Search results for: short text analysis

Authors: William Michael Short

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Semantic Web’ technologies such as the Unified Medical Language System Metathesaurus, SNOMED-CT, and MeSH have been touted as transformational for the way users access online medical and health information, enabling both the automated analysis of natural-language data and the integration of heterogeneous healthrelated resources distributed across the Internet through the use of standardized terminologies that capture concepts and relationships between concepts that are expressed differently across datasets. However, the approaches that have so far characterized ‘semantic bioinformatics’ have not yet fulfilled the promise of the Semantic Web for medical and health information retrieval applications. This paper argues within the perspective of cognitive linguistics and cognitive anthropology that four features of human meaning-making must be taken into account before the potential of semantic technologies can be realized for this domain. First, many semantic technologies operate exclusively at the level of the word. However, texts convey meanings in ways beyond lexical semantics. For example, transitivity patterns (distributions of active or passive voice) and modality patterns (configurations of modal constituents like may, might, could, would, should) convey experiential and epistemic meanings that are not captured by single words. Language users also naturally associate stretches of text with discrete meanings, so that whole sentences can be ascribed senses similar to the senses of words (so-called ‘discourse topics’). Second, natural language processing systems tend to operate according to the principle of ‘one token, one tag’. For instance, occurrences of the word sound must be disambiguated for part of speech: in context, is sound a noun or a verb or an adjective? In syntactic analysis, deterministic annotation methods may be acceptable. But because natural language utterances are typically characterized by polyvalency and ambiguities of all kinds (including intentional ambiguities), such methods leave the meanings of texts highly impoverished. Third, ontologies tend to be disconnected from everyday language use and so struggle in cases where single concepts are captured through complex lexicalizations that involve profile shifts or other embodied representations. More problematically, concept graphs tend to capture ‘expert’ technical models rather than ‘folk’ models of knowledge and so may not match users’ common-sense intuitions about the organization of concepts in prototypical structures rather than Aristotelian categories. Fourth, and finally, most ontologies do not recognize the pervasively figurative character of human language. However, since the time of Galen the widespread use of metaphor in the linguistic usage of both medical professionals and lay persons has been recognized. In particular, metaphor is a well-documented linguistic tool for communicating experiences of pain. Because semantic medical knowledge-bases are designed to help capture variations within technical vocabularies – rather than the kinds of conventionalized figurative semantics that practitioners as well as patients actually utilize in clinical description and diagnosis – they fail to capture this dimension of linguistic usage. The failure of semantic technologies in these respects degrades the efficiency and efficacy not only of medical research, where information retrieval inefficiencies can lead to direct financial costs to organizations, but also of care provision, especially in contexts of patients’ self-management of complex medical conditions.

Keywords: ambiguity, bioinformatics, language, meaning, metaphor, ontology, semantic web, semantics

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Authors: Ramesh K. Sunkaria, Puneeta Marwaha

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Nonlinear methods of heart rate variability (HRV) analysis are becoming more popular. It has been observed that complexity measures quantify the regularity and uncertainty of cardiovascular RR-interval time series. In the present work, SampEn has been evaluated in healthy Normal Sinus Rhythm (NSR) male and female subjects for different data lengths and tolerance level r. It is demonstrated that SampEn is small for higher values of tolerance r. Also SampEn value of healthy female group is higher than that of healthy male group for short data length and with increase in data length both groups overlap each other and it is difficult to distinguish them. The SampEn gives inaccurate results by assigning higher value to female group, because male subject have more complex HRV pattern than that of female subjects. Therefore, this traditional algorithm exhibits higher complexity for healthy female subjects than for healthy male subjects, which is misleading observation. This may be due to the fact that SampEn do not account for multiple time scales inherent in the physiologic time series and the hidden spatial and temporal fluctuations remains unexplored.

Keywords: heart rate variability, normal sinus rhythm group, RR interval time series, sample entropy

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Authors: Anna Slupik, Anna Mosiolek, Sebastian Wojtowicz, Dariusz Bialoszewski

