Search results for: categorizing TD

Authors: Blessing Igbadumhe

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The continuous long- and short-term delivery of value to customers continues to be the overarching objective of software organizations. Software engineering professionals and organizations face challenges in the maintenance and evolution of software as a result of architectural, technical debt. The issues of architectural, technical debt continue to receive a significant amount of attention because of its important impact on successful system implementation. The cost of doing nothing as far as architectural, technical debt is concerned can be significant both in financial terms and impacts on customers. Different architectural, technical debt issues exist, and this qualitative research design reviewed existing literature on the subject to identify and categorize them. This research intends to contribute to the existing bludgeoning body of knowledge on categorizations and descriptive model of technical debt related issues related to system architecture. The results identify the most common characteristics of architectural and technical debt categories. Raising awareness of the intricacies of architectural and technical debt helps technology stakeholders reduce negative consequences and increase the system success rate.

Keywords: architecture, categorizing TD, system design, technical debt

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Authors: Yukiko Sasaki Alam

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This research aims at finding out the causes that led to wrong lexical selections in machine translation (MT) rather than categorizing lexical errors, which has been a main practice in error analysis. By manually examining and analyzing lexical errors outputted by a MT system, it suggests what knowledge would help the system reduce lexical errors.

Keywords: machine translation, error analysis, lexical errors, evaluation

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Authors: Ahmet Karakuş, Akif Can Kilic, Emre Alptekin

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A growing number of studies have been conducted to determine how well-being may be predicted using well-designed models. It is necessary to investigate the backgrounds of features in order to construct a viable Subjective Well-Being (SWB) model. We have picked the suitable variables from the literature on SWB that are acceptable for real-world data instructions. The goal of this work is to evaluate the model by feeding it with SWB characteristics and then categorizing the stress levels using machine learning methods to see how well it performs on a real dataset. Despite the fact that it is a multiclass classification issue, we have achieved significant metric scores, which may be taken into account for a specific task.

Keywords: machine learning, multiclassification problem, subjective well-being, perceived stress scale

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Authors: Dongjoo Kim, Chang-Sik Son, Won-Seok Kang

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Adequate sleep affects various parts of one’s overall physical and mental life. As one of the methods in determining the appropriate amount of sleep, this research presents a heart rate based sleep quality index. In order to evaluate sleep quality using the heart rate, sleep data from 280 subjects taken over one month are used. Their sleep data are categorized by a three-part heart rate range. After categorizing, some features are extracted, and the statistical significances are verified for these features. The results show that some features of this sleep quality index model have statistical significance. Thus, this heart rate based sleep quality index may be a useful discriminator of sleep.

Keywords: sleep, sleep quality, heart rate, statistical analysis

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Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

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The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

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Authors: Ilango Thiagalingam, Erwann Yvin, Gabriel Crehan, Roch El Khoury

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An experimental investigation is carried out in order to evaluate the relevance of a customization approach of the passive thermal mannikin. The promise of this approach consists in the following assumption: physiological differences lead to distinct thermo-physiological responses that explain a part of the thermal appraisal differences between people. Categorizing people and developing an appropriate thermal mannikin for each group would help to reduce the actual dispersion on the subjective thermal comfort perception. The present investigation indicates that popular passive physiological diversity drivers such as sex, age and BMI are not the correct parameters to consider. Indeed, very little or no discriminated global thermo-physiological responses arise from the physiological classification of the population using these parameters.

Keywords: thermal comfort, thermo-physiology, customization, thermal mannikin

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Authors: Afaf Alharbi, Qianni Zhang

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The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper introduces a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple-instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation of an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: attention multiple instance learning, MIL and transfer learning, histopathological slides, cancer tissue classification

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Authors: Manal M. H. Said Najjar

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Arab Grammarians stood at variance with regard to the definition of kana (which might equal was, were, the past form of “be” in English). Kana was considered as a verb, a particle, or a quasi-verb by different scholars; others saw it as an auxiliary verb; while some other scholars categorized kana as one of the incomplete verbs or (Afa’al naqisa) based on two different claims: first, a considerable group of grammarians saw kana as fie’l naqis or an incomplete verb since it indicates time, but not the event or action itself. Second, kana requires a predicate (xabar) to complete the meaning, i.e., it does not suffice itself with a noun in the nominal sentence. This study argues that categorizing the verb kana as fie’l naqis or an incomplete verb is inaccurate and confusing since the term “incomplete” does not agree with its characteristics, meanings, and temporal indications. Moreover, interpreting kana as a past verb is also inaccurate. kana كان (derived from the absolute action of being كون) is considered unique and the most comprehensive verb, encompassing all tenses of the past, present, and future within the dimensions of continuity and eternity of all possible actions under “being”.

