Search results for: object oriented classification

Authors: Ermias A. Tegegn, Million Meshesha

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Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome (HIV/AIDS) is a major cause of death for most African countries. Ethiopia is one of the seriously affected countries in sub Saharan Africa. Previously in Ethiopia, having HIV/AIDS was almost equivalent to a death sentence. With the introduction of Antiretroviral Therapy (ART), HIV/AIDS has become chronic, but manageable disease. The study focused on a data mining technique to predict future living status of HIV/AIDS patients at the time of drug regimen change when the patients become toxic to the currently taking ART drug combination. The data is taken from University of Gondar Hospital ART program database. Hybrid methodology is followed to explore the application of data mining on ART program dataset. Data cleaning, handling missing values and data transformation were used for preprocessing the data. WEKA 3.7.9 data mining tools, classification algorithms, and expertise are utilized as means to address the research problem. By using four different classification algorithms, (i.e., J48 Classifier, PART rule induction, Naïve Bayes and Neural network) and by adjusting their parameters thirty-two models were built on the pre-processed University of Gondar ART program dataset. The performances of the models were evaluated using the standard metrics of accuracy, precision, recall, and F-measure. The most effective model to predict the status of HIV patients with drug regimen substitution is pruned J48 decision tree with a classification accuracy of 98.01%. This study extracts interesting attributes such as Ever taking Cotrim, Ever taking TbRx, CD4 count, Age, Weight, and Gender so as to predict the status of drug regimen substitution. The outcome of this study can be used as an assistant tool for the clinician to help them make more appropriate drug regimen substitution. Future research directions are forwarded to come up with an applicable system in the area of the study.

Keywords: HIV drug regimen, data mining, hybrid methodology, predictive model

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Authors: Brandon Ko

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Whether it’s a kitchen staff or a law firm, many groups tend to have homogenous characteristics of race, gender, interests, and goals. Social groups are not typically random samples of the population and will usually have common identifiers. According to Blau, age, sex, and education all play salient roles in shaping relationships within members of society. So if there is some degree of homogeneity within groups, the question arises whether this is beneficial or harmful to a group’s effectiveness. There has been much disagreement in the scientific community as to whether the presence of homophily benefits or hinders an athletic team's cohesiveness. For this paper, a comparative study of research of soccer case studies that followed various, youth players was studied against examinations of the effects that such a culture has on athletes. The case studies were used as evidence to determine what kind of homophily existed within the soccer camps. One case study followed several European developmental clubs such as Bayern Munich and Barcelona. Another study followed eight different players, four of each gender, implementing a similar method of interviewing, observing, and questioning. The individual and team goals of each athlete were reviewed to see which teams and players were ego-oriented and which were team-oriented. Additionally, there had been little research done on the relationship between homophily and how it applies to the sport community, suggesting the need to develop this neglected problem in applied psychology. This paper argues that the benefits of an egalitarian culture and stronger relations with people of a similar socio-demographic outweigh the liabilities of cohesion like being stereotyped and a lack of network outside the group as produced by homophily in athletic competition.

Keywords: group cohesion, homophily, sports psychology, youth athletics

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Authors: Marco Castagna

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Proposed paper is aimed to inquire about the relation between text and reader, focusing on the concept of ‘attestation’. Indeed, despite being widely accepted in semiotic research, even today the concept of text remains uncertainly defined. So, it seems to be undeniable that what is called ‘text’ offers an image of internal cohesion and coherence, that makes it possible to analyze it as an object. Nevertheless, this same object remains problematic when it is pragmatically activated by the act of reading. In fact, as for the T.A.R:D.I.S., that is the unique space-temporal vehicle used by the well-known BBC character Doctor Who in his adventures, every text appears to its own readers not only “bigger inside than outside”, but also offering spaces that change according to the different traveller standing in it. In a few words, as everyone knows, this singular condition raises the questions about the gnosiological relation between text and reader. How can a text be considered the ‘same’, even if it can be read in different ways by different subjects? How can readers can be previously provided with knowledge required for ‘understanding’ a text, but at the same time learning something more from it? In order to explain this singular condition it seems useful to start thinking about text as a device more than an object. In other words, this unique status is more clearly understandable when ‘text’ ceases to be considered as a box designed to move meaning from a sender to a recipient (marking the semiotic priority of the “code”) and it starts to be recognized as performative meaning hypothesis, that is discursively configured by one or more forms and empirically perceivable by means of one or more substances. Thus, a text appears as a “semantic hanger”, potentially offered to the “unending deferral of interpretant", and from time to time fixed as “instance of Discourse”. In this perspective, every reading can be considered as an answer to the continuous request for confirming or denying the meaning configuration (the meaning hypothesis) expressed by text. Finally, ‘attestation’ is exactly what regulates this dynamic of request and answer, through which the reader is able to confirm his previous hypothesis on reality or maybe acquire some new ones.Proposed paper is aimed to inquire about the relation between text and reader, focusing on the concept of ‘attestation’. Indeed, despite being widely accepted in semiotic research, even today the concept of text remains uncertainly defined. So, it seems to be undeniable that what is called ‘text’ offers an image of internal cohesion and coherence, that makes it possible to analyze it as an object. Nevertheless, this same object remains problematic when it is pragmatically activated by the act of reading. In fact, as for the T.A.R:D.I.S., that is the unique space-temporal vehicle used by the well-known BBC character Doctor Who in his adventures, every text appears to its own readers not only “bigger inside than outside”, but also offering spaces that change according to the different traveller standing in it. In a few words, as everyone knows, this singular condition raises the questions about the gnosiological relation between text and reader. How can a text be considered the ‘same’, even if it can be read in different ways by different subjects? How can readers can be previously provided with knowledge required for ‘understanding’ a text, but at the same time learning something more from it? In order to explain this singular condition it seems useful to start thinking about text as a device more than an object. In other words, this unique status is more clearly understandable when ‘text’ ceases to be considered as a box designed to move meaning from a sender to a recipient (marking the semiotic priority of the “code”) and it starts to be recognized as performative meaning hypothesis, that is discursively configured by one or more forms and empirically perceivable by means of one or more substances. Thus, a text appears as a “semantic hanger”, potentially offered to the “unending deferral of interpretant", and from time to time fixed as “instance of Discourse”. In this perspective, every reading can be considered as an answer to the continuous request for confirming or denying the meaning configuration (the meaning hypothesis) expressed by text. Finally, ‘attestation’ is exactly what regulates this dynamic of request and answer, through which the reader is able to confirm his previous hypothesis on reality or maybe acquire some new ones.