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Introduction: Whole-body vibration (WBV) uses high frequency mechanical stimuli generated by a vibration plate and transmitted through bone, muscle and connective tissues to the whole body. Research has shown that long-term vibration-plate training improves neuromuscular facilitation, especially in afferent neural pathways, responsible for the conduction of vibration and proprioceptive stimuli, muscle function, balance and proprioception. Some researchers suggest that the vibration stimulus briefly inhibits the conduction of afferent signals from proprioceptors and can interfere with the maintenance of body balance. The aim of this study was to evaluate the influence of a single set of exercises associated with whole-body vibration on the joint position sense and body balance. Material and methods: The study enrolled 55 people aged 19-24 years. These individuals were randomly divided into a test group (30 persons) and a control group (25 persons). Both groups performed the same set of exercises on a vibration plate. The following vibration parameters: frequency of 20Hz and amplitude of 3mm, were used in the test group. The control group performed exercises on the vibration plate while it was off. All participants were instructed to perform six dynamic exercises lasting 30 seconds each with a 60-second period of rest between them. The exercises involved large muscle groups of the trunk, pelvis and lower limbs. Measurements were carried out before and immediately after exercise. Joint position sense (JPS) was measured in the knee joint for the starting position at 45° in an open kinematic chain. JPS error was measured using a digital inclinometer. Balance was assessed in a standing position with both feet on the ground with the eyes open and closed (each test lasting 30 sec). Balance was assessed using Matscan with FootMat 7.0 SAM software. The surface of the ellipse of confidence and front-back as well as right-left swing were measured to assess balance. Statistical analysis was performed using Statistica 10.0 PL software. Results: There were no significant differences between the groups, both before and after the exercise (p> 0.05). JPS did not change in both the test (10.7° vs. 8.4°) and control groups (9.0° vs. 8.4°). No significant differences were shown in any of the test parameters during balance tests with the eyes open or closed in both the test and control groups (p> 0.05). Conclusions. 1. Deterioration in proprioception or balance was not observed immediately after the vibration stimulus. This suggests that vibration-induced blockage of proprioceptive stimuli conduction can have only a short-lasting effect that occurs only as long as a vibration stimulus is present. 2. Short-term use of vibration in treatment does not impair proprioception and seems to be safe for patients with proprioceptive impairment. 3. These results need to be supplemented with an assessment of proprioception during the application of vibration stimuli. Additionally, the impact of vibration parameters used in the exercises should be evaluated.

Keywords: balance, joint position sense, proprioception, whole body vibration

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Authors: Mohanad Alhabo, Naveed Nawaz

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The ongoing call or data session must be maintained to ensure a good quality of service. This can be accomplished by performing the handover procedure while the user is on the move. However, the dense deployment of small cells in 5G networks is a challenging issue due to the extensive number of handovers. In this paper, a neighbour cell list method is proposed to reduce the number of target small cells and hence minimizing the number of handovers. The neighbour cell list is built by omitting cells that could cause an unnecessary handover and handover failure because of short time of stay of the user in these cells. A multi-attribute decision making technique, simple additive weighting, is then applied to the optimized neighbour cell list. Multi-tier small cells network is considered in this work. The performance of the proposed method is analysed and compared with that of the existing methods. Results disclose that our method has decreased the candidate small cell list, unnecessary handovers, handover failure, and short time of stay cells compared to the competitive method.

Keywords: handover, HetNets, multi-attribute decision making, small cells

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Authors: Hilya Mudrika Arini, Nur Aini Masruroh, Budi Hartono

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There are more than 20 terrorist threats from 2002 to 2012 in Indonesia. Despite of this fact, preventive solution through studies in the field of national security in Indonesia has not been conducted comprehensively. This study aims to provide a preventive solution by developing prediction model of the terrorist threat in Indonesia by using Bayesian network. There are eight stages to build the model, started from literature review, build and verify Bayesian belief network to what-if scenario. In order to build the model, four experts from different perspectives are utilized. This study finds several significant findings. First, news and the readiness of terrorist group are the most influent factor. Second, according to several scenarios of the news portion, it can be concluded that the higher positive news proportion, the higher probability of terrorist threat will occur. Therefore, the preventive solution to reduce the terrorist threat in Indonesia based on the model is by keeping the positive news portion to a maximum of 38%.

Keywords: Bayesian network, decision analysis, national security system, text mining

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Authors: Judith Hanke

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Due to the increase of students with reading difficulties, digital reading support with diagnostics was developed to foster the individual student's reading comprehension. The digital reading support focused on the reading comprehension of elementary school students. The digital reading packages consist of literary texts with aligned reading exercises. The number of students with German as a second language is growing in Germany. Students with multilingualism, language 1, and language 2 learn German together in school. The research's focus is on determining whether and to what extent multilingualism, language 1, and language 2 affect reading comprehension. For the methodology, an ABA design was selected for the intervention study to examine the reading support. The study was expedited from April 2023 until July 2023 and collected quantitative data of individuals, groups, and classes. It comprised a survey group (N = 58) and a control group (N = 53). The quantitative data was collected from 3 classes of 3 teachers and 47 students for all three test times. To show differences between the groups, a standardized reading comprehension test was used for the three test times, pretest, posttest, and follow-up. The standardized test consists of three subtests regarding word comprehension, sentence comprehension, and text comprehension. The main findings include that students who spoke German as their first language had the best test scores. Interestingly, students with a different language had better testing scores than students with German as the first language and (an) other language/s. Also, the students with another language outperformed the native language speakers in one of the subtests of the post-testing. The variables of spoken language at home and German as a second language were also examined and correlated with the test results. One significant correlation was found between spoken language at home and the text comprehension test of the pretesting. Additionally, the variable German as a second language had multiple significant correlations in the pretest, posttest and follow-up. The study's significance is to understand the influence of several languages, language 1, and language 2, on reading comprehension.