Keywords: pragmatics, kana, context, Arab grammarians, meaning, fie’l naqis

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Authors: Smko Zangana, Ergun Ercelebi

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The alternating current is the main power in all industries and other aspects especially for the short and mid distances, but as far as long a distance which exceeds 500 KMs, using the alternating current technically will face many difficulties and more costs because it's difficult to control the current and also other restrictions. Therefore, recently those reasons led to building transmission lines HVDC to transmit power for long distances. This document presents technical comparison and assessments for power transmission system among distances either ways and studying the stability of the system regarding the proportion of losses in the actual power sent and received between both sides in different systems and also categorizing filters used in the HVDC system and its impact and effect on reducing Harmonic in the power transmission. MATLAB /Simulink simulation software is used to simulate both HVAC & HVDC power transmission system topologies.

Keywords: HVAC power system, HVDC power system, power system simulation (MATLAB), the alternating current, voltage stability

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Authors: Hong-Nam Choi, Hyeong-Wook Song, Sungwan Hong, Hong-Kyu Kim

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In Korea, elements that decide the quality of residential environment are not only diverse, but show deviation as well. However, people do not consider these elements and instead, they try to settle the uniformed style of residential environment, which focuses on the construction development of apartment housing and business based plans. Recently, block-unit redevelopment is becoming the standout alternative plan of standardize redevelopment projects, but constructions become inefficient because of indefinite planning criteria. In conclusion, the following research is about analyzing and categorizing the development method and legal ground of redevelopment project district, plan determinant and applicable standard. The purpose of this study is to become a basis in compatible analysis of planning standards that will happen in the future.

Keywords: shape restrictions, improvement of regulation, diversity of residential environment, classification of redevelopment project, planning criteria of redevelopment, special architectural district (SAD)

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Authors: Anyia Nduka, Aslan Bin Amad Senin, Ayu Azrin Binti Abdul Aziz

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Telemedicine is a rapidly developing discipline with enormous promise for better healthcare results for patients. To meet the demands of patients and the healthcare sector, medical providers must be proficient in telemedicine and also need government funding for infrastructure and core competencies. In this study, we surveyed general hospitals in Kuala Lumpur and Selangor to investigate patient’s impressions of both the positive and negative aspects of government funding for telemedicine and its level of acceptance. This survey was conducted in accordance with the Diffusion of Innovations (DOI) hypothesis; the survey instruments were designed through a Google Form and distributed to patients and every member of the medical team. The findings suggested a framework for categorizing patients' levels of technology use and acceptability, which provided practical consequences for healthcare. We therefore recommend the increase in technical assistance and government-backed funding of telemedicine by bolstering the entire system.

Keywords: technology acceptance, quality assurance, digital transformation, cost management.

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Authors: Jiyoung Bae, Gyoomi Kim

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This study explores a range of linguistic features used in Korean college students’ argumentative writings for the purpose of developing a model that identifies variables which predict writing proficiencies. This study investigated the latent variable structure of L2 linguistic features, including syntactic complexity, the lexical complexity, and fluency. One hundred forty-six university students in Korea participated in this study. The results of the study’s confirmatory factor analysis (CFA) showed that indicators of linguistic features from this study-provided a foundation for re-categorizing indicators found in extant research on L2 Korean writers depending on each latent variable of linguistic features. The CFA models indicated one measurement model of L2 syntactic complexity and L2 learners’ writing proficiency; these two latent factors were correlated with each other. Based on the overall findings of the study, integrated linguistic features of L2 writings suggested some pedagogical implications in L2 writing instructions.

