Search results for: distance based analysis

Authors: Yuyun Wabula, B. J. Dewancker

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In the past decade, the social networking app has been growing very rapidly. Geolocation data is one of the important features of social media that can attach the user's location coordinate in the real world. This paper proposes the use of geolocation data from the Twitter social media application to gain knowledge about urban dynamics, especially on human mobility behavior. This paper aims to explore the relation between geolocation Twitter with the existence of people in the urban area. Firstly, the study will analyze the spread of people in the particular area, within the city using Twitter social media data. Secondly, we then match and categorize the existing place based on the same individuals visiting. Then, we combine the Twitter data from the tracking result and the questionnaire data to catch the Twitter user profile. To do that, we used the distribution frequency analysis to learn the visitors’ percentage. To validate the hypothesis, we compare it with the local population statistic data and land use mapping released by the city planning department of Makassar local government. The results show that there is the correlation between Twitter geolocation and questionnaire data. Thus, integration the Twitter data and survey data can reveal the profile of the social media users.

Keywords: geolocation, Twitter, distribution analysis, human mobility

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Authors: Tushar Bhardwaj

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Internet of Things (IoT) possesses a dynamic network where the network nodes (mobile devices) are added and removed constantly and randomly, hence the traffic distribution in the network is quite variable and irregular. The basic but very important part in any network is route searching. We have many conventional route searching algorithms like link-state, and distance vector algorithms but they are restricted to the static point to point network topology. In this paper we propose a model that uses the Ant Colony Algorithm for route searching. It is dynamic in nature and has positive feedback mechanism that conforms to the route searching. We have also embedded the concept of Non-Deterministic Finite Automata [NDFA] minimization to reduce the network to increase the performance. Results show that Ant Colony Algorithm gives the shortest path from the source to destination node and NDFA minimization reduces the broadcasting storm effectively.

Keywords: routing, ant colony algorithm, NDFA, IoT

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

Procedia PDF Downloads 125

Authors: I. Slim, H. Akkari, A. Ben Abdallah, I. Bhouri, M. Hedi Bedoui

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Osteoporosis is a common disease characterized by low bone mass and deterioration of micro-architectural bone tissue, which provokes an increased risk of fracture. This work treats the texture characterization of trabecular bone radiographs. The aim was to analyze according to clinical research a group of 174 subjects: 87 osteoporotic patients (OP) with various bone fracture types and 87 control cases (CC). To characterize osteoporosis, Fractal and MultiFractal (MF) methods were applied to images for features (attributes) extraction. In order to improve the results, a new method of MF spectrum based on the q-stucture function calculation was proposed and a combination of Fractal and MF attributes was used. The Support Vector Machines (SVM) was applied as a classifier to distinguish between OP patients and CC subjects. The features fusion (fractal and MF) allowed a good discrimination between the two groups with an accuracy rate of 96.22%.

Keywords: fractal, micro-architecture analysis, multifractal, osteoporosis, SVM

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Authors: Bilha Paryente, Rivi Frei Landau

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Autoethnography - a combination of autobiography and ethnography - focuses on the intersection of personal experiences and the culture in which they take place and is considered a viable method for exploring human experiences. The Russo-Ukrainian war has resulted in millions of forcibly displaced asylum-seeking refugees facing ambiguous loss. Whereas much is known about refugees' support needs, little is known about the needs and experiences of the humanitarian delegation members (HDM) who assist them. Through a debrief-based co-autoethnographic account of a female HDM who supported Ukrainian refugee mothers and children on the Polish borders, we explored the lived experiences involved in such a mission. Specifically, we conducted a transnational dyadic autoethnography debrief-based co-autoethnography which included both verbal and photo-based debriefing (8 two-hour sessions) alongside a reflexive (10-day) field diary analysis. Content analysis revealed cognitive dilemmas, emotional struggles, and practical adaptations occurring within the HDM's three identity-related domains: personal, professional (psychologist), and ethnic. The methodology presented and demonstrated in this paper enhances our theoretical understanding of the challenges faced by HDMs and may contribute to better future design of HDM training. Practically, the findings of the current study suggest the need for a three-stage accompaniment for HDMs relating to their personal, professional, and ethnic identities and considering their cognitive, emotional, and adaptive aspects. First, before leaving, HDMs should be briefed on personal and professional aspects of their experiences and ways of coping with them, as well as ethnic and religious affiliation issues. Second, while volunteering every evening their dilemmas, emotional struggles, and ways of adapting should be addressed for the three layers of identities. And finally, shortly after their return, there should be a final meeting to discuss all aspects of their identities and layers of personality. In this way, HDMs can become more effective in the important mission they fulfill. We hope that future HDMs and the bodies that send them on humanitarian missions of paramount importance will adopt these recommendations and generate proactive insights for members of future delegations.