Keywords: attestation, meaning, reader, text

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Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.

Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection

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Authors: Eli Maria Forti-Pazzianotto, Carolina Moraes Da Costa, Daniela Faleiros Berteli Merino, Maura Rigoldi Simões Da Rocha, Irineu Rasera-Junior

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There is no conclusive evidence to support the use of one type or brand of incentive espirometry over others. The decision as to which equipment is best, have being based on empirical assessment of patient acceptance, ease of use, and cost. The aim was to evaluate the effects of use of two methodologies of breathing exercises, performed by flow-oriented incentive spirometry, in the reversal of diaphragmatic dysfunction in postoperative bariatric surgery. 38 morbid obese women were selected. Respiratory muscle strength was evaluated through the nasal inspiratory pressure (NIP), and the respiratory muscles endurance, through incremental test by measurement of sustained maximal inspiratory pressure (SMIP). They were randomized in 2 groups: 1- Respiron® Classic (RC) the inspirations were slow, deep and sustained for as long as possible (5 sec). 2- Respiron® Athletic1 (RA1) - the inspirations were explosive, quick and intense, raising balls by the explosive way. 6 sets of 15 repetitions with intervals of 30 to 60 seconds were performed in groups. At the end of the intervention program (second PO), the volunteers were reevaluated. The groups were homogeneous with regard to initial assessment. However on reevaluating there was a significant decline of the variable PIN (p= < 0.0001) and SMIP (p=0.0004) in RC. In the RA1 group there was a maintenance of SMIP (p=0.5076) after surgery. The use of the Respiron Athletic 1, as well as the methodology of application used, can contribute positively to preserve the inspiratory muscle endurance and improve the diaphragmatic dysfunction in postoperative period.

Keywords: bariatric surgery, incentive spirometry, respiratory muscle, physiotherapy

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Authors: Pedro Mario Gonzalez Jimenez

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The novelties introduced by the last Notice on agreements of minor importance tighten the application of the ‘De minimis’ safe harbour in the European Union. However, the undetermined legal concept of effect on trade between the Member States becomes importance at the same time. Therefore, the current analysis that the jurist should carry out in the European Union to determine if an agreement appreciably restrict competition under Article 101 of the Treaty on the Functioning of the European Union is double. Hence, it is necessary to know how to balance the significance in competition and the significance in effect on trade between the Member States. It is a crucial issue due to the negative delimitation of restriction of competition affects the positive one. The methodology of this research is rather simple. Beginning with a historical approach to the ‘De Minimis Rule’, their main problems and uncertainties will be found. So, after the analysis of normative documents and the jurisprudence of the Court of Justice of the European Union some proposals of ‘Lege ferenda’ will be offered. These proposals try to overcome the contradictions and questions that currently exist in the European Union as a consequence of the current legal regime of agreements of minor importance. The main findings of this research are the followings: Firstly, the effect on trade is another way to analyze the importance of an agreement different from the ‘De minimis rule’. In point of fact, this concept is singularly adapted to go through agreements that have as object the prevention, restriction or distortion of competition, as it is observed in the most famous European Union case-law. Thanks to the effect on trade, as long as the proper requirements are met there is no a restriction of competition under article 101 of the Treaty on the Functioning of the European Union, even if the agreement had an anti-competitive object. These requirements are an aggregate market share lower than 5% on any of the relevant markets affected by the agreement and turnover lower than 40 million of Euros. Secondly, as the Notice itself says ‘it is also intended to give guidance to the courts and competition authorities of the Member States in their application of Article 101 of the Treaty, but it has no binding force for them’. This reality makes possible the existence of different statements among the different Member States and a confusing perception of what a restriction of competition is. Ultimately, damage on trade between the Member States could be observed for this reason. The main conclusion is that the significant effect on trade between Member States is irrelevant in agreements that restrict competition because of their effects but crucial in agreements that restrict competition because of their object. Thus, the Member States should propose the incorporation of a similar concept in their legal orders in order to apply the content of the Notice. Otherwise, the significance of the restrictive agreement on competition would not be properly assessed.