Keywords: linguistic features, syntactic complexity, lexical complexity, fluency

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Authors: Girma Yohannis Bade, Olga Kolesnikova, Grigori Sidorov

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Named entity recognition (NER) is a building block for information extraction. Though the information extraction process has been automated using a variety of techniques to find and extract a piece of relevant information from unstructured documents, the discovery of targeted knowledge still poses a number of research difficulties because of the variability and lack of structure in Web data. NER, a subtask of information extraction (IE), came to exist to smooth such difficulty. It deals with finding the proper names (named entities), such as the name of the person, country, location, organization, dates, and event in a document, and categorizing them as predetermined labels, which is an initial step in IE tasks. This survey paper presents the roles and importance of NER to IE from the perspective of different algorithms and application area domains. Thus, this paper well summarizes how researchers implemented NER in particular application areas like finance, medicine, defense, business, food science, archeology, and so on. It also outlines the three types of sequence labeling algorithms for NER such as feature-based, neural network-based, and rule-based. Finally, the state-of-the-art and evaluation metrics of NER were presented.

Keywords: the role of NER, named entity recognition, information extraction, sequence labeling algorithms, named entity application area

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Authors: Marylene N. Tizon

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English instructors pay attention on errors committed by students as errors show whether they know or master their oral skills and what difficulties they may have in the process of learning the English language. This descriptive quantitative study aimed at identifying and categorizing the oral presentation errors of the purposively chosen 118 English 2A students enrolled during the first semester of school year 2013 – 2014. The analysis of the data for this study was undertaken using the errors committed by the students in their presentation. Marking and classifying of errors were made by first classifying them into linguistic grammatical errors then all errors were categorized further into Surface Structure Errors Taxonomy with the use of Frequency and Percentage distribution. From the analysis of the data, the researcher found out: Errors in tenses of the verbs (71 or 16%) and in addition 167 or 37% were most frequently uttered by the students. And Question and negation mistakes (12 or 3%) and misordering errors (28 or 7%) were least frequently enunciated by the students. Thus, the respondents in this study most frequently enunciated errors in tenses and in addition while they uttered least frequently the errors in question, negation, and misordering.

Keywords: grammatical error, oral presentation error, surface structure errors taxonomy, descriptive quantitative design, Philippines, Asia

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Authors: Joung Hyoun Lee

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Intransitive verbs consist of two subclasses called unergatives and unaccusatives. However, traditionally Italian intransitive verbs have been taught regardless their semantic distinctions and any mention of grammatical terms such as unaccusatives and unergatives even though there is a huge gap between them. This paper aims to explore the teaching of Italian intransitive verbs categorizing them into unaccusatives and unergatives, which is compared with researches on the teaching of English unaccusative and unergative verbs. For this purpose, first, the study analyses various aspects of English vs. Italian unergatives and unaccusatives, and their properties of the constructions. Next, this study highlights the research trend on Korean students' learning errors, which is leaning toward causal analyses of the over passivization of English unaccusative verbs. In order to investigate these issues, 53 students of the Busan University of Foreign Studies, who are studying Italian language as a second language, were surveyed through a grammaticality judgment test divided into 9 sections. As expected, the findings confirmed that the test results of Italian unaccusatives and unergatives showed similar and different aspects comparing to those of English. Moreover, there was a highly affirmative demand for a more careful way of teaching which should be considered both syntactically and semantically according to the grammatical items. The research provides a framework of a more effective and systematic teaching method of Italian intransitive verbs for further research.

Keywords: unaccusative verbs, unergative verbs, agent, patient, theme, overpassivization

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Authors: Angelis P. Barlampas

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Target: The (SARS-CoV-2) is still a threat. AI software could be useful, categorizing the disease into different severities and indicate the extent of the lesions. Materials and methods: AI is a new revolutionary technique, which uses powered computerized systems, to do what a human being does more rapidly, more easily, as accurate and diagnostically safe as the original medical report and, in certain circumstances, even better, saving time and helping the health system to overcome problems, such as work overload and human fatigue. Results: It will be given an effort to describe to the inexperienced reader (see figures), as simple as possible, how an artificial intelligence system diagnoses computed tomography pictures. First, the computerized machine learns the physiologic motives of lung parenchyma by being feeded with normal structured images of the lung tissue. Having being used to recognizing normal structures, it can then easily indentify the pathologic ones, as their images do not fit to known normal picture motives. It is the same way as when someone spends his free time in reading magazines with quizzes, such as <> and <>. General conclusion: The AI mimics the physiological processes of the human mind, but it does that more efficiently and rapidly and provides results in a few seconds, whereas an experienced radiologist needs many days to do that, or even worse, he is unable to accomplish such a huge task.