Keywords: autoethnography, refugees, humanitarian delegation, ambiguous loss, Russo-Ukraine War, parenting

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Authors: Areerut Jaipadub

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The purpose of this research is to analyze the pattern of television commercials and how they encourage non-governmental organizations to build their image in Thailand. It realizes how public relations can impact an organization's image. It is a truth that bad public relations management can cause hurt a reputation. On the other hand, a very small amount of work in public relations helps your organization to be recognized broadly and eventually accepted even wider. The main idea in this paper is to study and analyze patterns of television commercials that could impact non-governmental organization's images in a greater way. This research uses questionnaires and content analysis to summarize results. The findings show the aspects of how patterns of television commercials that are suited to non-governmental organization work in Thailand. It will be useful for any non-governmental organization that wishes to build their image through television commercials and also for further work based on this research.

Keywords: television commercial (TVC), organization image, non-governmental organization (NGO), public relation

Procedia PDF Downloads 279

Authors: Mevlüt Burak Dalmış, Kemal Yaman

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In this study, flutter characteristics of cantilever rectangular plate structure under incompressible flow regime are investigated by comparing the results of commercial flutter analysis program ZAERO^© with wind tunnel tests conducted in Ankara Wind Tunnel (ART). A rectangular polycarbonate (PC) plate, 5x125x1000 mm in dimensions, is used for both numerical and experimental investigations. Analysis and test results are very compatible with each other. A comparison between two different solution methods (g and k-method) of ZAERO^© is also done. It is seen that, k-method gives closer result than the other one. However, g-method results are on conservative side and it is better to use conservative results namely g-method results. Even if the modal analysis results are used for the flutter analysis for this simple structure, a modal test should be conducted in order to validate the modal analysis results to have accurate flutter analysis results for more complicated structures.

Keywords: flutter, plate, subsonic flow, wind tunnel

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Authors: Lumindu Dilumka, Ranaweera I. D., Sudusinghe S. P., Sanduni Kanchana A. M. K.

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This study was motivated by the challenges experienced by parents and guardians in ensuring the safety of children in cyberspace. In the last two or three years, online education has become very popular all over the world due to the Covid 19 pandemic. Therefore, parents, guardians and teachers must ensure the safety of children in cyberspace. Children are more likely to go astray and there are plenty of online programs are waiting to get them on the wrong track and also, children who are engaging in the online education can be distracted at any moment. Therefore, parents should keep a close check on their children's online activity. Apart from that, due to the unawareness of children, they tempt to share their sensitive information, causing a chance of being a victim of phishing attacks from outsiders. These problems can be overcome through the proposed web-based system. We use feature extraction, web tracking and analysis mechanisms, image processing and name entity recognition to implement this web-based system.

Keywords: online education, cyber bullying, social media, face recognition, web tracker, privacy data

Procedia PDF Downloads 83

Authors: Leonard Mike McNelly Longwa, Divine Kusosa Musiku, Dieudonne Nahum Kabeya

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In this paper, the bifurcation analysis of oilfields in the Democratic Republic of Congo is presented in order to enhance petroleum production in an intense tectonic evolution characterized by distinct compressive and extensive phases and the digenetic transformation in the reservoirs during burial geological configuration. The use of porous media in the Makelekese MS-25 field has been established to simulate the boundaries within 3 sedimentary basins open to exploration including the coastal basin with an area of 5992 km², a central basin with an area of 800,000 km², the western branch of the East African Rift in which there are 50,000 km². The fractal characterization of complex hydro-dynamic fractures in oilfields is developed to facilitate the oil production process based on the reservoirs bifurcation model.

Keywords: reservoir bifurcation, fractal characterization, permeability, conductivity, skin effect

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Authors: Janusz Bobulski, Mariusz Kubanek

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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.

