Search results for: Grey-box text attack

Authors: Ismail Seçer

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The purpose of this study is to investigate the effects of anxiety sensitivity in adolescents on anxiety disorder and childhood depression. Mood disorders and anxiety disorders in children and adolescents can be given examples of important research topics in recent years. The participants of the study consist of 670 students in Erzurum and Erzincan city centers. The participants of the study were 670 secondary and high school students studying in city centers of Erzurum and Erzincan. The participants were chosen based on convenience sampling. The participants were between the ages of 13 and 18 (M=15.7, Ss= 1.35) and 355 were male and 315 were female. The data were collected through Anxiety Sensitivity Index and Anxiety and Depression Index for Children and Adolescents. For data analysis, Correlation analysis and Structural Equation Model were used. In this study, correlational descriptive survey was used. This model enables the researcher to make predictions related to different variables based on the information obtained from one or more variables. Therefore, the purpose is to make predictions considering anxiety disorder and childhood depression based on anxiety sensitivity. For this purpose, latent variable and structural equation model was used. Structural equation model is an analysis method which enables the identification of direct and indirect effects by determining the relationship between observable and latent variables and testing their effects on a single model. CFI, RMR, RMSEA and SRMR, which are commonly accepted fit indices in structural equation model, were used. The results revealed that anxiety sensitivity impacts anxiety disorder and childhood depression through direct and indirect effects in a positive way. The results are discussed in line with the relevant literature. This finding can be considered that anxiety sensitivity can be a significant risk source in terms of children's and adolescents’ anxiety disorder experience. This finding is consistent with relevant research highlighting that in case the anxiety sensitivity increases then the obsessive compulsive disorder and panic attack increase too. The adolescents’ experience of anxiety can be attributed to anxiety sensitivity.

Keywords: anxiety sensitivity, anxiety, depression, structural equation

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Authors: Alpha Bolinao, Francine Rose De Castro, Jessie Kate Lumba, Raztine Mae Paeste, Hannah Grace Tosio

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The present study aimed to know the role of verbal bullying in the lives of obese teenagers exposed to it. The study employed a qualitative design specifically the phenomenological approach that focuses on the obese teenagers’ verbal bullying experiences. The study also used the social constructivism approach wherein it described the obese teenagers’ verbal bullying experiences as they interact with the social world. Through purposive and referral sampling technique, the researchers were able to choose twelve (12) respondents from different schools around the City of Manila, enrolled in the School Year 2015-2016, ages 16-21 years old, has experienced verbal bullying for the last ten (10) years and with the Body Mass Index (BMI) of equal to or greater than 30. Upon the consent of the respondents, ethical considerations were ensured. In-depth one (1) hour interviews were guided by the researchers’ aide memoir. The recorded interviews were transcribed into a field text and the responses were thoroughly analyzed through Thematic Analysis and Kelly’s Repertory Grid. It was found that the role of verbal bullying in the lives of obese teenagers exposed to it is a process and is best described through a syringe, or the 5S Responses of Obese Teenagers in Bullying, with five conceptual themes which also signify the experiences and the process that obese teenagers have gone through after experiencing verbal bullying. The themes conceptualized were: Suffering, self-doubt, suppression, self-acceptance and sanguineness. This paper may serve as a basis for a counseling program to help the obese teenagers cope with their bullying experiences.

Keywords: obesity, obese teenagers, bullying, experiences

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Authors: Varun K, Pramod B. Balareddy

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Estimation of wind forces plays a significant role in the in the design of large antenna parabolic reflectors. Reflector surface accuracies are very sensitive to the gain of the antenna system at higher frequencies. Hence accurate estimation of wind forces becomes important, which is primary input for design and analysis of the reflector system. In the present work, numerical simulation of wind flow using Computational Fluid Dynamics (CFD) software is used to investigate the external pressure coefficients. An extensive comparative study has been made between the CFD results and the published wind tunnel data for different wind angle of attacks (α) acting over concave to convex surfaces respectively. Flow simulations using CFD are carried out to estimate the coefficients of Drag, Lift and Moment for the parabolic reflector. Coefficients of pressures (Cp) over the front and the rear face of the reflector are extracted over surface of the reflector to study the net pressure variations. These resultant pressure variations are compared with the published wind tunnel data for different angle of attacks. It was observed from the CFD simulations, both convex and concave face of reflector system experience a band of pressure variations for the positive and negative angle of attacks respectively. In the published wind tunnel data, Pressure variations over convex surfaces are assumed to be uniform and vice versa. Chordwise and spanwise pressure variations were calculated and compared with the published experimental data. In the present work, it was observed that the maximum pressure coefficients for α ranging from +30° to -90° and α=+90° was lower. For α ranging from +45° to +75°, maximum pressure coefficients were higher as compared to wind tunnel data. This variation is due to non-uniform pressure distribution observed over front and back faces of reflector. Variations in Cd, Cl and Cm over α=+90° to α=-90° was in close resemblance with the experimental data.