Keywords: De minimis rule, effect on trade, minor importance agreements, safe harbour

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Authors: Tatsiana Haiden

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The role of the translator in the publishing process has been underestimated for centuries. Any translation is produced in a certain socio-political context by agents with different background, interests, and opinions, i.e., no translation is neutral. Any translation goes beyond the text; it is not only an interlingual transfer of signs but a social phenomenon. The case study shows how Jewish social networks influence publishing translations and aims to explain the unexpected success of the Jewish publishing house in pre-Anschluss Austria. The research shows that translators play a central role (‘Translator’s visibility’ - Pym, ‘Activist turn’ - Wolf, ‘Translator studies’ - Chesterman) in choosing what has to be translated and establishing communication between the author and the publisher. The concept of Translationskultur of Prunc is being historized and applied to the publishing house for the first time by analyzing business correspondence between the main actors of translation (publisher-translator-author). The translation studies project has become interdisciplinary –it encompasses sociology (concepts of Bourdieu’s ‘Field theory’ are used) and history. The historical research method Histoire croiseé is being used to avoid subjectivity and to introduce a new ‘translator-oriented’ vision in translation studies instead of the author-oriented one. In the course of the archival research, it was established that Jewish background plays an essential role in the destiny of the translators and the publishing house, so the Jewish studies have been added to the project. The study goes beyond the Austrian translational culture; it can be used as an example of dealing with publishing houses policies, publishing translations, and translator studies.

Keywords: history of translation, Jewish studies, publishing translations, translation sociology, translator studies, translators as actors

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Authors: Hee-Jung Seo, Yunjung Lee, Areum Han, Heeyoung Park, Se-Hyuk Park

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The purpose of this study was to analyze the relationship between happiness and depression among people with disabilities and to analyze the social phenomenon of leisure activities among them to promote physical and leisure activities for people with disabilities. The research methods included analyzing differences in happiness according to depression classification. A total of 281 people with disabilities were analyzed using SPSS WIN Ver. 29.0. In addition, the SumTrend platform was used to analyze terms related to 'leisure activities for the disabled.' The findings can be summarized into two main points: First, there were significant differences in happiness according to depression classification. Second, there were 20 mentions before COVID-19, 34 mentions after COVID-19, and currently 43 mentions, with high positive rates observed in each period. Based on these results, the following conclusions were drawn: First, measures for people with disabilities include strengthening online resources and services, social distancing response policies, improving accessibility, and providing support and financial assistance. Second, measures for non-disabled individuals emphasize the need for education and information provision, promoting dialogue and interaction, ensuring accessibility, and promoting inclusive cultural awareness and attitude change.

Keywords: leisure activities, individuals with disabilities, COVID-19 pandemic, depression

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Authors: N. Othman, J. Ujang, M. N. Ismail, R. Noordin, B. H. Lim

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Amoebiasis is caused by the Entamoeba histolytica and still endemic in many parts of the tropical region, worldwide. Currently, there is no available vaccine against amoebiasis. Hence, there is an urgent need to develop a vaccine. The excretory secretory antigen (ESA) of E. histolytica is a suitable biomarker for the vaccine candidate since it can modulate the host immune response. Hence, the objective of this study is to identify the proteome of the ESA towards finding suitable biomarker for the vaccine candidate. The non-gel based and gel-based proteomics analyses were performed to identify proteins. Two kinds of mass spectrometry with different ionization systems were utilized i.e. LC-MS/MS (ESI) and MALDI-TOF/TOF. Then, the functional proteins classification analysis was performed using PANTHER software. Combination of the LC -MS/MS for the non-gel based and MALDI-TOF/TOF for the gel-based approaches identified a total of 273 proteins from the ESA. Both systems identified 29 similar proteins whereby 239 and 5 more proteins were identified by LC-MS/MS and MALDI-TOF/TOF, respectively. Functional classification analysis showed the majority of proteins involved in the metabolic process (24%), primary metabolic process (19%) and protein metabolic process (10%). Thus, this study has revealed the proteome the E. histolytica ESA and the identified proteins merit further investigations as a vaccine candidate.

Keywords: E. histolytica, ESA, proteomics, biomarker

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Authors: Yan Zi, Han Xiao

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Across the globe, ICTs are influencing employment both as an industry that creates jobs and as a tool that empowers disabled people to access new forms of work, in innovative and more flexible ways. The advancements in ICT and the number of apps and solutions that support persons with physical, cognitive and intellectual disabilities challenge traditional biased notions and offer a pathway out of traditional sheltered workshops. As the global leader in digital technology innovation, China is arguably a leader in the use of digital technology as a 'lever' in ending the economic and social marginalization of the disabled. This study investigates factors that influence adoption and use of employment-oriented ICT applications among disabled people in China and seeks to integrate three theoretical approaches: the technology acceptance model (TAM), the uses and gratifications (U&G) approach, and the social model of disability. To that end, the study used data from self-reported survey of 214 disabled adults who have been involved in two top-down 'Internet + employment' programs promoted by local disabled persons’ federation in Shanghai. A structural equation model employed in the study demonstrates that the use of employment-oriented ICT applications is affected by demographic factors of gender, categories of disability, education and marital status. The organizational support of local social organizations demonstrates significate effects on the motivations of disabled people. Results from the focus group interviews particularly suggested that to maximize the positive impact of ICTs on employment, there is significant need to build stakeholder capacity on how ICTs could benefits persons with disabilities.