Keywords: an autonomous car, image processing, lidar, obstacle detection

Procedia PDF Downloads 218

Authors: Mabel Usunobun Olanipekun, Henry Ogbemudia Omoregbee

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Anomalies such as water pipeline and hydraulic or petrochemical pipeline network leakages and bursts have significant implications for economic conditions and the environment. In order to ensure pipeline systems are reliable, they must be efficiently controlled. Wireless Sensor Networks (WSNs) have become a powerful network with critical infrastructure monitoring systems for water, oil and gas pipelines. The loss of water, oil and gas is inevitable and is strongly linked to financial costs and environmental problems, and its avoidance often leads to saving of economic resources. Substantial repair costs and the loss of precious natural resources are part of the financial impact of leaking pipes. Pipeline systems experts have implemented various methodologies in recent decades to identify and locate leakages in water, oil and gas supply networks. These methodologies include, among others, the use of acoustic sensors, measurements, abrupt statistical analysis etc. The issue of leak quantification is to estimate, given some observations about that network, the size and location of one or more leaks in a water pipeline network. In detecting background leakage, however, there is a greater uncertainty in using these methodologies since their output is not so reliable. In this work, we are presenting a scalable concept and simulation where a pressure-driven model (PDM) was used to determine water pipeline leakage in a system network. These pressure data were collected with the use of acoustic sensors located at various node points after a predetermined distance apart. We were able to determine with the use of correlation difference to determine the leakage point locally introduced at a predetermined point between two consecutive nodes, causing a substantial pressure difference between in a pipeline network. After de-noising the signal from the sensors at the nodes, we successfully obtained the exact point where we introduced the local leakage using the correlation difference model we developed.

Keywords: leakage detection, acoustic signals, pipeline network, correlation, wireless sensor networks (WSNs)

Procedia PDF Downloads 100

Authors: Liu Chyong-Ru, Wang Yao-Chin, Huang Wen-Shiung, Tang Wan-Ching

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Although gamification has been concerned and applied in the tourism industry, limited literature could be found in tourism academy. Therefore, to contribute knowledge in festival gamification, it becomes essential to start by establishing a Festival Gamification Scale (FGS). This study defines festival gamification as the extent of a festival to involve game elements and game mechanisms. Based on self-determination theory, this study developed an FGS. Through the multi-study method, in study one, five FGS dimensions were sorted through literature review, followed by twelve in-depth interviews. A total of 296 statements were extracted from interviews and were later narrowed down to 33 items under six dimensions. In study two, 226 survey responses were collected from a cycling festival for exploratory factor analysis, resulting in twenty items under five dimensions. In study three, 253 survey responses were obtained from a marathon festival for confirmatory factor analysis, resulting in the final sixteen items under five dimensions. Then, results of criterion-related validity confirmed the positive effects of these five dimensions on flow experience. In study four, for examining the model extension of the developed five-dimensional 16-item FGS, which includes dimensions of relatedness, mastery, competence, fun, and narratives, cross-validation analysis was performed using 219 survey responses from a religious festival. For the tourism academy, the FGS could further be applied in other sub-fields such as destinations, theme parks, cruise trips, or resorts. The FGS serves as a starting point for examining the mechanism of festival gamification in changing tourists’ attitudes and behaviors. Future studies could work on follow-up studies of FGS by testing outcomes of festival gamification or examining moderating effects of enhancing outcomes of festival gamification. On the other hand, although the FGS has been tested in cycling, marathon, and religious festivals, the research settings are all in Taiwan. Cultural differences of FGS is another further direction for contributing knowledge in festival gamification. This study also contributes to several valuable practical implications. First, this FGS could be utilized in tourist surveys for evaluating the extent of gamification of a festival. Based on the results of the performance assessment by FGS, festival management organizations and festival planners could learn the relative scores among dimensions of FGS, and plan for future improvement of gamifying the festival. Second, the FGS could be applied in positioning a gamified festival. Festival management organizations and festival planners could firstly consider the features and types of their festival, and then gamify their festival based on investing resources in key FGS dimensions.

Keywords: festival gamification, festival tourism, scale development, self-determination theory

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Authors: L. Wei Sheng, M. T. Noor Syazwanee, C. J. Carolyna, M. Amiruddin, M. Pauziah

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This paper exhibits the alternatives towards active suspension systems revised based on the classical passive suspension system to improve comfort and handling performance. An active Magneto rheological (MR) suspension system is proposed as to explore the active based suspension system to enhance performance given its freedom to independently specify the characteristics of load carrying, handling, and ride quality. Malaysian quarter car with two degrees of freedom (2DOF) system is designed and constructed to simulate the actions of an active vehicle suspension system. The structure of a conventional twin-tube shock absorber is modified both internally and externally to comprehend with the active suspension system. The shock absorber peripheral structure is altered to enable the assembling and disassembling of the damper through a non-permanent joint whereby the stress analysis of the designed joint is simulated using Finite Element Analysis. Simulation on the internal part where an electrified copper coil of 24AWG is winded is done using Finite Element Method Magnetics to measure the magnetic flux density inside the MR damper. The primary purpose of this approach is to reduce the vibration transmitted from the effects of road surface irregularities while maintaining solid manoeuvrability. The aim of this research is to develop an intelligent control system of a consecutive damping automotive suspension system. The ride quality is improved by means of the reduction of the vertical body acceleration caused by the car body when it experiences disturbances from speed bump and random road roughness. Findings from this research are expected to enhance the quality of ride which in return can prevent the deteriorating effect of vibration on the vehicle condition as well as the passengers’ well-being.