Keywords: covid-19, artificial intelligence, automated imaging, CT, chest imaging

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Authors: Christina Kalogirou

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Investigating the integration of bioclimatic design into vernacular architecture could lead to interesting results regarding the preservation of cultural heritage while enhancing the energy efficiency of historic buildings. Furthermore, these recognized principles and systems of bioclimatic design in vernacular settlements could be applied to modern architecture and thus to new buildings in such areas. This study introduces an approach to categorizing distinct technologies and design principles of bioclimatic design based on a thoughtful approach to various climatic zones and environment in Greece (mountainous areas, islands and lowlands). For this purpose, various types of dwellings are evaluated for their response to climate, regarding the layout of the buildings (orientation, floor plans’ shape, semi-open spaces), the site planning, the openings (size, position, protection), the building envelope (walls: construction materials-thickness, roof construction detailing) and the migratory living pattern according to seasonal needs. As a result, various passive design principles (that could be adapted to current architectural practice in such areas, in order to optimize the relationship between site, building, climate and energy efficiency) are proposed.

Keywords: bioclimatic design, buildings physics, climatic zones, energy efficiency, vernacular architecture

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Authors: Chamindi Dilkushi Senaratne

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Communicating via a text or an SMS (Short Message Service) has become an integral part of our daily lives. With the increase in the use of mobile phones, text messaging has become a genre by itself worth researching and studying. It is undoubtedly a major phenomenon revealing language change. This paper attempts to describe the morphological processes of text language of urban bilinguals in Sri Lanka. It will be a typological study based on 500 English text messages collected from urban bilinguals residing in Colombo. The messages are selected by categorizing the deviant forms of language use apparent in text messages. These stylistic deviations are a deliberate skilled performance by the users of the language possessing an in-depth knowledge of linguistic systems to create new words and thereby convey their linguistic identity and individual and group solidarity via the message. The findings of the study solidifies arguments that the manipulation of language in text messages is both creative and appropriate. In addition, code mixing theories will be used to identify how existing morphological processes are adapted by bilingual users in Sri Lanka when texting. The study will reveal processes such as omission, initialism, insertion and alternation in addition to other identified linguistic features in text language. The corpus reveals the most common morphological processes used by Sri Lankan urban bilinguals when sending texts.

Keywords: bilingual, deviations, morphology, texts

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Authors: Aditya Karade, Sharada Falane, Dhananjay Deshmukh, Vijaykumar Mantri

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Brain tumors pose a significant challenge in healthcare due to their complex nature and impact on patient outcomes. The application of deep learning (DL) algorithms in medical imaging have shown promise in accurate and efficient brain tumour detection. This paper explores the performance of various pre-trained DL models ResNet50, Xception, InceptionV3, EfficientNetB0, DenseNet121, NASNetMobile, VGG19, VGG16, and MobileNet on a brain tumour dataset sourced from Figshare. The dataset consists of MRI scans categorizing different types of brain tumours, including meningioma, pituitary, glioma, and no tumour. The study involves a comprehensive evaluation of these models’ accuracy and effectiveness in classifying brain tumour images. Data preprocessing, augmentation, and finetuning techniques are employed to optimize model performance. Among the evaluated deep learning models for brain tumour detection, ResNet50 emerges as the top performer with an accuracy of 98.86%. Following closely is Xception, exhibiting a strong accuracy of 97.33%. These models showcase robust capabilities in accurately classifying brain tumour images. On the other end of the spectrum, VGG16 trails with the lowest accuracy at 89.02%.

Keywords: brain tumour, MRI image, detecting and classifying tumour, pre-trained models, transfer learning, image segmentation, data augmentation

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Authors: Lama Ajinah

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Luxury brands witnessed continuous growth which followed women’s desire towards individual distinctiveness and social glare. Bags are a woman’s best friend either for aesthetic or functional purposes when she leaves her home for leisure or work. One way of women constant aspiration for being distinguished while reflecting their wealth is through handbags. Subsequently, the demand and attraction by consumers towards the dazzle of luxurious brands for personal pleasure and social status have flourished. According to the literature review, a visual analysis on luxury brands has been explored yet a focus on bags was not discussed in details. Hence, a deep analysis will be dedicated on the two segments by showcasing examples of high-end bag advertising. The research is conducted to understand advertising strategies used in promoting for luxurious products. Furthermore, the paper explores the definition of the term luxury, the condition in which it is used in, and the visual language used along with the term. As luxury is an indicator of superior satisfaction, it is obtained on two levels: a personal and a social level. The examples of luxury brand ads are selected from the last five years to uncover the latest, most common strategies used to promote for luxurious brands. The methods employed in this paper consist of literature review, semiotic analysis, and content analysis. The researcher concludes with revealing the methods used in advertising while categorizing them into various themes.

