Search results for: syntax tree probing

Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

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Authors: Sender Dovchin

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Moving beyond two main frameworks of interlingual and intralingual discrimination, this paper will address the understanding of translingual discrimination. This concept refers to discrimination based on how one uses certain languages, linguistic and communicative repertoires, which are (il)legitimised by the interactants. Translingual discrimination contributes intensity to transnational migrations processes, where migrants with transitional backgrounds seem to illustrate two main characteristics of marginalizations – “name discrimination” and “accentism”. The lifelong accumulation of these characteristics of translingual discrimination may cause negative emotionality, such as translingual inferiority complexes, to its victims. As a result, these transnational migrants seem to adopt varied coping strategies such as CV-whitening and accent purifications while probing for translingual safe spaces. The presentation concludes with the socio-cultural and pedagogical implications of translingual discrimination in relation to the language usage of transnational migrants.

Keywords: accentism, discrimination, migrants, translingualism

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Authors: Mohsen Negmeddin

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Throughout their history, ancient Egyptians had known several kinds and types of boats, which were made from two main kinds of materials, the local one, as the dried papyrus reeds and the local tree trunks, the imported one, as the boats which were made from Lebanon cedar tree trunks. A varied using of these boats, as the fish hunting small boats, the transportation and trade boats "Cargo Boats", as well as the ceremonial boats, and the warfare boats. The research is intending for the last one, the warfare boats and the river/maritime battles since the beginning of ancient Egyptian civilization at the pre-historic era up till the end of the second intermediate period, to reveal the kinds and types of those fighting ships before establishing the Egyptian navy at the beginning of the New Kingdome (1550-1770 B.C). Two methods will follow at this research, the mention of names and titles of these ships through the texts (ancient Egyptian language) resources, and the depiction of it at the scenes.

Keywords: the warfare boats, the maritime battles, the pre-historic era, the second intermediate period

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Authors: I. Turk Cakir, A. Senol, A. T. Tasci, O. Cakir

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We study the anomalous WWγ and WWZ couplings by calculating total cross sections of the ep→νqγX and ep→νqZX processes at the LHeC with electron beam energy Ee=140 GeV and the proton beam energy Ep=7 TeV, and at the FCC-ep collider with the polarized electron beam energy Ee=80 GeV and the proton beam energy Ep=50 TeV. At the LHeC with electron beam polarization, we obtain the results for the difference of upper and lower bounds as (0.975, 0.118) and (0.285, 0.009) for the anomalous (Δκγ,λγ) and (Δκz,λz) couplings, respectively. As for FCC-ep collider, these bounds are obtained as (1.101,0.065) and (0.320,0.002) at an integrated luminosity of Lint=100 fb-1.

Keywords: anomalous couplings, future circular collider, large hadron electron collider, W-boson and Z-boson

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Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

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The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

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Authors: Indu ray

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In today’s digital world the internet is already flooded with information on how to master grammar in a foreign language. It is well known that one cannot master a language without grammar. Grammar is the backbone of any language. Without grammar there would be no structure to help you speak/write or listen/read. Successful communication is only possible if the form and function of linguistic utterances are firmly related to one another. Grammar has its own rules of use to formulate an easier-to-understand language. Like a tool, grammar formulates our thoughts and knowledge in a meaningful way. Every language has its own grammar. With grammar, we can quickly analyze whether there is any action in this text: (Present, past, future). Knowledge of grammar is an important prerequisite for mastering a foreign language. What’s most important is how teachers can make grammar lessons more interesting for students and thus promote grammar skills more successfully. Through this paper, we discuss a few important methods like (Interactive Grammar Exercises between students, Interactive Grammar Exercise between student to teacher, Grammar translation method, Audio -Visual Method, Deductive Method, Inductive Method). This paper is divided into two sections. In the first part, brief definitions and principles of these approaches will be provided. Then the possibility and the case of combination of this approach will be analyzed. In the last section of the paper, I would like to present a survey result conducted at my university on a few methods to quickly learn grammar in Foreign Language. We divided the Grammatical Skills in six Parts. 1.Grammatical Competence 2. Speaking Skills 3. Phonology 4. The syntax and the Semantics 5. Rule 6. Cognitive Function and conducted a survey among students. From our survey results, we can observe that phonology, speaking ability, syntax and semantics can be improved by inductive method, Audio-visual Method, and grammatical translation method, for grammar rules and cognitive functions we should choose IGE (teacher-student) method. and the IGE method (pupil-pupil). The study’s findings revealed, that the teacher delivery Methods should be blend or fusion based on the content of the Grammar.