Keywords: active suspension, FEA, magneto rheological damper, Malaysian quarter car model, vibration control

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Authors: Lauren Freed

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This research proposal outlines an examination of homeschool oversight in the Massachusetts educational system amid the backdrop of ideological differences between various parties with contributing interests. This mixed methodology study will follow an interpretive policy research approach, involving the use of existing data, surveys, and focus groups. The aim is to capture distinct sets of meanings, values, feelings, and beliefs by principal stakeholders, while exploring the ways in which they/each interact with, interpret, and implement homeschool guidelines set forth by the Massachusetts Supreme Judicial Court Decision Care and Protection of Charles (1987). This analysis will identify and contextualize the attitudes, administrative choices, financial implications, and educational impacts that result from the process and practice of enacting current homeschool oversight policy in Massachusetts. The following question will guide this study: How do districts, homeschooling parents, and Massachusetts Department of Elementary and Secondary Education (DESE) regulate, fund, collect, interpret, implement and report Massachusetts homeschool oversight policy? The resulting analysis will produce a unique and original baseline snapshot of qualitative and quantifiable point-in-time data based on the registered homeschool population in the state of Massachusetts.

Keywords: alternative education, homeschooling, home education, home schooling policy

Procedia PDF Downloads 183

Authors: Feiyu Fang, Han Wang, Xin Chen, Jun Zeng, Feng Liang, Peixuan Wu

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The 'rope coiling' effect is a normal instability phenomenon widespread exists in viscous fluid, elastic rods and polymeric fibers owing to compressive stress when they fall into a moving belt. Near-field electro-spinning is the modified electro-spinning technique has the ability to direct write micro fibers. In this research, we study the “rope coiling” effect in near-field electro-spinning. By changing the distance between nozzle and collector or the speed ratio between the charge jet speed and the platform moving speed, we obtain a pile of different models coils including the meandering, alternating and coiling patterns. Therefore, this instability can be used to direct write micro structured fibers with a one-step process.

Keywords: rope coiling effects, near-field electrospinning, direct write, micro structure

Procedia PDF Downloads 346

Authors: V. Pentland, S. Spilsbury, A. Biswas, M. F. Mottola, S. Paplinskie, M. S. Mitchell

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Postpartum depression (PPD) is a form of major depressive disorder that afflicts 10–22% of mothers worldwide. Rising demands for traditional PPD treatment options (e.g., psychiatry), especially in the context of the COVID-19 pandemic, are increasingly difficult to meet. More accessible treatment options (e.g., walking) are needed. The objective of this review is to determine the impact of walking on PPD severity. A structured search of seven electronic databases for randomised controlled trials published between 2000 and July 29, 2021, was completed. Studies were included if walking was the sole or primary aerobic exercise modality. A random-effects meta-analysis was conducted for studies reporting PPD symptoms measured using a clinically validated tool. A simple count of positive/null effect studies was undertaken as part of a narrative summary. Five studies involving 242 participants were included (mean age=~28.9 years; 100% with mild-to-moderate depression). Interventions were 12 (n=4) and 24 (n=1) weeks long. Each assessed PPD severity using the Edinburgh Postnatal Depression Scale (EPDS) and was included in the meta-analysis. The pooled effect estimate suggests that relative to controls, walking yielded clinically significant decreases in mean EPDS scores from baseline to intervention end (pooled MD=-4.01; 95% CI:-7.18 to -0.84, I2=86%). The narrative summary provides preliminary evidence that walking-only, supervised, and group-based interventions, including 90-120+ minutes/week of moderate-intensity walking, may produce greater EPDS reductions. While limited by a relatively small number of included studies, pooled effect estimates suggest walking may help mothers manage PPD. This is the first time walking as a treatment for PPD, an exercise modality that uniquely addresses many barriers faced by mothers has been summarized in a systematic way. Trial registration: PROSPERO (CRD42020197521) on August 16th, 2020

Keywords: postpartum, exercise, depression, walking

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Authors: Sergio V Davalos, Alison L. Watkins