Keywords: advertising, brands, fashion, graphic design, luxury, semiotic analysis, semiology, visual analysis, visual communication

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Authors: Fitri CaturLestari

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According to National Population and Family Planning Board (BKKBN), demographic bonus will occur in 2025-2035, when the number of people within the productive age bracket is higher than the number of elderly people and children. This time will be a gold moment for Indonesia to achieve maximum productivity and prosperity. But it will be a demographic bomb if it isn’t balanced by economic and social aspect considerations. Therefore it is important to make a prediction mapping of all provinces in Indonesia whether in demographic bomb or bonus condition after 100 years Indonesian independence. The purpose of this research were to make the demographic mapping based on the economic and social aspects of the provinces in Indonesia and categorizing them into demographic bomb and bonus condition. The research data are gained from Statistics Indonesia (BPS) as the secondary data. The multiregional component method, regression and quadrant analysis were used to predict the number of people, economic growth, Human Development Index (HDI), and gender equality in education and employment. There were different characteristic of provinces in Indonesia from economic aspect and social aspect. The west Indonesia was already better developed than the east one. The prediction result, many provinces in Indonesia will get demographic bonus but the others will get demographic bomb. It is important to prepare particular strategy to particular provinces with all of their characteristic based on the prediction result so the demographic bomb can be minimalized.

Keywords: demography, economic growth, gender, HDI

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Authors: S. Chabbak

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In a widely globalized world, the influence of audiovisual translation on the culture and identity of audiences is unmistakable. However, in the Arab World, there is a noticeable disproportion between this growing influence and the research carried out in the field. As a matter of fact, the voiced-over documentary is one of the most abundantly translated genres in the Arab World that carries lots of ideological elements which are in many cases rendered by manipulation. However, voiced-over documentaries have hardly received any focused attention from researchers in the Arab World. This paper attempts to scrutinize the process of translation of voiced-over documentaries in the Arab World, from French into Arabic in the present case study, by sub-categorizing the ideological items subject to manipulation, identifying the techniques utilized in their translation and exploring the potential extra-linguistic factors that prompt translation agents to opt for manipulative translation. The investigation is based on a corpus of 94 episodes taken from a series entitled 360° GEO Reports, produced by the French German network ARTE in French, and acquired, translated and aired by Al Jazeera Documentary Channel for Arab audiences. The results yielded 124 cases of manipulation in four sub-categories of ideological items, and the use of 10 different oblique procedures in the process of manipulative translation. The study also revealed that manipulation is in most of the instances dictated by the editorial line of the broadcasting channel, in addition to the religious, geopolitical and socio-cultural peculiarities of the target culture.

Keywords: audiovisual translation, ideological items, manipulation, voiced-over documentaries

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Authors: Melody Yin

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Concussions impact a large amount of adolescents; they make up as much as half of the diagnosed concussions in America. This research proposes a hybrid machine learning model based on the combination of human/knowledge-based domains and computer-generated feature rankings to improve the accuracy of diagnosing sports related concussion (SRC). Using a data set of symptoms collected on the sideline post-SRC events, the symptom selection criteria method has been developed by using Google AutoML's important score function to identify the top 10 symptom features. In addition, symptom domains have been introduced as another parameter, categorizing the symptoms into physical, cognitive, sleep, and emotional domains. The hybrid machine learning model has been trained with a combination of the top 10 symptoms and 4 domains. From the results, the hybrid model was the best performer for symptom resolution time prediction in 2 and 4-week thresholds. This research is a proof of concept study in the use of domains along with machine learning in order to improve concussion prediction accuracy. It is also possible that the use of domains can make the model more efficient due to reduced training time. This research examines the use of a hybrid method in predicting sports-related concussion. This achievement is based on data preprocessing, using a hybrid method to select criteria to achieve high performance.