Keywords: multilingualism, language 1, language 2, reading comprehension, second language

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Authors: Fangting Gao

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Ozone acts as an atmospheric shield, protecting organisms from ultraviolet radiation by absorbing it. Currently, a large amount of international environmental epidemiology has confirmed that short- and long-term exposure to ozone has significant effects on population health. Near-surface ozone, as a secondary pollutant in the atmosphere, not only negatively affects the production activities of living organisms but also damages ecosystems and affects climate change to some extent. In this paper, using the hour-by-hour ozone observations given by ground meteorological stations in four cities, namely Beijing, Kunming, Xining, and Guangzhou, from 2015 to 2017, the number of days of exceedance and the long-term change characteristics of ozone are analyzed by using the time series analysis method. On this basis, the effects of changes in meteorological conditions on ozone concentration were discussed in conjunction with the same period of meteorological data, and the similarities and differences of near-surface ozone in different cities were comparatively analyzed to establish a relevant quantitative model of near-surface ozone. This study found that ozone concentrations were highest during the summer months of the year, that ozone concentrations were strongly correlated with meteorological conditions, and that none of the four cities had ozone concentrations that reached the threshold for causing disease.

Keywords: ozone, meteorological conditions, pollution, health

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Authors: Mohua Dutta

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The primary aim of this research paper is to investigate the forced urban migration of Dalits in India who are fleeing caste persecution in rural areas. This paper examines the relationship between caste and rural-to-urban internal migration in India using a literary text, Rohinton Mistry’s A Fine Balance, highlighting the challenges faced by Dalits in rural areas that force them to migrate to urban areas. Despite the prevalence of such discussions in Dalit autobiographies written in vernacular languages, there is a lack of discussion regarding caste migration in Indian English Literature, including this present text, as evidenced by the existing critical interpretations of the novel, which this paper seeks to rectify. The primary research question is how urban migration affects caste system in India and why rural-to-urban caste migration occurs. The purpose of this paper is to better understand the reasons for Dalit migration, the challenges they face in rural and urban areas, and the lingering influence of caste in both rural and urban areas. The study reveals that the promise of mobility and emancipation provided by class operations drives rural-to-urban caste migration in India, but it also reveals that caste marginalization in rural areas is closely linked to class marginalization and other forms of subalternity in urban areas. Moreover, the caste system persists in urban areas as well, making Dalit migrants more vulnerable to social, political, and economic discrimination. The reason for this is that, despite changes in profession and urban migration, the trapped structure of caste capital and family networks exposes migrants to caste and class oppressions. To reach its conclusion, this study employs a variety of methodologies. Discourse analysis is used to investigate the current debates and narratives surrounding caste migration. Critical race theory, specifically intersectional theory and social constructivism, aids in comprehending the complexities of caste, class, and migration. Mistry's novel is subjected to textual analysis in order to identify and interpret references to caste migration. Secondary data, such as theoretical understanding of the caste system in operation and scholarly works on caste migration, are also used to support and strengthen the findings and arguments presented in the paper. The study concludes that rural-to-urban caste migration in India is primarily motivated by the promise of socioeconomic mobility and emancipation offered by urban spaces. However, the caste system persists in urban areas, resulting in the continued marginalisation and discrimination of Dalit migrants. The study also highlights the limitations of urban migration in providing true emancipation for Dalit migrants, as they remain trapped within caste and family network structures. Overall, the study raises awareness of the complexities surrounding caste migration and its impact on the lives of India's marginalised communities. This study contributes to the field of Migration Studies by shedding light on an often-overlooked issue: Dalit migration. It challenges existing literary critical interpretations by emphasising the significance of caste migration in Indian English Literature. The study also emphasises the interconnectedness of caste and class, broadening understanding of how these systems function in both rural and urban areas.

Keywords: rural-to-urban caste migration in india, internal migration in india, caste system in india, dalit movement in india, rooster coop of caste and class, urban poor as subalterns

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Authors: Ahmed T. Alahmar

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There is an increasing trend toward student-centred interactive e-learning methods and students’ feedback is a valuable tool for improving learning methods. The aim of this study was to explore the attitude of second year pharmacy students at the University of Babylon, Iraq, towards lectures, exams and e-learning. Materials and methods: Ninety pharmacy students were surveyed by paper questionnaire about their preference for lecture format, use of e-files, theoretical lectures versus practical experiments, lecture and lab time. Students were also asked about their predilection for Moodle-based online exams, different types of exam questions, exam time and other extra academic activities. Results: Students prefer to read lectures on paper (73.3%), use of PowerPoint file (76.7%), short lectures of less than 10 pages (94.5%), practical experiments (66.7%), lectures and lab time of less than two hours (89.9% and 96.6 respectively) and intra-lecture discussions (68.9%). Students also like to have paper-based exam (73.3%), short essay (40%) or MCQ (34.4%) questions and also prefer to do extra activities like reports (22.2%), seminars (18.6%) and posters (10.8%). Conclusion: Second year pharmacy students have different attitudes toward traditional and electronic leaning and assessment methods. Using multimedia, e-learning and Moodle are increasingly preferred methods among some students.