Keywords: disabled people, ICTs, technology acceptance model, uses and gratifications, the social model of disability

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Authors: Kollie B. Dogba, Willis Oluoch-Kosura, Chepchumba Chumo

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In Liberia, many of the agricultural households cultivate cassava for either sustenance purposes, or to generate farm income. Many of the concentrated cassava farmers reside in Nimba, a north-eastern County that borders two other economies: the Republics of Cote D’Ivoire and Guinea. With a high demand for cassava output and products in emerging Asian markets coupled with an objective of the Liberia agriculture policies to increase the competitiveness of valued agriculture crops; there is a need to examine the level of resource-use efficiency for many agriculture crops. However, there is a scarcity of information on the efficiency of many agriculture crops, including cassava. Hence the study applying an output-oriented method seeks to assess the economic efficiency of cassava farmers in Nimba County, Liberia. A multi-stage sampling technique was employed to generate a sample for the study. From 216 cassava farmers, data related to on-farm attributes, socio-economic and institutional factors were collected. The stochastic frontier models, using the Translog functional forms, of production and revenue, were used to determine the level of revenue efficiency and its determinants. The result showed that most of the cassava farmers are male (60%). Many of the farmers are either married, engaged or living together with a spouse (83%), with a mean household size of nine persons. Farmland is prevalently obtained by inheritance (95%), average farm size is 1.34 hectares, and most cassava farmers did not access agriculture credits (76%) and extension services (91%). The mean cassava output per hectare is 1,506.02 kg, which estimates average revenue of L$23,551.16 (Liberian dollars). Empirical results showed that the revenue efficiency of cassava farmers varies from 0.1% to 73.5%; with the mean revenue efficiency of 12.9%. This indicates that on average, there is a vast potential of 87.1% to increase the economic efficiency of cassava farmers in Nimba by improving technical and allocative efficiencies. For the significant determinants of revenue efficiency, age and group membership had negative effects on revenue efficiency of cassava production; while farming experience, access to extension, formal education, and average wage rate have positive effects. The study recommends the setting-up and incentivizing of farmer field schools for cassava farmers to primarily share their farming experiences with others and to learn robust cultivation techniques of sustainable agriculture. Also, farm managers and farmers should consider a fix wage rate in labor contracts for all stages of cassava farming.

Keywords: economic efficiency, frontier production and revenue functions, Nimba County, Liberia, output-oriented approach, revenue efficiency, sustainable agriculture

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Authors: Kuei-Ling Sun, Emily Chia-Yu Su

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Allergy is a hypersensitive overreaction of the immune system to environmental stimuli, and a major health problem. These overreactions include rashes, sneezing, fever, food allergies, anaphylaxis, asthmatic, shock, or other abnormal conditions. Allergies can be caused by food, insect stings, pollen, animal wool, and other allergens. Their development of allergies is due to both genetic and environmental factors. Allergies involve immunoglobulin E antibodies, a part of the body’s immune system. Immunoglobulin E antibodies will bind to an allergen and then transfer to a receptor on mast cells or basophils triggering the release of inflammatory chemicals such as histamine. Based on the increasingly serious problem of environmental change, changes in lifestyle, air pollution problem, and other factors, in this study, we both collect allergens and non-allergens from several databases and use several machine learning methods for classification, including logistic regression (LR), stepwise regression, decision tree (DT) and neural networks (NN) to do the model comparison and determine the permutations of allergen amino acid’s sequence.

Keywords: allergy, classification, decision tree, logistic regression, machine learning

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Authors: Jaishree Ranganathan, MuthuPriya Shanmugakani Velsamy, Shamika Kulkarni, Angelina Tzacheva

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Emotions play an important role in everyday life. An-alyzing these emotions or feelings from social media platforms like Twitter, Facebook, blogs, and forums based on user comments and reviews plays an important role in various factors. Some of them include brand monitoring, marketing strategies, reputation, and competitor analysis. The opinions or sentiments mined from such data helps understand the current state of the user. It does not directly provide intuitive insights on what actions to be taken to benefit the end user or business. Actionable Pattern Mining method provides suggestions or actionable recommendations on what changes or actions need to be taken in order to benefit the end user. In this paper, we propose automatic classification of emotions in Twitter data using Recurrent Neural Network - Gated Recurrent Unit. We achieve training accuracy of 87.58% and validation accuracy of 86.16%. Also, we extract action rules with respect to the user emotion that helps to provide actionable suggestion.

Keywords: emotion mining, twitter, recurrent neural network, gated recurrent unit, actionable pattern mining

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Authors: Yousef Sahari, Eisa Asiri

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Hollywood films are produced in an open and liberal context, and when subtitling for a more conservative and closed society such as an Arabic society, religious words can pose a thorny challenge for subtitlers. Using a corpus of 90 Hollywood films released between 2000 and 2018 and applying insights from Descriptive Translation Studies (Toury, 1995, 2012) and the dichotomy of domestication and foreignization, this paper investigates three main research questions: (1) What are the dominant religious terms and functions in the English subtitles? (2) What are the dominant translation strategies used in the translation of religious words? (3) Do these strategies tend to be SL-oriented or TL-oriented (domesticating or foreignising)? To answer the research questions above, a quantitative and qualitative analysis of the corpus is conducted, in which the researcher adopts a self-designed, parallel, aligned corpus of ninety films and their Arabic subtitles. A quantitative analysis is performed to compare the frequencies and distribution of religious words, their functions, and the translation strategies employed by the subtitlers of ninety films, with the aim of identifying similarities or differences in addition to identifying the impact of functions of religious terms on the use of subtitling strategies. Based on the quantitative analysis, a qualitative analysis is performed to identify any translational patterns in Arabic translations of religious words and the possible reasons for subtitlers’ choices. The results show that the function of religious words has a strong influence on the choice of subtitling strategies. Also, it is found that foreignization strategies are applied in about two-thirds of the total occurrences of religious words.