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User generated content (UGC) such as website post has data associated with it: time of the post, gender, location, type of device, and number of words. The text entered in user generated content (UGC) can provide a valuable dimension for analysis. In this research, each user post is treated as a collection of terms (words). In addition to the number of words per post, the frequency of each term is determined by post and by the sum of occurrences in all posts. This research focuses on one specific aspect of UGC: sentiment. Sentiment analysis (SA) was applied to the content (user posts) of two sets of political forums related to the US presidential elections for 2012 and 2016. Sentiment analysis results in deriving data from the text. This enables the subsequent application of data analytic methods. The SASA (SAIL/SAI Sentiment Analyzer) model was used for sentiment analysis. The application of SASA resulted with a sentiment score for each post. Based on the sentiment scores for the posts there are significant differences between the content and sentiment of the two sets for the 2012 and 2016 presidential election forums. In the 2012 forums, 38% of the forums started with positive sentiment and 16% with negative sentiment. In the 2016 forums, 29% started with positive sentiment and 15% with negative sentiment. There also were changes in sentiment over time. For both elections as the election got closer, the cumulative sentiment score became negative. The candidate who won each election was in the more posts than the losing candidates. In the case of Trump, there were more negative posts than Clinton’s highest number of posts which were positive. KNIME topic modeling was used to derive topics from the posts. There were also changes in topics and keyword emphasis over time. Initially, the political parties were the most referenced and as the election got closer the emphasis changed to the candidates. The performance of the SASA method proved to predict sentiment better than four other methods in Sentibench. The research resulted in deriving sentiment data from text. In combination with other data, the sentiment data provided insight and discovery about user sentiment in the US presidential elections for 2012 and 2016.

Keywords: sentiment analysis, text mining, user generated content, US presidential elections

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Authors: Michael S. Goodman

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The Joint Intelligence Committee (JIC) has been the senior most analytical body in the UK since its creation in 1936. At various points in its history, most notably and recently in 2004, in the wake of the Iraq war, questions have been asked about its analytical process. In 1968 the British intelligence community saw one of its biggest transformations: the creation of an independent, central cadre of analysts. The ‘Assessments Staff’ was a novel attempt to improve the quality of analysis by fostering independence from departmental biases that had long plagued British intelligence. Seconded into the Cabinet Office, staff were allocated a ‘desk,’ and their role was to produce high level assessments for the most senior readers in the land. At the same time, efforts were made to ‘professionalise’ the analysts. This paper is based on a detailed archival examination of the JIC’s documentary files. It will recount the reasons behind this organisational reform, what the changes entailed, and whether they were a success. The changes were immediately brought to bear with the intelligence assessments prior to the Soviet invasion of Czechoslovakia, something that the JIC failed to appreciate.

Keywords: intelligence, cold war history, analysis, united kingdom

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Authors: A. Šapkauskienė, A. Mačerinskienė, R. Andrulienė, R. Bruzgė, S. Masteika, K. Driaunys

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The COVID-19 pandemic has affected not only world markets and economies but also the daily lives of customers and their payment habits. The pandemic has accelerated the digital transformation, so the role of technology will become even more important post-COVID. Although the popularity of cryptocurrencies has reached unprecedented heights, there are still obstacles, such as a lack of consumer experience and distrust of these technologies, so exploring the role of cryptocurrency and blockchain in the context of international travel becomes extremely important. Research on tourists’ intentions to use cryptocurrencies for payment purposes is limited due to the small number of research studies. To fill this research gap, an exploratory study based on the analysis of survey data was conducted. The purpose of the research is to explore how the behavior of tourists has changed making their financial transactions when paying for the tourism services in order to determine the intention to pay in cryptocurrencies. Behavioral intention can be examined as a dependent variable that is useful for the study of the acceptance of blockchain as cutting-edge technology. Therefore, this study examines the intention of travelers to use cryptocurrencies in electronic payments for tourism services. Several studies have shown that the intention to accept payments in a cryptocurrency is affected by the perceived usefulness of these payments and the perceived ease of use. The findings deepen our understanding of the readiness of service users to apply for blockchain-based payment in the tourism sector. The tourism industry has to focus not only on the technology but on consumers who can use cryptocurrencies, creating new possibilities and increasing business competitiveness. Based on research results, suggestions are made to guide future research on the use of cryptocurrencies by tourists in the tourism industry. Therefore, in line with the rapid expansion of virtual currency users, market capitalization, and payment in cryptographic currencies, it is necessary to explore the possibilities of implementing a blockchain-based system aiming to promote the use of services in the tourism sector as the most affected by the pandemic.