Keywords: hybrid model, machine learning, sports related concussion, symptom resolution time

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Authors: Ming Liu, Chong Wu, Bingquan Liu, Lei Chen

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Internet users have to face the massive amount of textual data every day. Organizing texts into categories can help users dig the useful information from large-scale text collection. Clustering, in fact, is one of the most promising tools for categorizing texts due to its unsupervised characteristic. Unfortunately, most of traditional clustering algorithms lose their high qualities on large-scale text collection. This situation mainly attributes to the high- dimensional vectors generated from texts. To effectively and efficiently cluster large-scale text collection, this paper proposes a vector reconstruction based clustering algorithm. Only the features that can represent the cluster are preserved in cluster’s representative vector. This algorithm alternately repeats two sub-processes until it converges. One process is partial tuning sub-process, where feature’s weight is fine-tuned by iterative process. To accelerate clustering velocity, an intersection based similarity measurement and its corresponding neuron adjustment function are proposed and implemented in this sub-process. The other process is overall tuning sub-process, where the features are reallocated among different clusters. In this sub-process, the features useless to represent the cluster are removed from cluster’s representative vector. Experimental results on the three text collections (including two small-scale and one large-scale text collections) demonstrate that our algorithm obtains high quality on both small-scale and large-scale text collections.

Keywords: vector reconstruction, large-scale text clustering, partial tuning sub-process, overall tuning sub-process

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Authors: Hsiao-Yung Wang

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This essay aims to examine how the discursive formation of the 'transing-nationalism' (which is extended and slightly modified from 'homonationalism') had been constructed in the Taiwanese news media before the legalization of 'sex reassignment surgery (SRS)' in 1988. Samples for rhetorical analysis were selected from two mainstream newspapers, including China Times, and United Daily. The time frame for sample selection is from August 1953 (when the first transgender case was reported) to 1988, while the SRS was legalized in Taiwan. To enhance understanding of media representation as contextualized-based, the author refers to the representative of spatial rhetoric Mikhail Bakhtin for his late study on 'emergence' and 'visualization of time' in Bildungsroman; thereby categorizing the media discourse of transgender into two critical period: (1) transgender as 'misrecognized' and 'included' into the rhetoric of modern medical space; (2) transgender as 'institutionalized' into discourse of protection and salvation by the reified sympathy of nation-state. These two periods and relevant spatial rhetoric were of no immediate concern on the vital interest of transgender individuals; therefore constructed the imagery of transgender for the service of nationalism rather than gender consciousness or human right rhetoric. Based on the research findings, this essay concludes that 'queer multiplicity' should be regarded as not only the guideline for the amendment of the gendered policies and laws but the rhetorical resources for the mobilization of transgender movement in Taiwan from now on.

Keywords: Bakhtin, legalization, rhetoric, sex reassignment surgery, transgender, transing-nationalism

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Authors: Phornchanok Motantasut, Torkamol Hunsawong, Lugkana Mato, Wanida Donpunha

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Identifying abnormal foot posture is important for prescribing appropriate management in patients with lower limb disorders and chronic non-specific low back pain. The normalized navicular height truncated (NNHt) and the foot posture index-6 (FPI-6) have been recommended as the common, simple, valid, and reliable static measures for clinical application. The NNHt is a single plane measure while the FPI-6 is a triple plane measure. At present, there is inadequate information about the correlation between the NNHt and the FPI-6 for categorizing foot posture that leads to a difficulty of choosing the appropriate assessment. Therefore, the present study aimed to determine the correlation between the NNHt and the FPI-6 measures in adult participants with asymptomatic feet. Methods: A cross-sectional descriptive study was conducted in 47 asymptomatic individuals (23 males and 24 females) aged 28.89 ± 7.67 years with body mass index 21.73 ± 1.76 kg/m². The right foot was measured twice by the experienced rater using the NNHt and the FPI-6. A sequence of the measures was randomly arranged for each participant with a 10-minute rest between the tests. The Pearson’s correlation coefficient (r) was used to determine the relationship between the measures. Results: The mean NNHt score was 0.23 ± 0.04 (ranged from 0.15 to 0.36) and the mean FPI-6 score was 4.42 ± 4.36 (ranged from -6 to +11). The Pearson’s correlation coefficient among the NNHt score and the FPI-6 score was -0.872 (p < 0.01). Conclusion: The present finding demonstrates the strong correlation between the NNHt and FPI-6 in adult feet and implies that both measures could be substituted for each other in identifying foot posture.