Keywords: religious terms, subtitling, audiovisual translation, modern standard arabic, subtitling strategies, english-arabic subtitling

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Authors: Ni̇sa Yeni̇kalayci, Türkan Aybi̇ke Akarca

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The ability of correlation the number and space relations, one of the basic scientific process skills, is being used in the transformation of a two-dimensional object into a three-dimensional image or in the expression of symmetry axes of the object. With this research, it is aimed to determine the ability of science students to establish number and space relations. The research was carried out with a total of 90 students studying in the first semester of the Science Education program of a state university located in the Turkey’s Black Sea Region in the fall semester of 2017-2018 academic year. An ‘Integrative Perception Test (IPT)’ was designed by the researchers to collect the data. Within the scope of IPT, the courses and workbooks specific to the field of science were scanned and the ones without symmetrical structure from the visual items belonging to the ‘Physics - Chemistry – Biology’ sub-fields were selected and listed. During the application, it was expected that students would imagine and draw images of the missing half of the visual items that were given incomplete in the first place. The data obtained from the test in which there are 30 images or pictures in total (f Physics = 10, f Chemistry = 10, f Biology = 10) were analyzed descriptively based on the drawings created by the students as ‘complete (2 points), incomplete/wrong (1 point), empty (0 point)’. For the teaching of new concepts in small aged groups, images or pictures showing symmetrical structures and similar applications can also be used.

Keywords: integrative perception, number and space relations, science education, scientific process skills

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Authors: Li Niu, Jihong Liang, Lichao Liu, Huidi Chen

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With the drawing of ancient palace painter, the layout of Beijing famous architect and the lens under photographers, a series of pictures which described whether emperors or ordinary people, whether gardens or Hutongs, whether historical events or life scenarios has emerged into our society. These precious resources are scattered around and preserved in different places Such as organizations like archives and libraries, along with individuals. The research combined decentralized photographic resources with Geographic Information System (GIS), focusing on the figure, event, time and location of the pictures to map them with geographic information in webpage and to display them productively. In order to meet the demand of reality, we designed a metadata description proposal, which is referred to DC and VRA standards. Another essential procedure is to formulate a four-tier classification system to correspond with the metadata proposals. As for visualization, we used Photo Waterfall and Time Line to display our resources in front end. Last but not the least, leading the Web 2.0 trend, the research developed an artistic, friendly, expandable, universal and user involvement platform to show the historical and culture precipitation of Beijing.

Keywords: historical picture, geographic information system, display platform, four-tier classification system

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Authors: Tawfik Thelaidjia, Salah Chenikher

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Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

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Authors: Hsien-Te Lin

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The purpose of this paper is to introduce the BCFES (building carbon footprint evaluation system), which is a LCA (life cycle assessment) tool developed by the Low Carbon Building Alliance (LCBA) in Taiwan. A qualified BCFES for the building industry should fulfill the function of evaluating carbon footprint throughout all stages in the life cycle of building projects, including the production, transportation and manufacturing of materials, construction, daily energy usage, renovation and demolition. However, many existing BCFESs are too complicated and not very designer-friendly, creating obstacles in the implementation of carbon reduction policies. One of the greatest obstacle is the misapplication of the carbon footprint inventory standards of PAS2050 or ISO14067, which are designed for mass-produced goods rather than building projects. When these product-oriented rules are applied to building projects, one must compute a tremendous amount of data for raw materials and the transportation of construction equipment throughout the construction period based on purchasing lists and construction logs. This verification method is very cumbersome by nature and unhelpful to the promotion of low carbon design. With a view to provide an engineer-oriented BCFE with pre-diagnosis functions, a component input/output (I/O) database system and a scenario simulation method for building energy are proposed herein. Most existing BCFESs base their calculations on a product-oriented carbon database for raw materials like cement, steel, glass, and wood. However, data on raw materials is meaningless for the purpose of encouraging carbon reduction design without a feedback mechanism, because an engineering project is not designed based on raw materials but rather on building components, such as flooring, walls, roofs, ceilings, roads or cabinets. The LCBA Database has been composited from existing carbon footprint databases for raw materials and architectural graphic standards. Project designers can now use the LCBA Database to conduct low carbon design in a much more simple and efficient way. Daily energy usage throughout a building's life cycle, including air conditioning, lighting, and electric equipment, is very difficult for the building designer to predict. A good BCFES should provide a simplified and designer-friendly method to overcome this obstacle in predicting energy consumption. In this paper, the author has developed a simplified tool, the dynamic Energy Use Intensity (EUI) method, to accurately predict energy usage with simple multiplications and additions using EUI data and the designed efficiency levels for the building envelope, AC, lighting and electrical equipment. Remarkably simple to use, it can help designers pre-diagnose hotspots in building carbon footprint and further enhance low carbon designs. The BCFES-LCBA offers the advantages of an engineer-friendly component I/O database, simplified energy prediction methods, pre-diagnosis of carbon hotspots and sensitivity to good low carbon designs, making it an increasingly popular carbon management tool in Taiwan. To date, about thirty projects have been awarded BCFES-LCBA certification and the assessment has become mandatory in some cities.