Keywords: behavioral intention, blockchain-based payment, cryptocurrency, tourism

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Authors: Hossein Sabouri

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News stories as one of the branches of political discourse has always been regarded a sensitive and challenging area. Political translators often encounter some struggles that are vitally important when it comes to deal with the political tension between the source culture and the target one. Translating news stories is of prime importance since it has widespread availability and power of defining or even changing the facts. News translation is usually more than straight transfer of source text. Like original text endeavoring to manipulate the readers’ minds with imposing their ideologies, translated text seeking to change these ideologies influenced by ideological power. In other words, translation product is not considered more than a recontextualisation of the source text. The present study examines possible criteria for occurring changes in the translation process of news stories based on the ideological and political stance of translator using theories of ‘critical discourse analysis’and ‘translation and power. Fairclough investigates the ideological issues in (political) discourse and Tymoczko studies the political and power-related engagement of the translator in the process of translation. Incorporation of Fairclough and Gentzler and Tymoczko’s theories paves the way for the researcher to looks at the ideological power position of the translator. Data collection and analysis have been accomplished using 17 political-text samples taken from online news agencies which are related to the ‘Iran’s Nuclear Program’. Based on the findings, recontextualisation is mainly observed in terms of the strategies of ‘substitution, omissions, and addition’ in the translation process. The results of the study suggest that there is a significant relationship between the translation of political texts and ideologies of target culture.

Keywords: news translation, recontextualisation, ideological power, political discourse

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Authors: Muneeb Ullah, Daishihan, Xiadong Young

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Deep learning plays a crucial role in identifying COVID-19 and preventing its spread. To improve the accuracy of COVID-19 diagnoses, it is important to have access to a sufficient number of training images of CXRs (chest X-rays) depicting the disease. However, there is currently a shortage of such images. To address this issue, this paper introduces COVID-19 GAN, a model that uses generative adversarial networks (GANs) to generate realistic CXR images of COVID-19, which can be used to train identification models. Initially, a generator model is created that uses digressive channels to generate images of CXR scans for COVID-19. To differentiate between real and fake disease images, an efficient discriminator is developed by combining the dense connectivity strategy and instance normalization. This approach makes use of their feature extraction capabilities on CXR hazy areas. Lastly, the deep regret gradient penalty technique is utilized to ensure stable training of the model. With the use of 4,062 grape leaf disease images, the Leaf GAN model successfully produces 8,124 COVID-19 CXR images. The COVID-19 GAN model produces COVID-19 CXR images that outperform DCGAN and WGAN in terms of the Fréchet inception distance. Experimental findings suggest that the COVID-19 GAN-generated CXR images possess noticeable haziness, offering a promising approach to address the limited training data available for COVID-19 model training. When the dataset was expanded, CNN-based classification models outperformed other models, yielding higher accuracy rates than those of the initial dataset and other augmentation techniques. Among these models, ImagNet exhibited the best recognition accuracy of 99.70% on the testing set. These findings suggest that the proposed augmentation method is a solution to address overfitting issues in disease identification and can enhance identification accuracy effectively.

Keywords: classification, deep learning, medical images, CXR, GAN.

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Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

Procedia PDF Downloads 184

Authors: Jae-Hyun Ro, Jong-Kwang Kim, Chang-Hee Kang, Hyoung-Kyu Song

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In multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems, QR decomposition-M algorithm (QRD-M) has suboptimal error performance. However, the QRD-M has still high complexity due to many calculations at each layer in tree structure. To reduce the complexity of the QRD-M, proposed QRD-M modifies existing tree structure by eliminating unnecessary candidates at almost whole layers. The method of the elimination is discarding the candidates which have accumulated squared Euclidean distances larger than calculated threshold. The simulation results show that the proposed QRD-M has same bit error rate (BER) performance with lower complexity than the conventional QRD-M.

Keywords: complexity, MIMO-OFDM, QRD-M, squared Euclidean distance

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Authors: Felix Boehnisch, Alexander Lutz

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Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

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Authors: Nemes Alexandra

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The aim of the research is to develop an optimum microstructure of steel coatings on aluminum surfaces for application on the crankcase cylinder bores. For the proper design of the microstructure of the coat, it is important to control the plasma gun unit properly. The maximum operating time was determined while the plasma gun could optimally work before its destruction. Objectives: The aim of the research is to determine the optimal operating time of the plasma gun between renovations (the renovation shall involve the replacement of the test components of the plasma gun: electrode, nozzle plate, powder injector. Methodology: Plasma jet and particle flux analysis with PFI (PFI is a diagnostic tool for all kinds of thermal spraying processes), CT reconstruction and analysis on the new and the used plasma guns, failure analysis of electrodes, nozzle plates, and powder injectors, microscopic examination of the microstructure of the coating. Contributions: As the result of the failure analysis detailed above, the use of the plasma gun was maximized at 100 operating hours in order to get optimal microstructure for the coat.