Keywords: angle of attack, drag coefficient, lift coefficient, pressure coefficient

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Authors: Emily Rivera, Toni DiDona

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The Big Five personality traits is a hierarchical classification of personality traits that applies factor analysis to a personality survey data in order to describe human personality using five broad dimensions: Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness (Fetvadjiev & Van de Vijer, 2015). Research shows that personality constructs underline individual differences in processing conflict and interpersonal relations. (Graziano et al., 1996). This research explores the understudied correlation between the Big Five personality traits and perceived interpersonal conflict in the workplace. It revises social psychological literature on Big Five personality traits within a social context and discusses organizational development journal articles on the perceived efficacy of conflict tactics and approach to interpersonal relationships. The study also presents research undertaken on a survey group of 867 subjects over the age of 18 that were recruited by means of convenience sampling through social media, email, and text messaging. The central finding of this study is that only two of the Big Five personality traits had a significant correlation with perceiving interpersonal conflict in the workplace. Individuals who score higher on agreeableness and neuroticism, perceive more interpersonal conflict in the workplace compared to those that score lower on each dimension. The relationship between both constructs is worthy of research due to its everyday frequency and unique individual psycho-social consequences. This multimethod research associated the Big Five personality dimensions to interpersonal conflict. Its findings that can be utilized to further understand social cognition, person perception, complex social behavior and social relationships in the work environment.

Keywords: five-factor model, interpersonal conflict, personality, The Big Five personality traits

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Authors: Sushma Ghogale

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With a surge in user-generated content or feedback or reviews on the internet, it has become possible and important to know consumers' opinions about products and services. This data is important for both potential customers and businesses providing the services. Data from social media is attracting significant attention and has become the most prominent channel of expressing an unregulated opinion. Prospective customers look for reviews from experienced customers before deciding to buy a product or service. Several websites provide a platform for users to post their feedback for the provider and potential customers. However, the biggest challenge in analyzing such data is in extracting latent features and providing term-level analysis of the data. This paper proposes an approach to use topic modeling to classify the reviews into topics and conduct sentiment analysis to mine the opinions. This approach can analyse and classify latent topics mentioned by reviewers on business sites or review sites, or social media using topic modeling to identify the importance of each topic. It is followed by sentiment analysis to assess the satisfaction level of each topic. This approach provides a classification of hotel reviews using multiple machine learning techniques and comparing different classifiers to mine the opinions of user reviews through sentiment analysis. This experiment concludes that Multinomial Naïve Bayes classifier produces higher accuracy than other classifiers.

Keywords: latent Dirichlet allocation, topic modeling, text classification, sentiment analysis

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Authors: Jingjie Li, Wenjie Hu

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Phraseological units in academic English texts have been a central focus in recent corpus linguistic research. A wide variety of phraseological units have been explored, including collocations, chunks, lexical bundles, patterns, semantic sequences, etc. This paper describes a special category of clause-level phraseological units, namely, Characteristic Sentence Stems (CSSs), with a view to describing their defining criteria and extraction method. CSSs are contiguous lexico-grammatical sequences which contain a subject-predicate structure and which are frame expressions characteristic of academic writing. The extraction of CSSs consists of six steps: Part-of-speech tagging, n-gram segmentation, structure identification, significance of occurrence calculation, text range calculation, and overlapping sequence reduction. Significance of occurrence calculation is the crux of this study. It includes the computing of both the internal association and the boundary independence of a CSS and tests the occurring significance of the CSS from both inside and outside perspectives. A new normalization algorithm is also introduced into the calculation of LocalMaxs for reducing overlapping sequences. It is argued that many sentence stems are so recurrent in academic texts that the most typical of them have become the habitual ways of making meaning in academic writing. Therefore, studies of CSSs could have potential implications and reference value for academic discourse analysis, English for Academic Purposes (EAP) teaching and writing.

Keywords: characteristic sentence stem, extraction method, phraseological unit, the statistical measure

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Authors: Visa I. Tyakaray, M. Abdulaziz, O. Badmus, N. Karaye, M. Dalhat, A. Shehu, I. Bello, T. Hussaini, S. Akar, G. Effah, P. Nguku