Keywords: innovative method, grammatical skills, audio-visual, translation

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Authors: Eun-Ji Lee, Hye-Sung Park, Chan-Jung Lee, Won-Sik Kong

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We analyzed the DNA sequence of the ITS (Internal Transcribed Spacer) region of the 18S ribosomal gene and compared it with the gene sequence of T. fuciformis and Hypoxylon sp. in the BLAST database. The sequences of collected T. fuciformis and Hypoxylon sp. have over 99% homology in the T. fuciformis and Hypoxylon sp. sequence BLAST database. In order to select the optimal medium for T. fuciformis, five kinds of a medium such as Potato Dextrose Agar (PDA), Mushroom Complete Medium (MCM), Malt Extract Agar (MEA), Yeast extract (YM), and Compost Extract Dextrose Agar (CDA) were used. T. fuciformis showed the best growth on PDA medium, and Hypoxylon sp. showed the best growth on MCM. So as to investigate the optimum pH and temperature, the pH range was set to pH4 to pH8 and the temperature range was set to 15℃ to 35℃ (5℃ degree intervals). Optimum culture conditions for the T. fuciformis growth were pH5 at 25℃. Hypoxylon sp. were pH6 at 25°C. In order to confirm the most suitable carbon source, we used fructose, galactose, saccharose, soluble starch, inositol, glycerol, xylose, dextrose, lactose, dextrin, Na-CMC, adonitol. Mannitol, mannose, maltose, raffinose, cellobiose, ethanol, salicine, glucose, arabinose. In the optimum carbon source, T. fuciformis is xylose and Hypoxylon sp. is arabinose. Using the column test, we confirmed sawdust a suitable for T. fuciformis, since the composition of sawdust affects the growth of fruiting bodies of T. fuciformis. The sawdust we used is oak tree, pine tree, poplar, birch, cottonseed meal, cottonseed hull. In artificial cultivation of T. fuciformis with sawdust medium, T. fuciformis and Hypoxylon sp. showed fast mycelial growth on mixture of oak tree sawdust, cottonseed hull, and wheat bran.

Keywords: cultivation, optimal condition, tremella fuciformis, nutritional source

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Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

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For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

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Authors: Feras Hanandeh, Majdi Shannag

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This research studies the different factors that could affect the Faculty of Information Technology in Hashemite University students’ accumulative average. The research paper verifies the student information, background, their academic records, and how this information will affect the student to get high grades. The student information used in the study is extracted from the student’s academic records. The data mining tools and techniques are used to decide which attribute(s) will affect the student’s accumulative average. The results show that the most important factor which affects the students’ accumulative average is the student Acceptance Type. And we built a decision tree model and rules to determine how the student can get high grades in their courses. The overall accuracy of the model is 44% which is accepted rate.

Keywords: data mining, classification, extracting rules, decision tree

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Authors: Jovana M. Ćirković, Aleksandar M. Radojković, Sanja Z. Perać, Jelena N. Jovanović, Zorica M. Branković, Slobodan D. Milanović, Ivan Lj. Milenković, Jovan N. Dobrosavljević, Nemanja V. Simović, Vanja M. Tadić, Ana R. Žugić, Goran O. Branković