Keywords: pharmacy, students, lecture, exam, e-learning, Moodle

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Authors: Fereshteh Darash

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Reflective tax management corresponds to the Agency Theory since it determines the motivation of managers for tax management actions and short-term and long-term consequences. Therefore, selection of tax strategy contributes to the tax and financial position of the firm in the future. The aim of the present research is to evaluate the effect of tax management components on risk-taking of firms listed in Tehran stock exchange by using regression analysis method. Results show that tax effective rate, tax risk and tax planning have no significant effect on the firm's future risk. Results suggest that stakeholders assess the effective tax rate and delay in tax payment in line with their benefits. They tend to accept the higher risk cost for reduction of tax payments and benefits of higher liquidity in current period. Hence, effective tax rate and tax risk have no significant effect on future risk of the firm. Moreover, tax planning yields no information regarding the predictability of the future profits and as a result, it has no significant effect on the future risk of the firm since specific goals of financial reporting are in priority for the stakeholders and regardless of the firm’s data analysis, they take investment decisions and they less intend to purchase the stocks in a rational manner.

Keywords: tax management, tax effective rate, tax risk, tax planning, firm risk

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Authors: Chaudhary Muhammad Aqdus Ilyas, Matthias Rehm, Kamal Nasrollahi, Thomas B. Moeslund

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This paper presents the investigation of data collection procedures, associated with robots when placed with traumatic brain injured (TBI) patients for rehabilitation purposes through facial expression and mood analysis. Rehabilitation after TBI is very crucial due to nature of injury and variation in recovery time. It is advantageous to analyze these emotional signals in a contactless manner, due to the non-supportive behavior of patients, limited muscle movements and increase in negative emotional expressions. This work aims at the development of framework where robots can recognize TBI emotions through facial expressions to perform rehabilitation tasks by physical, cognitive or interactive activities. The result of these studies shows that with customized data collection strategies, proposed framework identify facial and emotional expressions more accurately that can be utilized in enhancing recovery treatment and social interaction in robotic context.

Keywords: computer vision, convolution neural network- long short term memory network (CNN-LSTM), facial expression and mood recognition, multimodal (RGB-thermal) analysis, rehabilitation, robots, traumatic brain injured patients

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Authors: Farzad Hosseini Hossein Abadi, Cristina Prieto Sierra, Cesar Álvarez Díaz

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Predicting streamflow accurately in flashy catchments prone to floods is a major research and operational challenge in hydrological modeling. Recent advancements in deep learning, particularly Long Short-Term Memory (LSTM) networks, have shown to be promising in achieving accurate hydrological predictions at daily and hourly time scales. In this work, a multi-timescale LSTM (MTS-LSTM) network was applied to the context of regional hydrological predictions at an hourly time scale in flashy catchments. The case study includes 40 catchments allocated in the Basque Country, north of Spain. We explore the impact of hyperparameters on the performance of streamflow predictions given by regional deep learning models through systematic hyperparameter tuning - where optimal regional values for different catchments are identified. The results show that predictions are highly accurate, with Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) metrics values as high as 0.98 and 0.97, respectively. A principal component analysis reveals that a hyperparameter related to the length of the input sequence contributes most significantly to the prediction performance. The findings suggest that input sequence lengths have a crucial impact on the model prediction performance. Moreover, employing catchment-scale analysis reveals distinct sequence lengths for individual basins, highlighting the necessity of customizing this hyperparameter based on each catchment’s characteristics. This aligns with well known “uniqueness of the place” paradigm. In prior research, tuning the length of the input sequence of LSTMs has received limited focus in the field of streamflow prediction. Initially it was set to 365 days to capture a full annual water cycle. Later, performing limited systematic hyper-tuning using grid search, revealed a modification to 270 days. However, despite the significance of this hyperparameter in hydrological predictions, usually studies have overlooked its tuning and fixed it to 365 days. This study, employing a simultaneous systematic hyperparameter tuning approach, emphasizes the critical role of input sequence length as an influential hyperparameter in configuring LSTMs for regional streamflow prediction. Proper tuning of this hyperparameter is essential for achieving accurate hourly predictions using deep learning models.

Keywords: LSTMs, streamflow, hyperparameters, hydrology

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Authors: Lavanya Srinivasan

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Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat, and case recorded using longwave infrared, short wave infrared, medium wave infrared, and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using YOLO, background subtraction, silhouettes extraction, and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the principal component analysis and recognised using different classifiers. The comparative results with the different classifier show that linear discriminant analysis outperforms other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.

Keywords: biometric, gait, silhouettes, YOLO

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Authors: A. Hadj Taieb, H. Ennouri

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The current study aimed to investigate the effect that optical illusion garments have on a woman’s self-perception of her own body shape. First, we created different optical illusion garment by using color contrasts. Second, a short survey based on visual perception is addressed to women in order to compare the different optical illusion garments to determine if they met the established 'ideal' body shape. A ‘visual analysis method’ was used to investigate the clothing models with optical illusions. The theories in relation with the optical illusion were used through this method. The effects of the optical illusion of color contrast on body shape in the fashion sector were tried to be revealed.