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Introduction: Nigeria has recorded outbreaks of meningitis in the past, being in the meningitis belt. A multi-state outbreak of Cerebrospinal Meningitis (CSM) from Neisseria meningitides occurred in 2017 involving 24 states, and Kano State reported its first two confirmed CSM cases on 22nd March, 2017. We conducted the outbreak investigation to characterize the outbreak, determine its associated risk factors and institute appropriate control measures. Method: We conducted an unmatched Case-control study with ratio 1:2. A case was defined as any person with sudden onset of fever (>38.5˚C rectal or 38.0˚C axillary) and one of the following: neck stiffness, altered consciousness or bulging fontanelle in toddlers while a control was defined as any person who resides around the case such as family members, caregivers, neighbors, and healthcare personnel. We reviewed and validated line list and conducted active case search in health facilities and neighboring communities. Descriptive, bivariate, stratified and multivariate analysis were performed. Laboratory confirmation was by Latex agglutination and/or Culture. Results: We recruited 48 cases with median age of 11 years (1 month – 65 years), attack rate was 2.4/100,000 population with case fatality rate of 8%; 34 of 44 local government areas were affected.On stratification, age was found to be a confounder. Independent factors associated with the outbreak were age (Adjusted Odds Ratio, AOR =6.58; 95% Confidence Interval (CI) =2.85-15.180, history of Vaccination (AOR=0.37; 95% CI=0.13-0.99) and history of travel (AOR=10.16; (1.99-51.85). Laboratory results showed 22 positive cases for Neisseria meningitides types C and A/Y. Conclusion: Major risk factors associated with this outbreak were age (>14years), not being vaccinated and history of travel. We sensitized communities and strengthened case management. We recommended immediate reactive vaccination and enhanced surveillance in bordering communities.

Keywords: cerebrospinal, factors, Kano-Nigeria, meningitis, risk

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Authors: Christine Ivy A. Nogot

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Under the colony of Spain for more than three centuries, the Philippines has a deep-rooted structure of Western ideologies and colonialism. The late 19th century, the period of Enlightenment, created a significant impact on our history when a group of middle-class Filipino men were sent to Europe to study. They were called Ilustrados, a Spanish word for erudite. They were the enlightened; the well-educated, intellectual scholars. Their writings provide intellectual grounds for the awakening of national consciousness that eventually prompted national movements and revolutions. They helped to establish a postcolonial society. In the modern era, Miguel Syjuco, a Filipino expatriate, wrote a novel and titled it Ilustrado. It is a representation of the liberal mind of the diasporic author in contemporary discourse. It provides a critical examination of the ilustrado in transition through the character of Miguel, who is also an expatriate writer. Using Syjuco’s award-winning novel as the primary text and anchored on Said’s concept of Orientalism, this paper examines how the depiction of features of the Eastern world is presented in the literary discourse. This paper looks into Said’s concept of orientalism as a hegemonic discursive structure and shows how Western superiority influences the Eastern culture in literary discourse. It explores Gramsci’s theory of cultural hegemony to explore Said’s argument that Western powers conquer the orient through culture and ideology. This paper presents how dominant ideologies and the social context redefine the ilustrado in the contemporary era.

Keywords: cultural hegemony, ilustrado, orientalism, postcolonial

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Authors: Nami Takase

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Computer-mediated-communication allows people to connect and interact with each other as if they were sharing the same space. The current study examined the effects of using video letters (VLs) on the development of second language speaking skills of Common European Framework of Reference for Languages (CEFR) A1 and CEFR B2 level learners of English as a foreign language. Two groups were formed to measure the impact of VLs. The experimental and control groups were given the same topic, and both groups worked with a native English-speaking university student from the United States of America. Students in the experimental group exchanged VLs, and students in the control group used video conferencing. Pre- and post-tests were conducted to examine the effects of each practice mode. The transcribed speech-text data showed that the VL group had improved speech accuracy scores, while the video conferencing group had increased sentence complexity scores. The use of VLs may be more effective for beginner-level learners because they are able to notice their own errors and replay videos to better understand the native speaker’s speech at their own pace. Both the VL and video conferencing groups provided positive feedback regarding their interactions with native speakers. The results showed how different types of computer-mediated communication impacts different areas of language learning and speaking practice and how each of these types of online communication tool is suited to different teaching objectives.

Keywords: computer-assisted-language-learning, computer-mediated-communication, english as a foreign language, speaking

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Authors: N. Nalini, Bhanu Prakash Gopularam

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The term data security refers to the degree of resistance or protection given to information from unintended or unauthorized access. The core principles of information security are the confidentiality, integrity and availability, also referred as CIA triad. Cloud computing services are classified as SaaS, IaaS and PaaS services. With cloud adoption the confidential enterprise data are moved from organization premises to untrusted public network and due to this the attack surface has increased manifold. Several cloud computing platforms like OpenStack, Eucalyptus, Amazon EC2 offer users to build and configure public, hybrid and private clouds. While the traditional encryption based on PKI infrastructure still works in cloud scenario, the management of public-private keys and trust certificates is difficult. The Identity based Public Key Cryptography (also referred as ID-PKC) overcomes this problem by using publicly identifiable information for generating the keys and works well with decentralized systems. The users can exchange information securely without having to manage any trust information. Another advantage is that access control (role based access control policy) information can be embedded into data unlike in PKI where it is handled by separate component or system. In OpenStack cloud platform the keystone service acts as identity service for authentication and authorization and has support for public key infrastructure for auto services. In this paper, we explain OpenStack security architecture and evaluate the PKI infrastructure piece for data confidentiality. We provide method to integrate ID-PKC schemes for securing data while in transit and stored and explain the key measures for safe guarding data against security attacks. The proposed approach uses JPBC crypto library for key-pair generation based on IEEE P1636.3 standard and secure communication to other cloud services.

