering, energy drinks, principal component analysis, sports drinks

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Authors: Mohammad Reza Baradaran, Farhad Hamzezarghani, Mehdi Rastegari Ghiri, Zahra Mirsanjari

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Passive control methods can be utilized to build earthquake resistant structures, and also to strengthen the vulnerable ones. One of the most effective, yet simple passive control methods is the use of vertical shear-links (VSL) in systems with eccentric bracing. In fact, vertical shear-links dissipate the earthquake energy and act like a ductile fuse. In this paper, we studied the effect of this system in increasing the ductility and energy dissipation and also modeled the behavior of this type of eccentric bracing, and compared the hysteresis diagram of the modeled samples with the laboratory samples. We studied several samples of frames with vertical shear-links in order to assess the behavior of this type of eccentric bracing. Each of these samples was modeled in finite element software ANSYS 9.0, and was analyzed under the static cyclic loading. It was found that vertical shear-links have a more stable hysteresis loops. Another analysis showed that using honeycomb beams as the horizontal beam along with steel reinforcement has no negative effect on the hysteresis behavior of the sample.

Keywords: vertical shear-link, passive control, cyclic analysis, energy dissipation, honeycomb beam

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Authors: Al. Tsertsvadze. L. Ebralidze, I. Matchutadze. D. Berashvili, A. Bakuridze

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Peatlands are landscape elements, they are formed over a very long period by physical, chemical, biologic, and geologic processes. In the moderate zone of Caucasus, the Kolkheti lowlands are distinguished by the diversity of relictual plants, a high degree of endemism, orographic, climate, landscape, and other characteristics of high levels of biodiversity. The unique properties of the Kolkheti region lead to the formation of special, so-called, endemic peat peloids. The composition and properties of peloids strongly depend on peat-forming plants. Peat is considered a unique complex of raw materials, which can be used in different fields of the industry: agriculture, metallurgy, energy, biotechnology, chemical industry, health care. They are formed in permanent wetland areas. As a result of decay, higher plants remain in the anaerobic area, with the participation of microorganisms. Peat mass absorbs soil and groundwater. Peloids are predominantly rich with humic substances, which are characterized by high biological activity. Humic acids stimulate enzymatic activity, regenerative processes, and have anti-inflammatory activity. Objects of the research were Kolkheti peat peloids (Ispani, Anaklia, Churia, Chirukhi, Peranga) possessing different formation phases. Due to specific physical and chemical properties of research objects, the aim of the research was to develop analytical methods in order to study the chemical composition of the objects. The research was held using modern instrumental methods of analysis: Ultraviolet-visible spectroscopy and Infrared spectroscopy, Scanning Electron Microscopy, Centrifuge, dry oven, Ultraturax, pH meter, fluorescence spectrometer, Gas chromatography-mass spectrometry (GC-MS/MS), Gas chromatography. Based on the research ration between organic and inorganic substances, the spectrum of micro and macro elements, also the content of minerals was determined. The content of organic nitrogen was determined using the Kjeldahl method. The total composition of amino acids was studied by a spectrophotometric method using standard solutions of glutamic and aspartic acids. Fatty acid was determined using GC (Gas chromatography). Based on the obtained results, we can conclude that the method is valid to identify fatty acids in the research objects. The content of organic substances in the research objects was held using GC-MS. Using modern instrumental methods of analysis, the chemical composition of research objects was studied. Each research object is predominantly reached with a broad spectrum of organic (fatty acids, amino acids, carbocyclic and heterocyclic compounds, organic acids and their esters, steroids) and inorganic (micro and macro elements, minerals) substances. Modified methods used in the presented research may be utilized for the evaluation of cosmetological balneological and pharmaceutical means prepared on the base of Kolkheti's Sphagnum Peat Peloids.

Keywords: modern analytical methods, natural resources, peat, chemistry

Procedia PDF Downloads 111

Authors: Tolga Aydin, M. Fatih Alaeddinoğlu

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People, throughout the history, have made estimates and inferences about the future by using their past experiences. Developing information technologies and the improvements in the database management systems make it possible to extract useful information from knowledge in hand for the strategic decisions. Therefore, different methods have been developed. Data mining by association rules learning is one of such methods. Apriori algorithm, one of the well-known association rules learning algorithms, is not commonly used in spatio-temporal data sets. However, it is possible to embed time and space features into the data sets and make Apriori algorithm a suitable data mining technique for learning spatio-temporal association rules. Lake Van, the largest lake of Turkey, is a closed basin. This feature causes the volume of the lake to increase or decrease as a result of change in water amount it holds. In this study, evaporation, humidity, lake altitude, amount of rainfall and temperature parameters recorded in Lake Van region throughout the years are used by the Apriori algorithm and a spatio-temporal data mining application is developed to identify overflows and newly-formed soil regions (underflows) occurring in the coastal parts of Lake Van. Identifying possible reasons of overflows and underflows may be used to alert the experts to take precautions and make the necessary investments.