Keywords: building carbon footprint, life cycle assessment, energy use intensity, building energy

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Authors: Jia-Chao Wang

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A model of the universe without invoking space expansion is proposed to explain the observed redshift-distance relation and the cosmic microwave background radiation (CMB). The main hypothesized feature of the model is that photons traveling in space interact with the CMB photon gas. This interaction causes the photons to gradually lose energy through dissipation and, therefore, experience redshift. The interaction also causes some of the photons to be scattered off their track toward an observer and, therefore, results in beam intensity attenuation. As observed, the CMB exists everywhere in space and its photon density is relatively high (about 410 per cm³). The small average energy of the CMB photons (about 6.3×10⁻⁴ eV) can reduce the energies of traveling photons gradually and will not alter their momenta drastically as in, for example, Compton scattering, to totally blur the images of distant objects. An object moving through a thermalized photon gas, such as the CMB, experiences a drag. The cause is that the object sees a blue shifted photon gas along the direction of motion and a redshifted one in the opposite direction. An example of this effect can be the observed CMB dipole: The earth travels at about 368 km/s (600 km/s) relative to the CMB. In the all-sky map from the COBE satellite, radiation in the Earth's direction of motion appears 0.35 mK hotter than the average temperature, 2.725 K, while radiation on the opposite side of the sky is 0.35 mK colder. The pressure of a thermalized photon gas is given by Pγ = Eγ/3 = αT⁴/3, where Eγ is the energy density of the photon gas and α is the Stefan-Boltzmann constant. The observed CMB dipole, therefore, implies a pressure difference between the two sides of the earth and results in a CMB drag on the earth. By plugging in suitable estimates of quantities involved, such as the cross section of the earth and the temperatures on the two sides, this drag can be estimated to be tiny. But for a photon traveling at the speed of light, 300,000 km/s, the drag can be significant. In the present model, for the dissipation part, it is assumed that a photon traveling from a distant object toward an observer has an effective interaction cross section pushing against the pressure of the CMB photon gas. For the attenuation part, the coefficient of the typical attenuation equation is used as a parameter. The values of these two parameters are determined by fitting the 748 µ vs. z data points compiled from 643 supernova and 105 γ-ray burst observations with z values up to 8.1. The fit is as good as that obtained from the lambda cold dark matter (ΛCDM) model using online cosmological calculators and Planck 2015 results. The model can be used to interpret Hubble's constant, Olbers' paradox, the origin and blackbody nature of the CMB radiation, the broadening of supernova light curves, and the size of the observable universe.

Keywords: CMB as the lowest energy state, model of the universe, origin of CMB in a static universe, photon-CMB photon gas interaction

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Authors: Antonio Marques, Graça Guedes

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The Portuguese footwear industry had in the last five years a remarkable performance in the exportation values, the trade balance and others economic indicators. After a long period of difficulties and with a strong reduction of companies and employees since 1994 until 2009, the Portuguese footwear industry changed the strategy and is now a success case between the international players of footwear. Only the Italian industry sells footwear with a higher value than the Portuguese and the distance between them is decreasing year by year. This paper analyses how the Portuguese footwear companies innovate and make innovation, according the classification proposed by the Oslo Manual. Also analyses the strategy follow in the innovation process, as suggested by Freeman and Soete, and shows the linkage between the type of innovation and the strategy of innovation. The research methodology was qualitative and the strategy for data collection was the case study. The qualitative data will be analyzed with the MAXQDA software. The economic results of the footwear companies studied shows differences between all of them and these differences are related with the innovation strategy adopted. The companies focused in product and marketing innovation, oriented to their target market, have higher ratios “turnover per worker” than the companies focused in process innovation. However, all the footwear companies in this “low-tech” industry create value and contribute to a positive foreign trade of 1.310 million euros in 2013. The growth strategies implemented has the participation of the sectorial organizations in several innovative projects. And it’s obvious that cooperation between all of them is a critical element to the performance achieved by the companies and the innovation observed. Can conclude that the Portuguese footwear sector has in the last years an excellent performance (economic results, exportation values, trade balance, brands and international image) and his performance is strongly related with the strategy in innovation followed, the type of innovation and the networks in the cluster. A simplified model, called “Ace of Diamonds”, is proposed by the authors and explains the way how this performance was reached by the seven companies that participate in the study (two of them are the leaders in the setor), and if this model can be used in others traditional and “low-tech” industries.

Keywords: footwear, innovation, “low-tech” industry, Oslo manual

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Authors: Anthoni Jeorge

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Throughout the history of the world, servant leadership has been researched, and favourable results such as individual, team, and organizational have been linked to the construct. This research paper designates St. Camillus de Lellis, a practitioner of servant leadership and founder of the Ministers of the Sick as a servant leader in his approach to care for the sick. Service is the visible face of his servant leadership. First of all, despite many challenges, St. Camillus de Lellis practiced leadership by the example of compassionate service to the sick. Second, he made service to the sick the highest priority of his life. Third, Camillus displayed servant leadership such that his manner of leadership gave birth to a New School of Service to the Sick. The paper identifies the distinctive dimensions and essential elements which characterized his service-centered leadership. Furthermore, discuss the six major characteristics of a servant leader as set forth by St. Camillus’s life example. The research illustrates the transformational power of servant leadership infield healthcare in general and, in doing so, provides servant leadership seekers ways servant leadership can transform elder care in one’s own field (St. Camillus Health Systems). Thus, it ascertains that servant leadership is best-fit for humanized elder care. Supported by the review of literature, the paper ascertains that Camillus, by identifying himself with the sick, gained deeper insights concerning the pain and suffering of the population. Uniquely drawn from his true grit, Camillus’ service-centered leadership is value-based, people-oriented, and compassion-filled. His way of service to the sick is the prolongation of gestures of mercy and compassion. It is hoped that the results of this study will help health care workers and servant leadership practitioners to humanize elder care and cultivate servant leadership attitude in their health care services to the sick. By incorporating such service-oriented elements into their leadership orientation, health care workers will be true servant leaders of the sick.