Keywords: data confidentiality, identity based cryptography, secure communication, open stack key stone, token scoping

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Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

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Authors: Claudio Díaz, Mabel Ortiz

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An EFL teacher education programme in Chile takes five years to train a future teacher of English. Preservice teachers are prepared to learn an advanced level of English and teach the language from 5th to 12th grade in the Chilean educational system. In the context of their first EFL Methodology course in year four, preservice teachers have to create a five-minute digital story that starts from a critical incident they have experienced as teachers-to-be during their observations or interventions in the schools. A critical incident can be defined as a happening, a specific incident or event either observed by them or involving them. The happening sparks their thinking and may make them subsequently think differently about the particular event. When they create their digital stories, preservice teachers put technology, teaching practice and theory together to narrate a story that is complemented by still images, moving images, text, sound effects and music. The story should be told as a personal narrative, which explains the critical incident. This presentation will focus on the creation process of 50 Chilean preservice teachers’ digital stories highlighting the critical incidents they started their stories. It will also unpack preservice teachers’ beliefs and reflections when approaching their teaching practices in schools. These beliefs will be coded and categorized through content analysis to evidence preservice teachers’ most rooted conceptions about English teaching and learning in Chilean schools. The findings seem to indicate that preservice teachers’ beliefs are strongly mediated by contextual and affective factors.

Keywords: beliefs, digital stories, preservice teachers, practicum

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Authors: Ayse Tarhan, Mustafa Ilkan, Mohammad Karimzadeh

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Science was considered as part of philosophy in ancient Greece. By the nineteenth century, it was understood that philosophy was very inclusive and that social and human sciences such as literature, history, and psychology should be separated and perceived as an autonomous branch of science. The computer was also first seen as a tool of mathematical science. Over time, computer science has grown by encompassing every area in which technology exists, and its growth compelled the division of computer science into different disciplines, just as philosophy had been divided into different branches of science. Now there is almost no branch of science in which computers are not used. One of the newer autonomous disciplines of computer science is digital humanities, and one of the areas of digital humanities is literature. The material of literature is words, and thanks to the software tools created using computer programming languages, data that a literature researcher would need months to complete, can be achieved quickly and objectively. In this article, three different tools that literary researchers can use in their work will be introduced. These studies were created with the computer programming languages Python and R and brought to the world of literature. The purpose of introducing the aforementioned studies is to set an example for the development of special tools or programs on Ottoman language and literature in the future and to support such initiatives. The first example to be introduced is the Stylometry tool developed with the R language. The other is The Metrical Tool, which is used to measure data in poems and was developed with Python. The latest literature analysis tool in this article is Voyant Tools, which is a multifunctional and easy-to-use tool.

Keywords: DH, literature, information technologies, stylometry, the metrical tool, voyant tools

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Authors: Jingsong Ma

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In political translation, ideology plays an important role in conveying implications accurately. Ideological collisions can occur in political translation when there existdifferences of political environments embedded in the translingual political texts in both source and target languages. To reach an accurate translationrequires the translatorto understand the ideologies implied in (and often transcending) the texts. This paper explores the conditions, procedure, and purpose of processingideological collision and resolution of such issues in political translation. These points will be elucidated by case studies of translating English and Chinese political texts. First, there are specific political terminologies in certain political environments. These terminological peculiarities in one language are often determined by ideological elements rather than by syntactical and semantical understanding. The translation of these ideological-loaded terminologiesis a process and operation consisting of understanding the ideological context, including cultural, historical, and political situations. This will be explained with characteristic Chinese political terminologies and their renderings in English. Second, when the ideology in the source language fails to match with the ideology in the target language, the decisions to highlight or disregard these conflicts are shaped by power relations, political engagement, social context, etc. It thus is necessary to go beyond linguisticanalysis of the context by deciphering ideology in political documents to provide a faithful or equivalent rendering of certain messages. Finally, one of the practical issues is about equivalence in political translation by redefining the notion of faithfulness and retainment of ideological messages in the source language in translations of political texts. To avoid distortion, the translator should be liberated from grip the literal meaning, instead diving into functional meanings of the text.