Keywords: optical illusion, color contrasts, body image perception, self-esteem

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Authors: Shazia Salam

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This paper focuses on studying the literary reactions of selected Muslim women writers to the event of Partition of India in the north western region. It aims to explore how Muslim women experienced the Partition and how that experience was articulated through their writing. There is a serious dearth of research on the experience of Muslim women who had to witness the momentous event of the subcontinent. Since scholars have often questioned the silence around the historiography related to the experiences of Muslim women, this paper aims to explore if literature could provide insights that may be less readily available in other modes of narration. Using literature as an archival source, it aims to delve into the arenas of history that have been cloistered and closed. Muslim women have been silent about their experiences of Partition which at the cost of essentializing could be attributed to patriarchal constraints, and taboos, on speaking of intimate matters. These silences have consigned the question of their experience to a realm of anonymity. The lack of ethnographic research has in a way been compensated in the realm of literature, mainly poetry and fiction. Besides reportage, literature remains an important source of social history about Partition and how Muslim women lived through it. Where traditional history fails to record moments of rupture and dislocation, literature serves the crucial purpose. The central premise in this paper is that there is a need to revise the history of partition owing to the gaps in historiography. It looks into if literature can serve as a ground for developing new approaches to history since the question of the representation always confronts us--between what a text represents and how it represents it since imagination of the writer plays a great role in the construction of any text. With this approach as an entry point, this paper aims to unpack the questions of representation, the coalescing of history /literature and the gendered nature of partition history. It concludes that the gaps in the narratives of Partition and the memory of Partition can be addressed by way of suing literary as a source to fill in the cracks and fissures.

Keywords: gender, history, literature, partition

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Authors: Sayuri Inoue, Naohiro Nakamura, Tsubasa Hamada

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The seismic design method of buildings is classified into two types: static design and dynamic design. The static design is a design method that exerts static force as seismic force and is a relatively simple design method created based on the experience of seismic motion in the past 100 years. At present, static design is used for most of the Japanese buildings. Dynamic design mainly refers to the time history response analysis. It is a comparatively difficult design method that input the earthquake motion assumed in the building model and examine the response. Currently, it is only used for skyscrapers and specific buildings. In the present design standard in Japan, it is good to use either the design method of the static design and the dynamic design in the medium and high-rise buildings. However, when actually designing middle and high-rise buildings by two kinds of design methods, the relatively simple static design method satisfies the criteria, but in the case of a little difficult dynamic design method, the criterion isn't often satisfied. This is because the dynamic design method was built with the intention of designing super high-rise buildings. In short, higher safety is required as compared with general buildings, and criteria become stricter. The authors consider applying the dynamic design method to general buildings designed by the static design method so far. The reason is that application of the dynamic design method is reasonable for buildings that are out of the conventional standard structural form such as emphasizing design. For the purpose, it is important to compare the design results when the criteria of both design methods are arranged side by side. In this study, we performed time history response analysis to medium-rise buildings that were actually designed with allowable stress method. Quantitative comparison between static design and dynamic design was conducted, and characteristics of both design methods were examined.

Keywords: buildings, seismic design, allowable stress design, time history response analysis, Japanese seismic code

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Authors: Elena Masi, Adolfo Morrone

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Migration has recently become a mainstream development sector and is currently at the forefront in institutional and civil society context. However, no consensus exists on how the link between migration and development operates, that is how development is related to migration and how migration can promote development. On one hand, Official Development Assistance is recognized to be one of the levers to development. On the other hand, the debate is focusing on what should be the scope of aid programs targeting migrants groups and in general the migration process. This paper provides a descriptive analysis on how development aid for migration was allocated in the recent past, focusing on the actions that were funded and implemented by the international donor community. In the absence of an internationally shared methodology for defining the boundaries of development aid on migration, the analysis based on lexical hypotheses on the title or on the short description of initiatives funded by several Organization for Economic Co-operation and Development (OECD) countries. Moreover, the research describes and quantifies aid flows for each country according to different criteria. The terms migrant and refugee are used to identify the projects in accordance with the most internationally agreed definitions and only actions in countries of transit or of origin are considered eligible, thus excluding the amount sustained for refugees in donor countries. The results show that the percentage of projects targeting migrants, in terms of amount, has followed a growing trend from 2009 to 2016 in several European countries, and is positively correlated with the flows of migrants. Distinguishing between programs targeting migrants and programs targeting refugees, some specific national features emerge more clearly. A focus is devoted to actions targeting the root causes of migration, showing an inter-sectoral approach in international aid allocation. The analysis gives some tentative solutions to the lack of consensus on language on migration and development aid, and emphasizes the need to internationally agree on a criterion for identifying programs targeting both migrants and refugees, to make action more transparent and in order to develop effective strategies at the global level.