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The protection of forests is a national interest and of strategic importance in every country. The spongy moth (Lymantria dispar) is a damaging invasive pest that can weaken and destroy trees by defoliating them. Chemical pesticides commonly used to protect forests against spongy moths not only have a negative impact on terrestrial and aquatic organisms/ecosystems but also often fail to provide significant protection. Therefore, many eco-friendly alternatives have been considered. Within this research, a new biopesticide was developed based on the method of nanoencapsulation of plant extracts in a biopolymer matrix, which provides a slow release of the active components during a substantial time period. The antifeedant activity of plant extracts of common (Fraxinus excelsior L.), manna (F. ornus L.) ash tree, and the tree of heaven Ailanthus altissima (Mill.) was tested on the spongy moth (Lymantria dispar L, 1758) larvae. To test the antifeedant activity of these compounds, the choice and non-choice tests in laboratory conditions for different plant extract concentrations (0.01, 0.1, 0.5, and 1 % v/v) were carried out. In both cases, the best results showed formulations based on the tree of heaven and common ash for the concentration of 1%, with deterioration indices of 163 and 132, respectively. The main benefit of these formulations is their versatility, effectiveness, prolonged effect, and because they are completely environmentally acceptable. Therefore, they can be considered for suppression of the spongy moth in forest ecosystems.

Keywords: Ailanthus altissima (Mill.), Fraxinus excelsior L., encapsulation, Lymantria dispar

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: Ghada S. Moussa

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Vehicle classification is an important task in traffic surveillance and intelligent transportation systems. Classification of vehicle images is facing several problems such as: high intra-class vehicle variations, occlusion, shadow, illumination. These problems and others must be considered to develop a reliable vehicle classification system. In this study, a reliable multi-type vehicle classification system based on Bag-of-Words (BoW) paradigm is developed. Our proposed system used and compared four well-known classifiers; Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbour (KNN), and Decision Tree to classify vehicles into four categories: motorcycles, small, medium and large. Experiments on a large dataset show that our approach is efficient and reliable in classifying vehicles with accuracy of 95.7%. The SVM outperforms other classification algorithms in terms of both accuracy and robustness alongside considerable reduction in execution time. The innovativeness of developed system is it can serve as a framework for many vehicle classification systems.

Keywords: vehicle classification, bag-of-words technique, SVM classifier, LDA classifier, KNN classifier, decision tree classifier, SIFT algorithm

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Authors: Dhanuja S. Patil, Sanjay B. Waykar

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Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

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Authors: Oktay Cinar

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The aim of this study is to investigate the acquisition of Overt Pronoun Constraint (OPC) by adult Korean L2 Turkish speakers in order to find out how constraints regulating the syntax of null and overt subjects are acquired. OPC is claimed to be a universal feature of all null subject languages restricting the co-indexation between overt embedded pronoun and quantified or wh-question antecedents. However, there is no such restriction when the embedded subject is null or the antecedent is a referential subject. Considered as a principle of Universal Grammar (UG), OPC knowledge of L2 speakers has been widely tested with different language pairs. In the light of previous studies on OPC, it can be argued that L2 learners display early sensitivity to OPC constraints during their interlanguage grammar development. Concerning this, the co-indexation between overt embedded pronoun o (third person pronoun) and referential matrix subject is claimed to be controversial in Turkish, which poses problems with the universality of OPC. However, the current study argues against this claim by providing evidence from advanced Korean speakers that OPC is universal to all null subject languages and OPC knowledge can be accessed with direct access to UG. In other words, the performances of adult Korean speakers on the syntax of null and overt subjects are tested to support this claim. In order to test this, OPC task is used. 15 advanced speakers and a control group of adult native Turkish participants are instructed to determine the co-reference relationship between the subject of embedded clause, either overt pronominal o or null, and the subject of the matrix clause, either quantified pronoun and wh-question or referential antecedent. They are asked to select the interpretation of the embedded subject, either as the same person as in the matrix subject or another person who is not the same person in the matrix subject. These relations are represented with four conditions, and each condition has four questions (16 questions in total). The results claim that both control group and Korean L2 Turkish speakers display sensitivity to all constraints that OPC has, which suggests that OPC works in Turkish as well.