Keywords: APS, air plasma spray, failure analysis, electrode, nozzle plate, powder injector

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Authors: Alessandro Evangelista, Vito M. Manghisi, Michele Gattullo, Enricoandrea Laviola

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In this work, we propose a custom visualization technique for Out-Of-View-Objects in Virtual and Augmented Reality applications using Head Mounted Displays. In the last two decades, Augmented Reality (AR) and Virtual Reality (VR) technologies experienced a remarkable growth of applications for navigation, interaction, and collaboration in different types of environments, real or virtual. Both environments can be potentially very complex, as they can include many virtual objects located in different places. Given the natural limitation of the human Field of View (about 210° horizontal and 150° vertical), humans cannot perceive objects outside this angular range. Moreover, despite recent technological advances in AR e VR Head-Mounted Displays (HMDs), these devices still suffer from a limited Field of View, especially regarding Optical See-Through displays, thus greatly amplifying the challenge of visualizing out-of-view objects. This problem is not negligible when the user needs to be aware of the number and the position of the out-of-view objects in the environment. For instance, during a maintenance operation on a construction site where virtual objects serve to improve the dangers' awareness. Providing such information can enhance the comprehension of the scene, enable fast navigation and focused search, and improve users' safety. In our research, we investigated how to represent out-of-view-objects in HMD User Interfaces (UI). Inspired by commercial video games such as Call of Duty Modern Warfare, we designed a customized Compass. By exploiting the Unity 3D graphics engine, we implemented our custom solution that can be used both in AR and VR environments. The Compass Bar consists of a graduated bar (in degrees) at the top center of the UI. The values of the bar range from -180 (far left) to +180 (far right), the zero is placed in front of the user. Two vertical lines on the bar show the amplitude of the user's field of view. Every virtual object within the scene is represented onto the compass bar as a specific color-coded proxy icon (a circular ring with a colored dot at its center). To provide the user with information about the distance, we implemented a specific algorithm that increases the size of the inner dot as the user approaches the virtual object (i.e., when the user reaches the object, the dot fills the ring). This visualization technique for out-of-view objects has some advantages. It allows users to be quickly aware of the number and the position of the virtual objects in the environment. For instance, if the compass bar displays the proxy icon at about +90, users will immediately know that the virtual object is to their right and so on. Furthermore, by having qualitative information about the distance, users can optimize their speed, thus gaining effectiveness in their work. Given the small size and position of the Compass Bar, our solution also helps lessening the occlusion problem thus increasing user acceptance and engagement. As soon as the lockdown measures will allow, we will carry out user-tests comparing this solution with other state-of-the-art existing ones such as 3D Radar, SidebARs and EyeSee360.

Keywords: augmented reality, situation awareness, virtual reality, visualization design

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Authors: Tai Mei Kin, Omar Abdull Kareem

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In light of globalization, educational reform has become a top priority for many countries. However, the task of leading change effectively requires a multidimensional set of competencies. Over the past two decades, technical competencies of principal change leadership have been extensively analysed and discussed. Comparatively, little research has been conducted in Malaysian education context on non-technical competencies or popularly known as emotional intelligence, which is equally crucial for the success of change. This article provides a validation of the Principal Change Leadership Non-Technical Competencies (PCLnTC) Scale, a tool that practitioners can easily use to assess school principals’ level of change leadership non-technical competencies that facilitate change and maximize change effectiveness. The overall coherence of the PCLnTC model was constructed by incorporating three theories: a)the change leadership theory whereby leading change is the fundamental role of a leader; b)competency theory in which leadership can be taught and learned; and c)the concept of emotional intelligence whereby it can be developed, fostered and taught. An exploratory factor analysis (EFA) was used to determine the underlying factor structure of PCLnTC model. Before conducting EFA, five important pilot test approaches were conducted to ensure the validity and reliability of the instrument: a)reviewed by academic colleagues; b)verification and comments from panel; c)evaluation on questionnaire format, syntax, design, and completion time; d)evaluation of item clarity; and e)assessment of internal consistency reliability. A total of 335 teachers from 12 High Performing Secondary School in Malaysia completed the survey. The PCLnTCS with six points Liker-type scale were subjected to Principal Components Analysis. The analysis yielded a three-factor solution namely, a)Interpersonal Sensitivity; b)Flexibility; and c)Motivation, explaining a total 74.326 per cent of the variance. Based on the results, implications for instrument revisions are discussed and specifications for future confirmatory factor analysis are delineated.