Keywords: migration, official development assistance, ODA, refugees, time series

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Authors: Ahmed A. A. Fadol, Guangji Tong, Wlaa Mohamed

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This paper provides a comprehensive analysis of food insecurity in Sudan, focusing on consumption patterns and their implications, employing the Integrated Food Security Phase Classification (IPC) assessment framework. Years of conflict and economic instability have driven large segments of the population in Sudan into crisis levels of acute food insecurity according to the (IPC). A substantial number of people are estimated to currently face emergency conditions, with an additional sizeable portion categorized under less severe but still extreme hunger levels. In this study, we explore the multifaceted nature of food insecurity in Sudan, considering its historical, political, economic, and social dimensions. An analysis of consumption patterns and trends was conducted, taking into account cultural influences, dietary shifts, and demographic changes. Furthermore, we employ logistic regression and random forest analysis to identify significant independent variables influencing food security status in Sudan. Random forest clearly outperforms logistic regression in terms of area under curve (AUC), accuracy, precision and recall. Forward projections of the IPC for Sudan estimate that 15 million individuals are anticipated to face Crisis level (IPC Phase 3) or worse acute food insecurity conditions between October 2023 and February 2024. Of this, 60% are concentrated in Greater Darfur, Greater Kordofan, and Khartoum State, with Greater Darfur alone representing 29% of this total. These findings emphasize the urgent need for both short-term humanitarian aid and long-term strategies to address Sudan's deepening food insecurity crisis.

Keywords: food insecurity, consumption patterns, logistic regression, random forest analysis

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Authors: Mustafa Ekici, Sacide Güzin Mazman

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Programming is the one of ability in computer science fields which is generally perceived difficult by students and various individual differences have been implicated in that ability success. Although several factors that affect programming ability have been identified over the years, there is not still a full understanding of why some students learn to program easily and quickly while others find it complex and difficult. Programming self-efficacy and mathematic success are two of those essential individual differences which are handled as having important effect on the programming success. This study aimed to identify the relationship between programming performance, programming self efficacy and mathematics success. The study group is consisted of 96 undergraduates from Department of Econometrics of Uşak University. 38 (39,58%) of the participants are female while 58 (60,41%) of them are male. Study was conducted in the programming-I course during 2014-2015 fall term. Data collection tools are comprised of programming course final grades, programming self efficacy scale and a mathematics achievement test. Data was analyzed through correlation analysis. The result of study will be reported in the full text of the study.

Keywords: programming performance, self efficacy, mathematic success, computer science

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Authors: Baran Johansson

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This PhD dissertation aimed to explore children’s writing and reading in L1 (Persian) and L2 (Swedish). It adds new perspectives to reading and writing studies of bilingual biscriptal children with and without reading and writing difficulties (RWD). The study used standardised tests to examine linguistic and cognitive skills related to word reading and writing fluency in both languages. Furthermore, all participants produced two texts (one descriptive and one narrative) in each language. The writing processes and the writing product of these children were explored using logging methodologies (Eye and Pen) for both languages. Furthermore, this study investigated how two bilingual children with RWD presented themselves through writing across their languages. To my knowledge, studies utilizing standardised tests and logging tools to investigate bilingual children’s word reading and writing fluency across two different alphabetic scripts are scarce. There have been few studies analysing how bilingual children construct meaning in their writing, and none have focused on children who write in two different alphabetic scripts or those with RWD. Therefore, some aspects of the systemic functional linguistics (SFL) perspective were employed to examine how two participants with RWD created meaning in their written texts in each language. The results revealed that children with and without RWD had higher writing fluency in all measures (e.g. text lengths, writing speed) in their L2 compared to their L1. Word reading abilities in both languages were found to influence their writing fluency. The findings also showed that bilingual children without reading difficulties performed 1 standard deviation below the mean when reading words in Persian. However, their reading performance in Swedish aligned with the expected age norms, suggesting greater efficient in reading Swedish than in Persian. Furthermore, the results showed that the level of orthographic depth, consistency between graphemes and phonemes, and orthographic features can probably explain these differences across languages. The analysis of meaning-making indicated that the participants with RWD exhibited varying levels of difficulty, which influenced their knowledge and usage of writing across languages. For example, the participant with poor word recognition (PWR) presented himself similarly across genres, irrespective of the language in which he wrote. He employed the listing technique similarly across his L1 and L2. However, the participant with mixed reading difficulties (MRD) had difficulties with both transcription and text production. He produced spelling errors and frequently paused in both languages. He also struggled with word retrieval and producing coherent texts, consistent with studies of monolingual children with poor comprehension or with developmental language disorder. The results suggest that the mother tongue instruction provided to the participants has not been sufficient for them to become balanced biscriptal readers and writers in both languages. Therefore, increasing the number of hours dedicated to mother tongue instruction and motivating the children to participate in these classes could be potential strategies to address this issue.