Keywords: adult Korean speakers, binding theory, generative second language acquisition, overt pronoun constraint

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Authors: Zhang Dongqing

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Concern for students' mental health and the application of intelligent advanced technologies are driving changes in teaching models. The traditional teacher-centered classroom is beginning to transform into a student-centered smart interactive learning environment. Nowadays, smart classrooms are compatible with constructivist learning. This theory emphasizes the role of teachers in the teaching process as helpers and facilitators of knowledge construction, and students learn by interacting with them. The spatial design of classrooms is closely related to the teaching model and should also be developed in the direction of smart classroom design. The goal is to explore the impact of smart classroom layout on student-centered teaching environment and teacher-student interaction under the guidance of constructivist learning theory, by combining the design process and feedback analysis of the smart transformation project on the campus of Tongji University in Shanghai. During the research process, the theoretical basis of constructivist learning was consolidated through literature research and case analysis. The integration and visual field analysis of the traditional and transformed indoor floor plans were conducted using space syntax tools. Finally, questionnaire surveys and interviews were used to collect data. The main conclusions are as followed: flexible spatial layouts can promote students' learning effects and mental health; the interactivity of smart classroom layouts is different and needs to be combined with different teaching models; the public areas of teaching buildings can also improve the interactive learning atmosphere by adding discussion space. This article provides a data-based research basis for improving students' learning effects and mental health, and provides a reference for future smart classroom design.

Keywords: spatial layout, smart classroom, space syntax, renovation, educational environment

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Authors: I. Ahmad, A. Hannan, S. Ahmad, M. Asif, M. F. Nawaz, M. A. Tanvir, M. F. Azhar

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During this research, a comprehensive survey of tree growing areas of Faisalabad district of Pakistan was conducted to observe the symptoms, spectrum, occurrence and severity of A. nilotica and E. camaldulensis decline. Objective of current research was to investigate specific fungal pathogens involved in decline of A. nilotica and E. camaldulensis. For this purpose, infected roots, bark, neck portion, stem, branches, leaves and infected soils were collected to identify associated fungi. Potato dextrose agar (PDA) and Czepak dox agar media were used for isolations. Identification of isolated fungi was done microscopically and different fungi were identified. During survey of urban locations of Faisalabad, disease incidence on Kikar and Eucalyptus was recorded as 3.9-7.9% and 2.6-7.1% respectively. Survey of Agroforest zones of Faisalabad revealed decline incidence on kikar 7.5% from Sargodha road while on Satiana and Jhang road it was not planted. In eucalyptus trees, 4%, 8% and 0% disease incidence was observed on Jhang road, Sargodha road and Satiana road respectively. The maximum fungus isolated from the kikar tree was Drechslera australiensis (5.00%) from the stem part. Aspergillus flavus also gave the maximum value of (3.05%) from the bark. Alternaria alternata gave the maximum value of (2.05%) from leaves. Rhizopus and Mucor spp. were recorded minimum as compared to the Drechslera, Alternaria and Aspergillus. The maximum fungus isolated from the Eucalyptus tree was Armillaria luteobubalina (5.00%) from the stem part. The other fungi isolated were Macrophamina phaseolina and A. niger.

Keywords: decline, frequency of mycoflora, A. nilotica and E. camaldulensis, Drechslera australiensis, Armillaria luteobubalina

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Authors: Yaxuan Wang

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It has long been a mystery that why the Mongolian possessive suffix, which is constrained by Condition A of binding theory, has the ability to probe a potential antecedent outside of its binding domain. This squib argues that binding theory alone is not sufficient to explain the linguistic facts and proposes an analysis adopting the Agree operation. The current analysis correctly predicts all the possible and impossible structures, with an additional hypothesis that Mongolian possessive suffixes serve as an antecedent for PROs in adjunct. The findings thus provide insights into how Agree operates in Mongolian language.

Keywords: syntax, Mongolian, agreement, possessive particles

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Authors: Yukiko Sasaki Alam, Shahid Alam

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Syntactic parsing is vital for semantic treatment by many applications related to natural language processing (NLP), because form and content coincide in many cases. However, it has not yet reached the levels of reliable performance. By manually examining and analyzing individual machine translation output errors that involve syntax as well as semantics, this study attempts to discover what is required for improving syntactic and semantic parsing.