Keywords: translation, ideology, politics, society

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Authors: Moyahabo Molefe

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The persistence of HIV/AIDS infection rates in SA has not only been a subject of academic debate but a mediated narrative that has dominated SA’s post-apartheid film space over the last two decades. SA’s colonial geo-spatial architecture still influences migrant labour patterns, which the Oscar-nominated (2003) SA film ‘Yesterday’ has erstwhile reflected upon, yet continues to account for the spread of HIV/AIDS in SA society. Accordingly, men who had left their homes in the rural areas to work in the mines in the cities become infected with HIV/AIDS, only to return home to infect their wives or partners in the rural areas. This paper analyses, through Social Semiotic theory, how SA geo-spatial arrangement had raptured family structures with both men and women taking new residences in the urban areas where they work away from their homes. By using Social semiotic theory, this paper seeks to understand how images and discourses have been deployed in the film ‘Yesterday’ to demonstrate how HIV/AIDS is embedded in the socio-cultural, economic and political architect of SA society. The study uses qualitative approach and content/text/visual semiotic analysis to decipher meanings from array of imagery and discourses/dialogues that are used to mythologise the relationship between the spread of HIV/AIDS and SA migrant labour patterns. The findings of the study are significant to propose a conceptual framework that can be used to mitigate the spread of HIV/AIDS among SA populace, against the backdrop of changing migrant labour patterns and other related factors

Keywords: colonialism, decoloniality, HIV/AIDS, labour migration patterns, social semiotics

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Authors: Lorena Antonovici, Maria Nicoleta Turliuc

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The process of becoming a vegetarian involves changes in several life aspects, including health. Despite its relevance, however, little research has been carried out to analyze vegetarians' self-perceived health, and even less empirical attention has received in the Romanian population. This study aimed to assess health-related beliefs and practices among vegetarian adults in a Romanian sample. We have undertaken 20 semi-structured interviews (10 males, 10 females) based on a snowball sample with a mean age of 31 years. The interview guide was divided into three sections: causes of adopting the diet, general aspects (beliefs, practices, tensions, and conflicts) and consequences of adopting the diet (significant changes, positive aspects, and difficulties, physical and mental health). Additional anamnestic data were reported by means of a questionnaire. Data analyses were performed using Tropes text analysis software (v. 8.2) and SPSS software (v. 24.0.) Findings showed that most of the participants considered a vegetarian diet as a natural and healthy choice as opposed to meat-eating, which is not healthy, and its consumption should be moderated among omnivores. A higher proportion of participants (65%) had an average body mass index (BMI), and several women even assumed having certain affections that no longer occur after following a vegetarian diet. Moreover, participants admitted having better moods and mental health status, given their self-contentment with the dietary choice. Relatives were perceived as more skeptical about their practices than others, and especially women had this view. This study provides a valuable insight into health-related beliefs and practices and how a vegetarian diet might interact.

Keywords: beliefs, health, practices, vegetarians

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Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

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The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

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Authors: Cheryl Marie Cordeiro

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Although fisheries and aquaculture studies might seem marginal to international business (IB) studies in general, fisheries and aquaculture IB (FAIB) management is currently facing increasing pressure to meet global demand and consumption for fish in the next coming decades. In part address to this challenge, the purpose of this systematic review of literature (SLR) study is to investigate the use of the term ‘market access’ in its context of use in the generic literature and business sector discourse, in comparison to the more specific literature and discourse in fisheries, aquaculture and seafood. This SLR aims to uncover the knowledge/interest gaps between the academic subject discourses and business sector practices. Corpus driven in methodology and using a triangulation method of three different text analysis software including AntConc, VOSviewer and Web of Science (WoS) analytics, the SLR results indicate a gap in conceptual knowledge and business practices in how ‘market access’ is conceived and used in the context of the pharmaceutical healthcare industry and FAIB research and practice. While it is acknowledged that the product orientation of different business sectors might differ, this SLR study works with the assumption that both business sectors are global in orientation. These business sectors are complex in their operations from product to market. This SLR suggests a conceptual model in understanding the challenges, the potential barriers as well as avenues for solutions to developing market access for FAIB.

Keywords: market access, fisheries and aquaculture, international business, systematic literature review

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Authors: Abubakar Sadiq Mensah, Hassan Usman

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The study compared the effectiveness of Audition, Multiplication, subtraction and Division (AMSD) and Addition, subtraction, Multiplication and Division (ASMD), sequence of teaching these four basic operations in mathematics to primary one pupil’s in Katsina Local Government, Katsina State. The study determined the sequence that was more effective and mostly adopted by teachers of the operations. One hundred (100) teachers and sixty pupils (60) from primary one were used for the study. The pupils were divided into two equal groups. The researcher taught these operations to each group separately for four weeks (4 weeks). Group one was taught using the ASMD sequence, while group two was taught using ASMD sequence. In order to generate the needed data for the study, questionnaires and tests were administered on the samples. Data collected were analyzed and major findings were arrived at: (i) Two primary mathematics text books were used in all the primary schools in the area; (ii) Each of the textbooks contained the ASMD sequence; (iii) 73% of the teachers sampled adopted the ASMD sequence of teaching these operations; and (iv) Group one of the pupils (taught using AMSD sequence) performed significantly better than their counter parts in group two (taught using AMSD sequence). On the basis of this, the researcher concluded that the AMSD sequence was more effective in teaching the operations than the ASMD sequence. Consequently, the researcher concluded that primary schools teachers, authors of primary mathematics textbooks, and curriculum planner should adopt the AMSD sequence of teaching these operations.