Keywords: leadership, service, healthcare, compassion

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Ling Qi, Matloob Khushi, Josiah Poon

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This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.

Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning

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Authors: Chin-Hsiang Chu

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This article review the literature in the field among the marketing and aesthetics, the current market and customer-oriented product sales, and gradually from the practical functionality, transformed into the visual appearance of the concept note and the importance of marketing experience substance 'economic Aesthetics' trend. How to introduce the concept of aesthetic and differentiate products have become an important content of marketing management in for an organization in marketing.In previous studies,marketing aesthetic related researches are rare.Therefore, the purpose of this study to explore the connection between aesthetics and marketing of the market economy, and aggregated content through literature review, trying to find related research implications for the management of marketing aesthetics, market-oriented and customer value and development of the product. In this study, the problem statement and background, the development of the theory of evolution, as well as methods and results of discovery stage, literature review was conducted to explore. The results found: (1) Study of Aesthetics will help deepen the shopping environment and service environment commonly understood. (2) the perceived value of products imported aesthetic, consumer willingness to buy, and even premium products will be more attractive. (3) marketing personnel for general marketing management with a high degree of aesthetic identity. (4) management in marketing aesthetics connotation, aesthetic characteristics of five elements is greatly valued by the real-time, complex, specificity, attract sexual and richness. (5) allows consumers to experience through the process due to stimulate the senses, the mind and thinking with the corporate brand or have a deeper link. Results of this study can be used as business in a competitive market, new product development and design of the guide.

Keywords: marketing aesthetics, aesthetics economic, aesthetic, experiential marketing

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Authors: Haruya Tamaki, Tsugunosuke Sakai, Ryuichi Yoshida, Ryohei Egusa, Shigenori Inagaki, Etsuji Yamaguchi, Fusako Kusunoki, Miki Namatame, Masanori Sugimoto, Hiroshi Mizoguchi

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Art appreciation is important as part of children education. Art appreciation can enrich sensibility and creativity. To enrich sensibility and creativity, the children have to learning knowledge of picture such as social and historical backgrounds and author intention. High learning effect can acquire by actively learning. In short, it is important that encourage learning of the knowledge about pictures actively. It is necessary that children feel like interest to encourage learning of the knowledge about pictures actively. In a general art museum, comments on pictures are done through writing. Thus, we expect that this method cannot arouse the interest of the children in pictures, because children feel like boring. In brief, learning about the picture information is difficult. Therefore, we are developing an art-appreciation support system that will encourage learning of the knowledge about pictures actively by children feel like interest. This system uses that Interacting with Pictures to learning of the knowledge about pictures. To Interacting with Pictures, children have to utterance by themselves. We expect that will encourage learning of the knowledge about pictures actively by Interacting with Pictures. To more actively learning, children can choose who talking with by information that location and movement of the children. This system must be able to acquire real-time knowledge of the location, movement, and voice of the children. We utilize the Microsoft’s Kinect v2 sensor and its library, namely, Kinect for Windows SDK and Speech Platform SDK v11 for this purpose. By using these sensor and library, we can determine the location, movement, and voice of the children. As the first step of this system, we developed ukiyo-e game that use ukiyo-e to appreciation object. Ukiyo-e is a traditional Japanese graphic art that has influenced the western society. Therefore, we believe that the ukiyo-e game will be appreciated. In this study, we applied talking to pictures to learn information about the pictures because we believe that learning information about the pictures by talking to the pictures is more interesting than commenting on the pictures using only texts. However, we cannot confirm if talking to the pictures is more interesting than commenting using texts only. Thus, we evaluated through EDA measurement whether the user develops an interest in the pictures while talking to them using voice recognition or by commenting on the pictures using texts only. Hence, we evaluated that children have interest to picture while talking to them using voice recognition through EDA measurement. In addition, we quantitatively evaluate that enjoyed this game or not and learning information about the pictures for primary schoolchildren. In this paper, we summarize these two evaluation results.

Keywords: actively learning, art appreciation, EDA, Kinect V2

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Authors: Zbigniew Czyz, Krzysztof Skiba, Miroslaw Wendeker