Keywords: foot posture index, foot type, measurement of foot posture, navicular height

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Authors: Dasom Kim, Chen Liu, Myungsu Lim, Su-Hyeon Jeon, ByeoungKug Jeon, Kee-Young Kwahk, Namgyu Kim

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Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we previously proposed a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. In this paper, we design a survey-based verification scenario for estimating the accuracy of our automatic categorization methodology.

Keywords: big data analysis, document classification, multi-category, text mining, topic analysis

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Authors: Shirin Abbas, Sandeep Kumar Dubey

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Intimate partner violence (IPV) is one of the most common forms of gender-based violence (GBV) and is classified as discrimination on the basis of gender. Article 2 of the non-binding UN Declaration on the Elimination of Violence against Women (DEVAW). This was adopted in 1993 as the first international pronouncement regarding violence against women, including physical, sexual, and psychological violence in the family (i.e., domestic violence, marital rape, battery, statutory rape, rape by male members of the family, etc.) While crime against women continues unabated, the Indian government has strongly refuted the 2018 study by the Thomson Reuters Foundation categorizing India as a risky country for women due to the high risk of sexual violence and being forced into slave labour, according to a poll of global experts. This paper has explored consent, agency, and abuse through the lens of intimate partner violence among women from lower income groups in smart cities in the state of Uttar Pradesh, India. Using focused mapping, the paper has explored the situation on IPV internationally and studied the status of working women from lower income groups to ascertain if their lot was any different where IPV was concerned to study. The findings of the study also vindicate global reports which rate India as a country unsafe for women, even within marriage.

Keywords: consent and agency, domestic violence, gender based violence GBV, intimate partner violence IPV

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Authors: Dustin Dill

Abstract:

The physical movement of crossing over water points to both developing narrative tropes and innovative cinematography in World Cinema today. Two prime examples, Alamar (2009) by Pedro González-Rubio and Kaili Blues (2015) by Bi Gan, demonstrate how contemporary storytelling in a film not only rests upon these water shots but also emerges from them. The range of symbolism that these episodes in the story provoke goes hand in hand with the diverse filming sequences found in the respective productions. While González-Rubio decides to cut the scene into long and longer shots, Gan uses a single take. The differing angles depict equally unique directors and film projects: Alamar runs parallel to many definitions of the essay film, and Kaili Blues resonates much more with mystery and art film. Nonetheless, the crossing of water scenes influence the narratives’ subjects despite the generic consequences, and it is within the essay, mystery, and art film genres which allows for a better understanding of World Cinema. Tiago de Luca explains World Cinema’s prerogative of giving form to a certain type of spectator does not always line up. Given the immense number of interpretations of crossing water —the escape from suffering to find nirvana, rebirth, and colonization— underline the difficulty of categorizing it. If before this type of cross-genre was a trait that defined World Cinema in its beginning, this study observes that González-Rubio and Gan question the all-encompassing genre with their experimental shots of a universal narrative trope, the crossing of water.

Keywords: cinematography, genre, narrative, world cinema

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Authors: Ali Abbas

Abstract:

This paper presents a descriptive model of organizational misconduct based on observed patterns that occur before and after an ethical collapse. The patterns were classified by categorizing media articles in both "for-profit" and "not-for-profit" organizations. Based on the model parameters, the paper provides a descriptive model of various organizational deflection strategies under numerous scenarios, including situations where ethical complaints build-up, situations under which whistleblowers become more prevalent, situations where large scandals that relate to leadership occur, and strategies by which organizations deflect blame when pressure builds up or when media finds out. The model parameters start with the premise of a tolerance to double standards in unethical acts when conducted by leadership or by members of corporate governance. Following this premise, the model explains how organizations engage in discursive strategies to cover up the potential conflicts that arise, including secret agreements and weakening stakeholders who may oppose the organizational acts. Deflection strategies include "preemptive" and "post-complaint" secret agreements, absence of (or vague) documented procedures, engaging in blame and scapegoating, remaining silent on complaints until the media finds out, as well as being slow (if at all) to acknowledge misconduct and fast to cover it up. The results of this paper may be used to guide organizational leaders into the implications of such shortsighted strategies toward unethical acts, even if they are deemed legal. Validation of the model assumptions through numerous media articles is provided.

Keywords: ethical decision making, prediction, scandals, organizational strategies

Procedia PDF Downloads 83