Keywords: syntactic parsing, error analysis, machine translation, deep parsing

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Authors: Miguel Mellado, Cecilia Zapata

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Goats can be exploited in harsh environments due to their capacity to adjust to limited quantity and quality forage sources. In these environments, leguminous trees can be used as supplementary feeds as foliage and fruits of these trees can contribute to maintain or improve production efficiency in ruminants. The objective of this study was to determine the nutritional value of three leguminous trees heavily selected by goats in a xerophyllous shrubland. Chemical composition and in vitro dry matter disappearance (IVDMD) of leaves and pods from leucaena (Leucaena leucocephala), mesquite (Prosopis laevigata) and huisache (Acacia farnesiana) is presented. Crude protein (CP) ranged from 17.3% for leaves of huisache to 21.9% for leucaena. The neutral detergent fiber (NDF) content ranged from 39.0 to 40.3 with no difference among fodder threes. Across tree species, mean IVDMD was 61.6% for pods and 52.2% for leaves. IVDMD for leaves was highest (P < 0.01) for leucaena (54.9%) and lowest for huisache (47.3%). Condensed tannins in an acetonic extract were highest for leaves of huisache (45.3 mg CE/g DM) and lowest for mesquite (25.9 mg CE/g DM). Pods and leaves of huisache presented the highest number of secondary metabolites, mainly related to hydrobenzoic acid and flavonols; leucaena and mesquite presented mainly flavonols and anthocyanins. It was concluded that leaves and pods of leucaena, mesquite and huisache constitute valuable forages for ruminant livestock due to its low fiber, high CP levels, moderate in vitro fermentation characteristics and high mineral content. Keywords: Fodder tree; ruminants; secondary metabolites; minerals; tannins

Keywords: fodder tree, ruminants, secondary metabolites, minerals, tannins

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Authors: Azene Zenebe

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Deep learning is a subset of machine learning which incorporates techniques for the construction of artificial neural networks and found to be useful for modeling complex problems with large dataset. Deep learning requires a very high power computational and longer time for training. By aggregating computing power, high performance computer (HPC) has emerged as an approach to resolving advanced problems and performing data-driven research activities. Cyber threat intelligence (CIT) is actionable information or insight an organization or individual uses to understand the threats that have, will, or are currently targeting the organization. Results of review of literature will be presented along with results of experimental study that compares the performance of tree-based and function-base machine learning including deep learning algorithms using secondary dataset collected from darknet.

Keywords: deep-learning, cyber security, cyber threat modeling, tree-based machine learning, function-based machine learning, data science

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Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi

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Background:-Due to the essential role of the foot in movement, foot disorders (FDs) have significant impacts on activity and quality of life. Many studies confirmed the association between FDs and demographic characteristics. On the other hand, recent advances in data collection and statistical analysis led to an increase in the volume of databases. Analysis of patient’s data through the decision tree can be used to explore the relationship between demographic characteristics and FDs. Significance of the study: This study aimed to investigate the relationship between demographic characteristics with common FDs. The second purpose is to better inform foot intervention, we classify FDs based on demographic variables. Methodologies: We analyzed 2323 subjects with pes-planus (PP), pes-cavus (PC), hallux-valgus (HV) and plantar-fasciitis (PF) who were referred to a foot therapy clinic between 2015 and 2021. Subjects had to fulfill the following inclusion criteria: (1) weight between 14 to 150 kilogram, (2) height between 30 to 220, (3) age between 3 to 100 years old, and (4) BMI between 12 to 35. Medical archives of 2323 subjects were recorded retrospectively and all the subjects examined by an experienced physician. Age and BMI were classified into five and four groups, respectively. 80% of the data were randomly selected as training data and 20% tested. We build a decision tree model to classify FDs using demographic characteristics. Findings: Results demonstrated 981 subjects from 2323 (41.9%) of people who were referred to the clinic with FDs were diagnosed as PP, 657 (28.2%) PC, 628 (27%) HV and 213 (9%) identified with PF. The results revealed that the prevalence of PP decreased in people over 18 years of age and in children over 7 years. In adults, the prevalence depends first on BMI and then on gender. About 10% of adults and 81% of children with low BMI have PP. There is no relationship between gender and PP. PC is more dependent on age and gender. In children under 7 years, the prevalence was twice in girls (10%) than boys (5%) and in adults over 18 years slightly higher in men (62% vs 57%). HV increased with age in women and decreased in men. Aging and obesity have increased the prevalence of PF. We conclude that the accuracy of our approach is sufficient for most research applications in FDs. Conclusion:-The increased prevalence of PP in children is probably due to the formation of the arch of the foot at this age. Increasing BMI by applying high pressure on the foot can increase the prevalence of this disorder in the foot. In PC, the Increasing prevalence of PC from women to men with age may be due to genetics and innate susceptibility of men to this disorder. HV is more common in adult women, which may be due to environmental reasons such as shoes, and the prevalence of PF in obese adult women may also be due to higher foot pressure and housekeeping activities.