Keywords: reading, writing, reading and writing difficulties, bilingual children, biscriptal

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Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

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Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

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Authors: Irene Yi

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

Keywords: gendered grammar, misogynistic language, natural language processing, neural networks

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Authors: Mohit Kumar, Beklashwar Salona, Shiv Murti, Mukesh Singh

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We report here a case of five-months old male baby, born as second child of non-consanguineous parents with no considerable history of genetic abnormality which was referred to our cytogenetic laboratory for chromosomal analysis. Physical dysmorphic facial features including mongoloid face, cleft palate, simian crease, and developmental delay were observed. We present this case with unique balanced autosomal translocation of t(3;10)(p21;p13). The risk of phenotypic abnormalities based on de novo balanced translocation was estimated to be 7%. The association of balanced chromosomal rearrangement with Down syndrome features such as multiple congenital anomalies, facial dysmorphism and congenital heart anomalies are very rare in a 5-months old male child. Trisomy-21 is not uncommon in chromosomal abnormality with the birth defect and balanced translocations are frequently observed in patients with secondary infertility or recurrent spontaneous abortion (RSA). Two ml heparinized peripheral blood cells cultured in RPMI-1640 for 72 hours supplemented with 20% fetal bovine serum, phytohemagglutinin (PHA), and antibiotics were used for chromosomal analysis. A total 30 metaphases images were captured using Olympus-BX51 microscope and analyzed using Bio-view karyotyping software through GTG-banding (G bands by trypsin and Giemsa) according to International System for Human Cytogenetic Nomenclature 2016. The results showed balanced translocation between short arm of chromosome # 3 and short arm of chromosome # 10. The karyotype of the child was found to be 46,XY,t(3;10)(p21; p13). Chromosomal abnormalities are one of the major causes of birth defect in new born babies. Also, balanced translocations are frequently observed in patients with secondary infertility or recurrent spontaneous abortion. The index case presented with dysmorphic facial features and had a balanced translocation 46,XY,t(3;10)(p21;p13). This translocation with break points at (p21; p13) has not been reported in the literature in a child with facial dysmorphism. To the best of our knowledge, this is the first report of novel balanced translocation t(3;10) with break points in a child with dysmorphic features. We found balanced chromosomal translocation instead of any trisomy or unbalanced aberrations along with some phenotypic abnormalities. Therefore, we suggest that such novel balanced translocation with abnormal phenotype should be reported in order to enable the pathologist, pediatrician, and gynecologist to have a better insight into the intricacies of chromosomal abnormalities and their associated phenotypic features. We hypothesized that dysmorphic features as seen in this case may be the result of change in the pattern of genes located at the breakpoint area in balanced translocations or may be due to deletion or mutation of genes located on the p-arm of chromosome # 3 and p-arm of chromosome # 10.

Keywords: balanced translocation, karyotyping, phenotypic abnormalities, facial dimorphisms

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Authors: Tismazammi Mustafa, Jaharudin Padli

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The frequency of terrorism is increasing throughout years that is resulting in loss of life, damaging people’s property, and destructing the environment. The incident of terrorism is not stationed in one particular country but has spread and scattered in other countries hence causing an increase in the number of terrorism cases. Thus, this paper aims to investigate the factors of human development upon the terrorism in East Asia and Pacific countries. This study used a panel ARDL model, in which it enables to capture the long run and the short run relationship among the variables of interest. Logit Model for Binary data is also used, in which to representing an attributes of dependent variables. This study focuses on several human development variables namely GDP per capita, population, human capital, land area, and technologies. The empirical finding revealed that the GDP per capita, population, human capital, land area, and technologies are positively and statistically significant in influencing the terrorism. Thus, the finding in this study will present as grounds to preserve human rights and develop public awareness and will offer guidelines to policy makers, emergency managers, first responders, public health workers, physicians, and other researchers.

Keywords: terrorism, East Asia and Pacific, human development, econometric analysis

Procedia PDF Downloads 403

Authors: Rahul Srivastava, Priti Pundir, Y. R. Sood, Rajnish Shrivastava

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For the interpretation of the signatures of sweep frequency response analysis(SFRA) of transformer different types of statistical techniques serves as an effective tool for doing either phase to phase comparison or sister unit comparison. In this paper with the discussion on SFRA several statistics techniques like cross correlation coefficient (CCF), root square error (RSQ), comparative standard deviation (CSD), Absolute difference, mean square error(MSE),Min-Max ratio(MM) are presented through several case studies. These methods require sample data size and spot frequencies of SFRA signatures that are being compared. The techniques used are based on power signal processing tools that can simplify result and limits can be created for the severity of the fault occurring in the transformer due to several short circuit forces or due to ageing. The advantages of using statistics techniques for analyzing of SFRA result are being indicated through several case studies and hence the results are obtained which determines the state of the transformer.

Keywords: absolute difference (DABS), cross correlation coefficient (CCF), mean square error (MSE), min-max ratio (MM-ratio), root square error (RSQ), standard deviation (CSD), sweep frequency response analysis (SFRA)

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Authors: Yulan Wu

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With the rapid development of social media, the issue of fake news has gained considerable prominence, drawing the attention of both the public and governments. The widespread dissemination of false information poses a tangible threat across multiple domains of society, including politics, economy, and health. However, much research has concentrated on supervised training models within specific domains, their effectiveness diminishes when applied to identify fake news across multiple domains. To solve this problem, some approaches based on domain labels have been proposed. By segmenting news to their specific area in advance, judges in the corresponding field may be more accurate on fake news. However, these approaches disregard the fact that news records can pertain to multiple domains, resulting in a significant loss of valuable information. In addition, the datasets used for training must all be domain-labeled, which creates unnecessary complexity. To solve these problems, an unsupervised domain knowledge discovery framework for fake news detection is proposed. Firstly, to effectively retain the multidomain knowledge of the text, a low-dimensional vector for each news text to capture domain embeddings is generated. Subsequently, a feature extraction module utilizing the unsupervisedly discovered domain embeddings is used to extract the comprehensive features of news. Finally, a classifier is employed to determine the authenticity of the news. To verify the proposed framework, a test is conducted on the existing widely used datasets, and the experimental results demonstrate that this method is able to improve the detection performance for fake news across multiple domains. Moreover, even in datasets that lack domain labels, this method can still effectively transfer domain knowledge, which can educe the time consumed by tagging without sacrificing the detection accuracy.