Keywords: apriori algorithm, association rules, data mining, spatio-temporal data

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Authors: Abduxukur Zayit, Guo Rui Chen

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Universities play important role for develop and distribute sustainable development ideas. This research based on the current situation of large and widely distributed university campuses in China. In view of the deterioration of campus performance, the aging of function and facilities, the large consumption of energy and resources, a logic of "problem-oriented-goal-oriented- At the level, taking the problem orientation as the focus,this paper analyzes the main influencing factors of the existing characteristics of the university campuses, establishes the digital assessment methods and clarifies the key points of the rennovation. Based on the goal orientation, this paper puts forward the existing university campus design principles, builds the green transformation-carding model and sets up the post-use evaluation model. In the end, with dual guidance as the constraint, we will formulate green design standards for campus greening, construct a greening enhancement measure for campus environment, and develop and promote a green campus after-use assessment platform. It provides useful research methods and research ideas for the reconstruction of the existing campus in China, especially the urban universities.

Keywords: design method, existing university campus, green renovation, sustainable development

Procedia PDF Downloads 115

Authors: Denise Allison D. Garcia, Camille C. Garcia, Keanu Raphael Garrido, Crestita B. Tan

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Introduction: Anxiety is a common problem among pre-operative patients. Several methods or interventions are being applied in order to relieve anxiety. Laughter yoga, however, is a method that has been used to relieve anxiety but has not yet been tested to pre-operative patients. Therefore, this study determined the effectiveness of laughter yoga in reducing anxiety among pre-operative middle-aged patients scheduled for major surgery. Methods: After Ethics Review Board approval, a quasi-experimental study was conducted among 40 purposely-selected pre-operative patients in two tertiary hospitals. Anxiety level was measured prior to administration of laughter yoga using the State-Trait Anxiety Inventory with a Cronbach alpha of 0.83. After Laughter yoga, anxiety level was then measured again. Gathered data were analyzed in SPSS version 20 using paired and independent t-test and ANCOVA. Results: After analysis of the data gathered, the results showed that there was a significant decrease in the anxiety level of patients in the experimental group. From an anxiety level of 44.00, the rating went down to 36.85. Meanwhile in the control group, the anxiety level at the pretest at 41.25 went up to 42.50. Laughter yoga was an effective non-pharmacologic intervention for reducing anxiety of pre-operative patients. Conclusion: It is therefore concluded that laughter yoga causes a significant decrease in the anxiety level of patients.

Keywords: anxiety, laughter yoga, non-pharmacologic, pre-operative

Procedia PDF Downloads 423

Authors: Abdulmalek Ahmed

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Formation pressure is the main function that affects drilling operation economically and efficiently. Knowing the pore pressure and the parameters that affect it will help to reduce the cost of drilling process. Many empirical models reported in the literature were used to calculate the formation pressure based on different parameters. Some of these models used only drilling parameters to estimate pore pressure. Other models predicted the formation pressure based on log data. All of these models required different trends such as normal or abnormal to predict the pore pressure. Few researchers applied artificial intelligence (AI) techniques to predict the formation pressure by only one method or a maximum of two methods of AI. The objective of this research is to predict the pore pressure based on both drilling parameters and log data namely; weight on bit, rotary speed, rate of penetration, mud weight, bulk density, porosity and delta sonic time. A real field data is used to predict the formation pressure using five different artificial intelligence (AI) methods such as; artificial neural networks (ANN), radial basis function (RBF), fuzzy logic (FL), support vector machine (SVM) and functional networks (FN). All AI tools were compared with different empirical models. AI methods estimated the formation pressure by a high accuracy (high correlation coefficient and low average absolute percentage error) and outperformed all previous. The advantage of the new technique is its simplicity, which represented from its estimation of pore pressure without the need of different trends as compared to other models which require a two different trend (normal or abnormal pressure). Moreover, by comparing the AI tools with each other, the results indicate that SVM has the advantage of pore pressure prediction by its fast processing speed and high performance (a high correlation coefficient of 0.997 and a low average absolute percentage error of 0.14%). In the end, a new empirical correlation for formation pressure was developed using ANN method that can estimate pore pressure with a high precision (correlation coefficient of 0.998 and average absolute percentage error of 0.17%).