Keywords: decision tree, demographic characteristics, foot disorders, machine learning

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Authors: J. V. Gonzalez Fernandez, T. Mozume, S. Gozu, A. Lastras Martinez, L. F. Lastras Martinez, J. Ortega Gallegos, R. E. Balderas Navarro

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We report on a theoretical-experimental study of photoreflectance anisotropy (PRA) spectroscopy of coupled double quantum wells. By probing the in-plane interfacial optical anisotropies, we demonstrate that PRA spectroscopy has the capacity to detect and distinguish layers with quantum dimensions. In order to account for the experimental PRA spectra, we have used a theoretical model at k=0 based on a linear electro-optic effect through a piezoelectric shear strain.

Keywords: coupled double quantum well (CDQW), linear electro-optic (LEO) effect, photoreflectance anisotropy (PRA), piezoelectric shear strain

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Authors: Chuan-Ching Sue, Kai-Chun Chuang

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Peer-to-Peer (P2P) live streaming systems still suffer a challenge when thousands of new peers want to join into the system in a short time, called flash crowd, and most of new peers suffer long start-up delay. Recent studies have proposed a slot-based user access control mechanism, which periodically determines a certain number of new peers to enter the system, and a user batch join mechanism, which divides new peers into several tree structures with fixed tree size. However, the slot-based user access control mechanism is difficult for accurately determining the optimal time slot length, and the user batch join mechanism is hard for determining the optimal tree size. In this paper, we propose a structured access control (SAC) mechanism, which constructs new peers to a multi-layer mesh structure. The SAC mechanism constructs new peer connections layer by layer to replace periodical access control, and determines the number of peers in each layer according to the system’s remaining upload bandwidth and average video rate. Furthermore, we propose an analytical model to represent the behavior of the system growth if the system can utilize the upload bandwidth efficiently. The analytical result has shown the similar trend in system growth as the SAC mechanism. Additionally, the extensive simulation is conducted to show the SAC mechanism outperforms two previously proposed methods in terms of system growth and start-up delay.

Keywords: peer-to-peer, live video streaming system, flash crowd, start-up delay, access control

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Authors: Nur Nadhirah Rusyda Rosnan, Nursuhaili Najwa Masrol, Nurul Fatiha MD Nor, Mohammad Zafrullah Mohammad Salim, Sim Choon Cheak

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Accurate inventories of oil palm planted areas are crucial for plantation management as this would impact the overall economy and production of oil. One of the technological advancements in the oil palm industry is semi-automated palm counting, which is replacing conventional manual palm counting via digitizing aerial imagery. Most of the semi-automated palm counting method that has been developed was limited to mature palms due to their ideal canopy size represented by satellite image. Therefore, immature palms were often left out since the size of the canopy is barely visible from satellite images. In this paper, an approach using a morphological filter and high-resolution satellite image is proposed to detect immature palm trees. This approach makes it possible to count the number of immature oil palm trees. The method begins with an erosion filter with an appropriate window size of 3m onto the high-resolution satellite image. The eroded image was further segmented using watershed segmentation to delineate immature palm tree regions. Then, local minimum detection was used because it is hypothesized that immature oil palm trees are located at the local minimum within an oil palm field setting in a grayscale image. The detection points generated from the local minimum are displaced to the center of the immature oil palm region and thinned. Only one detection point is left that represents a tree. The performance of the proposed method was evaluated on three subsets with slopes ranging from 0 to 20° and different planting designs, i.e., straight and terrace. The proposed method was able to achieve up to more than 90% accuracy when compared with the ground truth, with an overall F-measure score of up to 0.91.