Keywords: exploratory factor analysis, principal change leadership non-technical competencies (PCLnTC), interpersonal sensitivity, flexibility, motivation

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Authors: Pratishtha Singh

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Gender-based violence (GBV) or gendered violence refers to violence inflicted on a person because of their gender. Majority of men who perpetrate gender-based violence, first do so during their teenage years. Further, the first sexual experience of most girls is coerced. In order to reduce the widespread occurrence of GBV, it is vital to intervene and reach people, especially boys, when their attitudes and beliefs about sexuality and gender are developing. This study aims to understand GBV through an adolescent lens, focusing on their knowledge, attitudes and experiences regarding gendered abuse. This is a cross-sectional, qualitative study. The respondents are Delhi based students in grades 11th and 12th, recruited via snowball sampling. Sixteen in-depth, telephonic interviews were carried out in the month of April, 2020. The data was transcribed verbatim into MS Word and qualitative coding was undertaken in Atlas.ti 8. Twelve out of sixteen respondents admitted experiencing sexual GBV. Out of these, a little more than half of the victims reported it to somebody. Thematic analysis revealed key themes of: (i) Introduction and reinforcement of a patriarchal structure (ii) Violence in teen dating (iii) Acceptability and normalization of violence and (iv) Justice System. Findings reflect a process wherein GBV becomes an intricate part of adolescents’ lives. Participants showed a moderately well-informed understanding of gendered abuse whereas attitudes reflected a complex combination of internalized patriarchy and a desire to bring positive societal reform. The results of this study highlight a need for health promoting, gender-equitable interventions.

Keywords: adolescents, gender, health, violence

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Authors: Siti Nadiah Nuwawi, Roshidah Hassan

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Dialect is one of the language variants emerge due to certain factors. One of the distinctive dialects spoken by people in Malaysia is the one spoken by those who reside in the inland area of the East Peninsular Malaysia; Hulu Terengganu, which is known as Ulu Terengganu Malay dialect. This dialect is unique since it possesses ancient elements in its phonology elements, which makes it is hard to be understood by people who come from other states. There is dearth of acoustic studies of the dialect in which this paper aims to attain by describing the quality of the monophthongs found in the dialect instrumentally based on their first and second formant values. The hertz values are observed and recorded from the waveforms and spectrograms depicted in PRAAT version 6.0.43 software. The findings show that Ulu Terengganu Malay speakers produced ten monophthongs namely /ɛ/, /e/, /a/, /ɐ/, /ɞ/, /ɔ/, /i/, /o/, /ɵ/ and /ɘ/ which applauds a few monophthongs suggested by past researchers which were based on auditory impression namely /ɛ/, /e/, /a/, ɔ/, and /i/. It also discovers the other five monophthongs of the dialect which are unknown before namely /ɐ/, /ɞ/, /o/, /ɵ/ and /ɘ/.

Keywords: acoustic analysis, dialect, formant values, monophthongs, Ulu Terengganu Malay

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Authors: Soo-Yong Cho, Chong-Hyun Cho, Chae-Whan Rim, Sang-Kyu Choi, Jin-Gyun Kim, Ju-Seok Nam

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Recently, vertical axis wind turbines (VAWT) have been widely used to produce electricity even in urban. They have several merits such as low sound noise, easy installation of the generator and simple structure without yaw-control mechanism and so on. However, their blades are operated under the influence of the trailing vortices generated by the preceding blades. This phenomenon deteriorates its output power and makes difficulty predicting correctly its performance. In order to improve the performance of VAWT, wind power towers can be applied. Usually, the wind power tower can be constructed as a multi-story building to increase the frontal area of the wind stream. Hence, multiple sets of the VAWT can be installed within the wind power tower, and they can be operated at high elevation. Many different types of wind power tower can be used in the field. In this study, a wind power tower with circular column shape was applied, and the VAWT was installed at the center of the wind power tower. Seven guide walls were used as a strut between the floors of the wind power tower. These guide walls were utilized not only to increase the wind velocity within the wind power tower but also to adjust the wind direction for making a better working condition on the VAWT. Hence, some important design variables, such as the distance between the wind turbine and the guide wall, the outer diameter of the wind power tower, the direction of the guide wall against the wind direction, should be considered to enhance the output power on the VAWT. A numerical analysis was conducted to find the optimum dimension on design variables by using the computational fluid dynamics (CFD) among many prediction methods. The CFD could be an accurate prediction method compared with the stream-tube methods. In order to obtain the accurate results in the CFD, it needs the transient analysis and the full three-dimensional (3-D) computation. However, this full 3-D CFD could be hard to be a practical tool because it requires huge computation time. Therefore, the reduced computational domain is applied as a practical method. In this study, the computations were conducted in the reduced computational domain and they were compared with the experimental results in the literature. It was examined the mechanism of the difference between the experimental results and the computational results. The computed results showed this computational method could be an effective method in the design methodology using the optimization algorithm. After validation of the numerical method, the CFD on the wind power tower was conducted with the important design variables affecting the performance of VAWT. The results showed that the output power of the VAWT obtained using the wind power tower was increased compared to them obtained without the wind power tower. In addition, they showed that the increased output power on the wind turbine depended greatly on the dimension of the guide wall.

Keywords: CFD, performance, VAWT, wind power tower

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