Keywords: fake news, deep learning, natural language processing, multiple domains

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Authors: L. Totladze

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The role of financial sector in supporting economic growth and development is well acknowledged. The term spread (the difference between the yields on long-term and short-term Treasury securities) has been found useful for predicting economic variables as output growth, inflation, industrial production, consumption. The temp spread is one of the leading economic indicators according to NBER methodology. Leading economic indicators are widely used in forecasting of economic activity. Many empirical studies find that the term spread predicts future economic activity. The article shortly explains how the term spread might predict future economic activity. This paper analyses the dynamics of the spread between short and long-term interest rates in countries with transition economies. The research paper analyses term spread dynamics in Georgia and compare it with post-communist countries and transition economies spread dynamics. In Georgia, the banking sector plays an important and dominant role in the financial sector, especially with respect to the mobilization of savings and provision of credit and may impact on economic activity. For this purpose, we study the impact of the term spread on economic growth in Georgia.

Keywords: forecasting, leading economic indicators, term spread, transition economies

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Authors: Mohsen Farhadloo, Majid Farhadloo

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Aspect-level opinion mining that aims at discovering aspects (aspect identification) and their corresponding ratings (sentiment identification) from customer reviews have increasingly attracted attention of researchers and practitioners as it provides valuable insights about products/services from customer's points of view. Instead of addressing aspect identification and sentiment identification in two separate steps, it is possible to simultaneously identify both aspects and sentiments. In recent years many graphical models based on Latent Dirichlet Allocation (LDA) have been proposed to solve both aspect and sentiment identifications in a single step. Although LDA models have been effective tools for the statistical analysis of document collections, they also have shortcomings in addressing some unique characteristics of opinion mining. Our goal in this paper is to address one of the limitations of topic models to date; that is, they fail to directly model the associations among topics. Indeed in many text corpora, it is natural to expect that subsets of the latent topics have higher probabilities. We propose a probabilistic graphical model called focus-LDA, to better capture the associations among topics when applied to aspect-level opinion mining. Our experiments on real-life data sets demonstrate the improved effectiveness of the focus-LDA model in terms of the accuracy of the predictive distributions over held out documents. Furthermore, we demonstrate qualitatively that the focus-LDA topic model provides a natural way of visualizing and exploring unstructured collection of textual data.

Keywords: aspect-level opinion mining, document modeling, Latent Dirichlet Allocation, LDA, sentiment analysis

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Authors: Shreya Borthakur, Aastha Vartak

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This Electroencephalogram (EEG) project on Rapid Visual Serial Processing (RSVP) paradigm explores the temporal dynamics of visual attention processing in response to rapidly presented visual stimuli. The study builds upon previous research that used real-world images in RSVP tasks to understand the emergence of object representations in the human brain. The objectives of the research include investigating the differences in accuracy and reaction times between 5 Hz and 20 Hz presentation rates, as well as examining the prominent brain waves, particularly alpha and beta waves, associated with the attention task. The pre-processing and data analysis involves filtering EEG data, creating epochs for target stimuli, and conducting statistical tests using MATLAB, EEGLAB, Chronux toolboxes, and R. The results support the hypotheses, revealing higher accuracy at a slower presentation rate, faster reaction times for less complex targets, and the involvement of alpha and beta waves in attention and cognitive processing. This research sheds light on how short-term memory and cognitive control affect visual processing and could have practical implications in fields like education.

Keywords: RSVP, attention, visual processing, attentional blink, EEG

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Authors: Malin Isaksson

Abstract:

Teaching French as a foreign language usually implies teaching French literature, especially in higher education. Training university students in literary reading in a foreign language requires addressing several aspects at the same time: the (foreign) language, the poetic language, the aesthetic aspects of the studied works, and various interpretations of them. A pilot study sought to test a teaching model that would support students in learning to perform competent readings and short analyses of French literary works, in a rather independent manner. This shared practice paper describes the use of a flipped classroom method in two French literature courses, a campus course and an online course, and suggests that the teaching model may provide efficient tools for teaching literary reading and analysis in a foreign language. The teaching model builds on a high level of student activity and focuses on attentive reading, meta-perspectives such as theoretical concepts, individual analyses by students where said concepts are applied, and group discussions of the studied texts and of possible interpretations.

Keywords: attentive reading, flipped classroom, literature in foreign language studies, teaching literature analysis

Procedia PDF Downloads 112