Keywords: immature palm count, oil palm, precision agriculture, remote sensing

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Authors: A. Zare Javid, H. Babaee, E. Ashrafzadeh, H. Yousefimanesh, M. Zakerkish, K. Ahmadi Angali, M. Ravanbakhsh

Abstract:

Introduction: Type 2 diabetes mellitus and periodontal disease hold a physiologically relationship. Periodontal disease, a common widespread chronic disease, is considered as an important complication in diabetes mellitus. The prevalence and severity of periodontal disease are increased among diabetic patients. A balanced nutrition may improve either diabetes or periodontal disease by controlling one of them. The aim of this study was to evaluate the effects of cranberry juice enriched with n-3 PUFA and their individual consumption on glycemic control and antioxidant status in diabetic patients with periodontal disease. Methods: In this randomized clinical trial 41 diabetic patients (35 – 65 y) with chronic adult periodontal disease were recruited from Endocrinology Clinic of Golestan Hospital in Ahvaz city, Iran. Subjects were randomly assigned to four groups as follow: one control group (n=12) and three intervention groups as receiving 1 g n-3 PUFA capsule (n=10), 400 ml cranberry juice (n=9), 400 ml cranberry juice enriched with 1g n-3 PUFA (n=10) for 8 weeks. Non-surgical periodontal therapy was provided for all patients during study. Fasting blood glucose, glycated hemoglobin, plasma and saliva TAOC and MDA, pocket depth and bleeding on probing were measured at baseline and post intervention. Results: There was a significant reduction in glycated hemoglobin observed in intervention groups of receiving n-3 PUFA and cranberry enriched with n-3 PUFA (11 %, P = 0.01 and 7 %, P = 0.01, respectively). The intervention group receiving n-3 PUFA had significantly lower glycated hemoglobin compared with control group. There was no significant difference found in FBS between and within groups. Furthermore, there was a significant increase in plasma TAOC only in cranberry enriched with n-3 PUFA group. Moreover, plasma MDA significantly decreased in intervention groups of receiving cranberry and cranberry enriched with n-3 PUFA. A significant increase was observed in TAOC of salvia in cranberry enriched with n-3 PUFA group compared to control group .The intervention group receiving cranberry enriched with n-3 PUFA had significantly lower MDA of salvia compared with control group. Pocket depth were significantly decreased in all groups, however, bleeding on probing didn’t significantly changed in patients post intervention. Conclusion: It is suggested that consumption of cranberry juice enriched with n-3 PUFA as a nutritional approach in adjunct with non-surgical periodontal therapy may help to improve glycosylated hemogolobin and TAOC in salvia and plasma in diabetic patients with periodontal disease.

Keywords: antioxidant, cranberry, oxidant status, periodontal disease, type 2 diabetes mellitus

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Authors: Milad Mirzaei Aminiyan, Abdolreza Akhgar, Farzad Mirzaei Aminiyan

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Water quality is the critical factor that influence on human health and quantity and quality of grain production in semi-humid and semi-arid area. Pistachio is a main crop that accounts for a considerable portion of Iranian agricultural exports. Give that pistachio tree is a tolerant type of tree to saline and alkaline soil and water conditions, but groundwater and irrigation water quality play important roles in main production this crop. For this purpose, 94 well water samples were taken from 25 wells and samples were analyzed. The results showed give that region’s geological, climatic characteristics, statistical analysis, and based on dominant cations and anions in well water samples (piper diagram); four main types of water were found: Na-Cl, K-Cl, Na-SO4, and K-SO4. It seems that most wells in terms of water quality (salinity and alkalinity) and based on Wilcox diagram have critical status. The analysis suggested that more than eighty-seven percentage of the well water samples have high values of EC that these values are higher than into critical limit EC value for irrigation water, which may be due to the sandy soils in this area. Most groundwater were relatively unsuitable for irrigation but it could be used by application of correct management such as removing and reducing the ion concentrations of Cl‾, SO42‾, Na+ and total hardness in groundwater and also the concentrated deep groundwater was required treatment to reduce the salinity and sodium hazard. Given that irrigation water quality in this area was relatively unsuitable for most agriculture production but pistachio tree was adapted to this area conditions. The integrated management of groundwater for irrigation is the way to solve water quality issues not only in Rafsanjan area, but also in other arid and semi-arid areas.