Keywords: matematic, high school, four basic operations, effectiveness of teaching

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Authors: Minhal Abidi, Moinuddin

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Diabetes mellitus (DM) induced metabolic abnormalities causes oxidative stress which leads to the pathogenesis of complications associated with diabetes like retinopathy, nephropathy periodontitis etc. Combination of glycation and oxidation 'glycoxidation' occurs when oxidative reactions affect the early state of glycation products. Low density lipoprotein (LDL) is prone to glycoxidative attack by sugars and methylglyoxal (MGO) being a strong glycating agent may have severe impact on its structure and consequent role in diabetes. Pro-inflammatory cytokines like IL1β and TNFα produced by the action of gram negative bacteria in periodontits (PD) can in turn lead to insulin resistance. This work discusses modifications to LDL as a result of glycoxidation. The changes in the protein molecule have been characterized by various physicochemical techniques and the immunogenicity of the modified molecules was also evaluated as they presented neo-epitopes. Binding of antibodies present in diabetes patients to the native and glycated LDL has been evaluated. Role of modified epitopes in the generation of antibodies in diabetes and periodontitis has been discussed. The structural perturbations induced in LDL were analyzed by UV–Vis, fluorescence, circular dichroism and FTIR spectroscopy, molecular docking studies, thermal denaturation studies, Thioflavin T assay, isothermal titration calorimetry, comet assay. MALDI-TOF, ketoamine moieties, carbonyl content and HMF content were also quantitated in native and glycated LDL. IL1β and TNFα levels were also measured in the type 2 DM and PD patients. We report increased carbonyl content, ketoamine moieties and HMF content in glycated LDL as compared to native analogue. The results substantiate that in hyperglycemic state MGO modification of LDL causes structural perturbations making the protein antigenic which could obstruct normal physiological functions and might contribute in the development of secondary complications in diabetic patients like periodontitis.

Keywords: advanced glycation end products, diabetes mellitus, glycation, glycoxidation, low density lipoprotein, periodontitis

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Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Jairson Barbosa Rodrigues, Paulo Romero Martins Maciel, Germano Crispim Vasconcelos

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This paper presents an investigation of the performance impacts regarding the variation of five factors (input data size, node number, cores, memory, and disks) when applying a distributed implementation of Naïve Bayes for text classification of a large Corpus on the Spark big data processing framework. Problem: The algorithm's performance depends on multiple factors, and knowing before-hand the effects of each factor becomes especially critical as hardware is priced by time slice in cloud environments. Objectives: To explain the functional relationship between factors and performance and to develop linear predictor models for time and cost. Methods: the solid statistical principles of Design of Experiments (DoE), particularly the randomized two-level fractional factorial design with replications. This research involved 48 real clusters with different hardware arrangements. The metrics were analyzed using linear models for screening, ranking, and measurement of each factor's impact. Results: Our findings include prediction models and show some non-intuitive results about the small influence of cores and the neutrality of memory and disks on total execution time, and the non-significant impact of data input scale on costs, although notably impacts the execution time.

Keywords: big data, design of experiments, distributed machine learning, natural language processing, spark

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for the classification of an unstructured format description for identification of file formats. The main contribution of this work is the employment of data mining techniques to support file format selection with just the unstructured text description that comprises the most important format features for a particular organisation. Subsequently, the file format indentification method employs file format classifier and associated configurations to support digital preservation experts with an estimation of required file format. Our goal is to make use of a format specification knowledge base aggregated from a different Web sources in order to select file format for a particular institution. Using the naive Bayes method, the decision support system recommends to an expert, the file format for his institution. The proposed methods facilitate the selection of file format and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and specifications of file formats. To facilitate decision-making, the aggregated information about the file formats is presented as a file format vocabulary that comprises most common terms that are characteristic for all researched formats. The goal is to suggest a particular file format based on this vocabulary for analysis by an expert. The sample file format calculation and the calculation results including probabilities are presented in the evaluation section.

Keywords: data mining, digital libraries, digital preservation, file format

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Authors: Mohammad Nazri Abdul Bahari, Nurshafika Mohd Sakeh, Siti Nor Akmar Abdullah