Keywords: Artificial Intelligence (AI), Formation pressure, Artificial Neural Networks (ANN), Fuzzy Logic (FL), Support Vector Machine (SVM), Functional Networks (FN), Radial Basis Function (RBF)

Procedia PDF Downloads 134

Authors: Tomas Barnak, Libor Matejka

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The aim of this study is to create a standard application using multi-criteria evaluation in the field of forensic engineering. This situation can occur in the professional assessment in several cases such as when it is necessary to consider more criteria variant of the structural subsystems, more variants according to several criteria based on a court claim, which requires expert advice. A problematic situation arises when it is necessary to clearly determine the ranking of the options according to established criteria, and reduce subjective evaluation. For the procurement in the field of construction which is based on the prepared text of the law not only economic criteria but also technical, technological and environmental criteria will be determined. This fact substantially changes the style of evaluation of individual bids. For the above-mentioned needs of procurement, the unification of expert’s decisions and the use of multi-criteria assessment seem to be a reasonable option. In the case of experimental verification when using multi-criteria evaluation of alternatives construction subsystem the economic, technical, technological and environmental criteria will be compared. The core of the solution is to compare a selected number of set criteria, application methods and evaluation weighting based on the weighted values assigned to each of the criteria to use multi-criteria evaluation methods. The sequence of individual variations is determined by the evaluation of the importance of the values of corresponding criteria concerning expertise in the problematic of outside wall constructional subsystems.

Keywords: criteria, expertise, multi-criteria evaluation, outside wall subsystems

Procedia PDF Downloads 303

Authors: Anne Schattel, Mitja Echim, Christof Büskens

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Trajectory planning for deep space missions has become a recent topic of great interest. Flying to space objects like asteroids provides two main challenges. One is to find rare earth elements, the other to gain scientific knowledge of the origin of the world. Due to the enormous spatial distances such explorer missions have to be performed unmanned and autonomously. The mathematical field of optimization and optimal control can be used to realize autonomous missions while protecting recourses and making them safer. The resulting algorithms may be applied to other, earth-bound applications like e.g. deep sea navigation and autonomous driving as well. The project KaNaRiA ('Kognitionsbasierte, autonome Navigation am Beispiel des Ressourcenabbaus im All') investigates the possibilities of cognitive autonomous navigation on the example of an asteroid mining mission, including the cruise phase and approach as well as the asteroid rendezvous, landing and surface exploration. To verify and test all methods an interactive, real-time capable simulation using virtual reality is developed under KaNaRiA. This paper focuses on the specific challenge of the guidance during the cruise phase of the spacecraft, i.e. trajectory optimization and optimal control, including first solutions and results. In principle there exist two ways to solve optimal control problems (OCPs), the so called indirect and direct methods. The indirect methods are being studied since several decades and their usage needs advanced skills regarding optimal control theory. The main idea of direct approaches, also known as transcription techniques, is to transform the infinite-dimensional OCP into a finite-dimensional non-linear optimization problem (NLP) via discretization of states and controls. These direct methods are applied in this paper. The resulting high dimensional NLP with constraints can be solved efficiently by special NLP methods, e.g. sequential quadratic programming (SQP) or interior point methods (IP). The movement of the spacecraft due to gravitational influences of the sun and other planets, as well as the thrust commands, is described through ordinary differential equations (ODEs). The competitive mission aims like short flight times and low energy consumption are considered by using a multi-criteria objective function. The resulting non-linear high-dimensional optimization problems are solved by using the software package WORHP ('We Optimize Really Huge Problems'), a software routine combining SQP at an outer level and IP to solve underlying quadratic subproblems. An application-adapted model of impulsive thrusting, as well as a model of an electrically powered spacecraft propulsion system, is introduced. Different priorities and possibilities of a space mission regarding energy cost and flight time duration are investigated by choosing different weighting factors for the multi-criteria objective function. Varying mission trajectories are analyzed and compared, both aiming at different destination asteroids and using different propulsion systems. For the transcription, the robust method of full discretization is used. The results strengthen the need for trajectory optimization as a foundation for autonomous decision making during deep space missions. Simultaneously they show the enormous increase in possibilities for flight maneuvers by being able to consider different and opposite mission objectives.

Keywords: deep space navigation, guidance, multi-objective, non-linear optimization, optimal control, trajectory planning.

Procedia PDF Downloads 395