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This paper discusses the results of aerodynamic investigation of the Tajfun gyroplane body designed by a Polish company, Aviation Artur Trendak. This gyroplane has been studied as a 1:8 scale model. Scaling objects for aerodynamic investigation is an inherent procedure in any kind of designing. If scaling, the criteria of similarity need to be satisfied. The basic criteria of similarity are geometric, kinematic and dynamic. Despite the results of aerodynamic research are often reduced to aerodynamic coefficients, one should pay attention to how values of coefficients behave if certain criteria are to be satisfied. To satisfy the dynamic criterion, for example, the Reynolds number should be focused on. This is the correlation of inertial to viscous forces. With the multiplied flow speed by the specific dimension as a numerator (with a constant kinematic viscosity coefficient), flow speed in a wind tunnel research should be increased as many times as an object is decreased. The aerodynamic coefficients specified in this research depend on the real forces that act on an object, its specific dimension, medium speed and variations in its density. Rapid prototyping with a 3D printer was applied to create the research object. The research was performed with a T-1 low-speed wind tunnel (its diameter of the measurement volume is 1.5 m) and a six-element aerodynamic internal scales, WDP1, at the Institute of Aviation in Warsaw. This T-1 wind tunnel is low-speed continuous operation with open space measurement. The research covered a number of the selected speeds of undisturbed flow, i.e. V = 20, 30 and 40 m/s, corresponding to the Reynolds numbers (as referred to 1 m) Re = 1.31∙106, 1.96∙106, 2.62∙106 for the angles of attack ranging -15° ≤ α ≤ 20°. Our research resulted in basic aerodynamic characteristics and observing the impact of undisturbed flow speed on the correlation of aerodynamic coefficients as a function of the angle of attack of the gyroplane body. If the speed of undisturbed flow in the wind tunnel changes, the aerodynamic coefficients are significantly impacted. At speed from 20 m/s to 30 m/s, drag coefficient, Cx, changes by 2.4% up to 9.9%, whereas lift coefficient, Cz, changes by -25.5% up to 15.7% if the angle of attack of 0° excluded or by -25.5% up to 236.9% if the angle of attack of 0° included. Within the same speed range, the coefficient of a pitching moment, Cmy, changes by -21.1% up to 7.3% if the angles of attack -15° and -10° excluded or by -142.8% up to 618.4% if the angle of attack -15° and -10° included. These discrepancies in the coefficients of aerodynamic forces definitely need to consider while designing the aircraft. For example, if load of certain aircraft surfaces is calculated, additional correction factors definitely need to be applied. This study allows us to estimate the discrepancies in the aerodynamic forces while scaling the aircraft. This work has been financed by the Polish Ministry of Science and Higher Education.

Keywords: aerodynamics, criteria of similarity, gyroplane, research tunnel

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Authors: Zheng Yi

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Among the attempts made worldwide to foster urban and transport sustainability, transit-oriented development certainly is one of the most successful. Residents' travel behavior is a concern in the researches about the impacts of transit-oriented development. The study takes 620 English journal papers in the core collection database of Web of Science as the study objects; the paper tries to map out the scientific knowledge mapping in the field and draw the basic conditions by co-citation analysis, co-word analysis, a total of citation network analysis and visualization techniques. This study teases out the research hotspots and evolution of the relationship between urban rail transit and resident's travel behavior from 1999 to 2019. According to the results of the analysis of the time-zone view and burst-detection, the paper discusses the trend of the next stage of international study. The results show that in the past 20 years, the research focuses on these keywords: land use, behavior, model, built environment, impact, travel behavior, walking, physical activity, smart card, big data, simulation, perception. According to different research contents, the key literature is further divided into these topics: the attributes of the built environment, land use, transportation network, transportation policies. The results of this paper can help to understand the related researches and achievements systematically. These results can also provide a reference for identifying the main challenges that relevant researches need to address in the future.

Keywords: urban rail transit, travel behavior, knowledge map, evolution of researches

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

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Authors: David Pham, Yongfeng Zhang

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Graphs are an important structure for data storage and computation. Recent years have seen the success of deep learning on graphs such as Graph Neural Networks (GNN) on various data mining and machine learning tasks. However, most of the deep learning models on graphs cannot easily explain their predictions and are thus often labelled as “black boxes.” For example, Graph Attention Network (GAT) is a frequently used GNN architecture, which adopts an attention mechanism to carefully select the neighborhood nodes for message passing and aggregation. However, it is difficult to explain why certain neighbors are selected while others are not and how the selected neighbors contribute to the final classification result. In this paper, we present a graph learning model called Explainable Graph Attention Network (XGAT), which integrates graph attention modeling and explainability. We use a single model to target both the accuracy and explainability of problem spaces and show that in the context of graph attention modeling, we can design a unified neighborhood selection strategy that selects appropriate neighbor nodes for both better accuracy and enhanced explainability. To justify this, we conduct extensive experiments to better understand the behavior of our model under different conditions and show an increase in both accuracy and explainability.

Keywords: explainable AI, graph attention network, graph neural network, node classification

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Authors: Joseph Wolff, Jeffrey Eilbott

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Autism Spectrum Disorders (ASD) are a spectrum of social disorders characterized by deficits in social communication, verbal ability, and interaction that can vary in severity. In recent years, researchers have used magnetic resonance imaging (MRI) to help detect how neural patterns in individuals with ASD differ from those of neurotypical (NT) controls for classification purposes. This study analyzed the classification of ASD within males and females using functional MRI data. Functional connectivity (FC) correlations among brain regions were used as feature inputs for machine learning algorithms. Analysis was performed on 558 cases from the Autism Brain Imaging Data Exchange (ABIDE) I dataset. When trained specifically on females, the algorithm underperformed in classifying the ASD subset of our testing population. Although the subject size was relatively smaller in the female group, the manual matching of both male and female training groups helps explain the algorithm’s bias, indicating the altered sex abnormalities in functional brain networks compared to typically developing peers. These results highlight the importance of taking sex into account when considering how generalizations of findings on males with ASD apply to females.

Keywords: autism spectrum disorder, machine learning, neuroimaging, sex differences

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