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Basal stem rot (BSR) is the most devastating disease in oil palm. Among the oil palm pathogenic fungi, the most prevalent and virulent species associated with BSR is Ganoderma boninense. Early detection of G. boninense attack in oil palm wherein physical symptoms has not yet appeared can offer opportunities to prevent the spread of the necrotrophic fungus. However, poor understanding of molecular defense responses and roles of antifungal metabolites in oil palm against G. boninense has complicated the resolving measures. Hence, characterization of defense-related molecular responses and production of antifungal compounds during early interaction with G. boninense is of utmost important. Four month-old oil palm (Elaeis guineensis) seedlings were artificially infected with G. boninense-inoculated rubber wood block via sitting technique. RNA of samples were extracted from roots and leaves tissues at 0, 3, 7 and 11 days post inoculation (d.p.i) followed with sequencing using RNA-Seq method. Differentially-expressed genes (DEGs) of oil palm-G. boninense interaction were identified, while changes in metabolite profile will be scrutinized related to the DEGs. The RNA-Seq data generated a total of 113,829,376 and 313,293,229 paired-end clean reads from untreated (0 d.p.i) and treated (3, 7, 11 d.p.i) samples respectively, each with two biological replicates. The paired-end reads were mapped to Elaeis guineensis reference genome to screen out non-oil palm genes and subsequently generated 74,794 coding sequences. DEG analysis of phytohormone biosynthetic genes in oil palm roots revealed that at p-value ≤ 0.01, ethylene and jasmonic acid may act in antagonistic manner with salicylic acid to coordinate defense response at early interaction with G. boninense. Findings on metabolite profiling of G. boninense-infected oil palm roots and leaves are hoped to explain the defense-related compounds elicited by Elaeis guineensis in response to G. boninense colonization. The study aims to shed light on molecular defense response of oil palm at early interaction with G. boninense and promote prevention measures against Ganoderma infection.

Keywords: Ganoderma boninense, metabolites, phytohormones, RNA-Seq

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Authors: Cheryl-Ann Sarita Boodram

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Historically, the movement of people has been the subject of socio-political and economic regulatory policies which congeal to regulate human mobility and establish geopolitical and spatial identities and borderlands. As migratory practices evolved, so too has the problematization associated with movement, migration and citizenship. The emerging trends have led to active development of immigration technology governing human mobility and the naming of migratory practices. One such named phenomenon is ‘deportation’ or the forced removal of individuals from their adopted country. Deportation, has gained much attention within the human mobility landscape in the past twenty years following the September 2001 terrorist attack on the World Trade Centre in New York. In a reactionary move, several metropolitan countries, including Canada and the United Kingdom enacted or reviewed immigration laws which further enabled the removal of foreign born criminals to the land of their birth in the global south. Existing studies fall short of understanding the multiple textures of the forced returned migration experiences and the social injustices resulting from deportation displacement. This study brings together indigenous research methodologies through the use of participatory action research and social work with returned migrants in Trinidad and Tobago to uncover the experiences of displacement of deported nationals. The study explores the experiences of negotiating life as a ‘stranger’ and how return has influenced the construction of identities of returned nationals. Findings from this study reveal that deportation has led to inequalities and facilitated ‘othering’ of this group within their own country of birth. The study further highlighted that deportation leads to circuits of dispossession, and perpetuates inequalities. This study provides original insights into the way returned migrants negotiate, map and embody ‘strangeness’ and manage their return to a soil they consider unfamiliar and alien.

Keywords: stranger, alien geographies, displacement, deportation, negotiating strangeness, identity, otherness, alien landscapes

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Authors: Usama Shahid, Muhammad Zunnurain Hussain

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This research paper presents a comprehensive analysis of a sentiment analysis approach that employs valence and arousal as its foundational pillars, in comparison to traditional techniques. Sentiment analysis is an indispensable task in natural language processing that involves the extraction of opinions and emotions from textual data. The valence and arousal dimensions, representing the intensity and positivity/negativity of emotions, respectively, enable the creation of four quadrants, each representing a specific emotional state. The study seeks to determine the impact of utilizing these quadrants to identify distinct emotional states on the accuracy and efficiency of sentiment analysis, in comparison to traditional techniques. The results reveal that the valence and arousal-based approach outperforms other approaches, particularly in identifying nuanced emotions that may be missed by conventional methods. The study's findings are crucial for applications such as social media monitoring and market research, where the accurate classification of emotions and opinions is paramount. Overall, this research highlights the potential of using valence and arousal as a framework for sentiment analysis and offers invaluable insights into the benefits of incorporating specific types of emotions into the analysis. These findings have significant implications for researchers and practitioners in the field of natural language processing, as they provide a basis for the development of more accurate and effective sentiment analysis tools.

Keywords: sentiment analysis, valence and arousal, emotional states, natural language processing, machine learning, text analysis, sentiment classification, opinion mining

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Authors: Ferah Tesfaye Admasu

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Autism Spectrum Disorder (ASD) often presents significant communication challenges, particularly for non-verbal individuals who struggle to express their needs and emotions effectively. Assistive technologies (AT) have emerged as vital tools in enhancing communication abilities for this population. Recent advancements in artificial intelligence (AI) hold the potential to revolutionize the design and functionality of these technologies. This study explores the application of AI in developing intelligent, adaptive, and user-centered assistive technologies for non-verbal individuals with autism. Through a review of current AI-driven tools, including speech-generating devices, predictive text systems, and emotion-recognition software, this research investigates how AI can bridge communication gaps, improve engagement, and support independence. Machine learning algorithms, natural language processing (NLP), and facial recognition technologies are examined as core components in creating more personalized and responsive communication aids. The study also discusses the challenges and ethical considerations involved in deploying AI-based AT, such as data privacy and the risk of over-reliance on technology. Findings suggest that integrating AI into assistive technologies can significantly enhance the quality of life for non-verbal individuals with autism, providing them with greater opportunities for social interaction and participation in daily activities. However, continued research and development are needed to ensure these technologies are accessible, affordable, and culturally sensitive.