Keywords: groundwater quality, irrigation water quality, salinity, alkalinity, Rafsanjan plain, pistachio

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Authors: Irene Yi

Abstract:

Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

Procedia PDF Downloads 90

Authors: Galal Omer, Onisimo Mutanga, Elfatih M. Abdel-Rahman, Elhadi Adam

Abstract:

Threatened tree species (TTS) play a significant role in ecosystem functioning and services, land use dynamics, and other socio-economic aspects. Such aspects include ecological, economic, livelihood, security-based, and well-being benefits. The development of techniques for mapping and monitoring TTS is thus critical for understanding the functioning of ecosystems. The advent of advanced imaging systems and supervised learning algorithms has provided an opportunity to classify TTS over fragmenting landscape. Recently, vegetation maps have been produced using advanced imaging systems such as WorldView-2 (WV-2) and robust classification algorithms such as support vectors machines (SVM) and artificial neural network (ANN). However, delineation of TTS in a fragmenting landscape using high resolution imagery has widely remained elusive due to the complexity of the species structure and their distribution. Therefore, the objective of the current study was to examine the utility of the advanced WV-2 data for mapping TTS in the fragmenting Dukuduku indigenous forest of South Africa using SVM and ANN classification algorithms. The results showed the robustness of the two machine learning algorithms with an overall accuracy (OA) of 77.00% (total disagreement = 23.00%) for SVM and 75.00% (total disagreement = 25.00%) for ANN using all eight bands of WV-2 (8B). This study concludes that SVM and ANN classification algorithms with WV-2 8B have the potential to classify TTS in the Dukuduku indigenous forest. This study offers relatively accurate information that is important for forest managers to make informed decisions regarding management and conservation protocols of TTS.

Keywords: artificial neural network, threatened tree species, indigenous forest, support vector machines

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Authors: Mohammed Khalil Ur Rahman, Pradnya Chigle, Bushra Farhen

Abstract:

Indian mythology believes that Vedas are eternal treatises. Vedas are categorized into four divisions viz., Rigveda, Yajurveda, Samveda, Atharveda. All these spiritual classics not only deal with rituals and customs but also consist of inclusion of many references related to health. Out of these four, Atharveda deals with maximum principles pertaining to health sciences. Therefore, it is said that the science and the art of Ayurveda has developed from Atharveda. Ayurveda deals with many medicinal plants either as a single therapeutic use or in combination. One such medicinal plant is Snuhi (Euphorbia neriifolia Linn.) which finds its extensive importance along with Haridra and Apamargakshar, in the preparation of Ksharsutra which in turn is used for the treatment of Fistula in Ano. It is interesting to note that this plant Snuhi is also referred in Holy Quran as the Tree of Zaqqum advocated as the food for the sinners as a part of torment. The reference in Surat Ad-Dukhan is as follows: - 44:43-46. “Verily, the tree of Zaqqum will be the food of the sinners, Like boiling oil, it will boil in the bellies, like the boiling of scalding water.” The above verse implies that plant Snuhi/Zaqqum due to irritant property acts as a drastic purgative but at the same time it also possesses anti inflammatory properties in order to relieve the irritation. These properties of Zaqqum has been unfolded in the modern research which states that, Diterpene polycyclic esters are responsible for its toxic and irritant nature whereas; triterpenes are responsible for its anti inflammatory property. Present work will be an effort to review the concept of Quran about latex of the Tree of Zaqqum in terms of its phytochemistry and its therapeutic use in Ksharsutra pertaining to irritant and anti inflammatory property.

Keywords: ayurveda, Quran, zaqqum, ksharsutra, latex piles, inflammation

Procedia PDF Downloads 331