Keywords: artificial intelligence, autism spectrum disorder, non-verbal communication, assistive technology, machine learning

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Authors: Cristina Bahón Arnaiz

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Many Asian languages, such as Korean and Japanese, are well-known for their wide use of sound symbolic words or ideophones. This is a very particular characteristic which enriches its lexicon hugely. Ideophones are a class of sound symbolic words that utilize sound symbolism to express aspects, states, emotions, or conditions that can be experienced through the senses, such as shape, color, smell, action or movement. Ideophones have very particular characteristics in terms of sound symbolism and morphology, which distinguish them from other words. The phonological characteristics of ideophones are vowel ablaut or vowel gradation and consonant mutation. In the case of Korean, there are light vowels and dark vowels. Depending on the type of vowel that is used, the meaning will slightly change. Consonant mutation, also known as consonant ablaut, contributes to the level of intensity, emphasis, and volume of an expression. In addition to these phonological characteristics, there is one main morphological singularity, which is reduplication and it carries the meaning of continuity, repetition, intensity, emphasis, and plurality. All these characteristics play an important role in both linguistics and literature as they enhance the meaning of what is trying to be expressed with incredible semantic detail, expressiveness, and rhythm. The following study will analyze the ideophones used in a single paragraph of a Korean novel, which add incredible yet subtle detail to the meaning of the words, and advance the expressiveness and rhythm of the text. The results from analyzing one paragraph from a novel, after presenting the phonological and morphological characteristics of Korean ideophones, will evidence the important role that ideophones play in literature. 

Keywords: ideophones, mimetic words, phonomimes, phenomimes, psychomimes, sound symbolism

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Authors: Samar Alharbi, Yota Dimitriadi

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With the exponential growth of information and communication technologies in higher education, new online teaching strategies have become increasingly important for student engagement and learning. In particular, some institutions depend solely on asynchronous e-learning to provide courses for their students. The major challenge facing these institutions is how to improve the quality of teaching and learning in their asynchronous tools. One of the most important methods that can help e-learner to enhance their social learning and social presence in asynchronous learning setting is immediacy. This study explores tutors perceptions of their instructional immediacy practices as part of their communication actions in online learning environments. It was used a mixed-methods design under the umbrella of pragmatic philosophical assumption. The participants included tutors at an educational institution in a Saudi university. The participants were selected with a purposive sampling approach and chose an institution that offered fully online courses to students. The findings of the quantitative data show the importance of teachers’ immediacy practices in an online text-based learning environment. The qualitative data contained three main themes: the tutors’ encouragement of student interaction; their promotion of class participation; and their addressing of the needs of the students. The findings from these mixed methods can provide teachers with insights into instructional designs and strategies that they can adopt in order to use e-immediacy in effective ways, thus improving their students’ online learning experiences.

Keywords: asynchronous e-learning, higher education, immediacy, tutor

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Authors: Tyler T. Procko, Steve Collins

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New features in .NET (6 and above) permit streamlined access to information residing in JSON-capable relational databases, such as SQL Server (2016 and above). Traditional methods of data access now comparatively involve unnecessary steps which compromise system performance. This work posits that the established ORM (Object Relational Mapping) based methods of data access in applications and APIs result in common issues, e.g., object-relational impedance mismatch. Recent developments in C# and .NET Core combined with a framework of modern SQL Server coding conventions have allowed better technical solutions to the problem. As an amelioration, this work details the language features and coding conventions which enable this streamlined approach, resulting in an open-source .NET library implementation called Codeless Data Access (CODA). Canonical approaches rely on ad-hoc mapping code to perform type conversions between the client and back-end database; with CODA, no mapping code is needed, as JSON is freely mapped to SQL and vice versa. CODA streamlines API data access by improving on three aspects of immediate concern to web developers, database engineers and cybersecurity professionals: Simplicity, Speed and Security. Simplicity is engendered by cutting out the “middleman” steps, effectively making API data access a whitebox, whereas traditional methods are blackbox. Speed is improved because of the fewer translational steps taken, and security is improved as attack surfaces are minimized. An empirical evaluation of the speed of the CODA approach in comparison to ORM approaches ] is provided and demonstrates that the CODA approach is significantly faster. CODA presents substantial benefits for API developer workflows by simplifying data access, resulting in better speed and security and allowing developers to focus on productive development rather than being mired in data access code. Future considerations include a generalization of the CODA method and extension outside of the .NET ecosystem to other programming languages.

Keywords: API data access, database, JSON, .NET core, SQL server

Procedia PDF Downloads 65