Search results for: foreign/second language learning

Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Sai Sankalp Vemavarapu

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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.

Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation

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Authors: Ivan Potapov

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Background: The aim of this paper is to investigate poly code texts in the communication of youth antisocial groups. Nowadays, the notion of a text has numerous interpretations. Besides all the approaches to defining a text, we must take into account semiotic and cultural-semiotic ones. Rapidly developing IT, world globalization, and new ways of coding of information increase the role of the cultural-semiotic approach. However, the development of computer technologies leads also to changes in the text itself. Polycode texts play a more and more important role in the everyday communication of the younger generation. Therefore, the research of functional and pragmatic aspects of both verbal and non-verbal content is actually quite important. Methods and Material: For this survey, we applied the combination of four methods of text investigation: not only intention and content analysis but also semantic and syntactic analysis. Using these methods provided us with information on general text properties, the content of transmitted messages, and each communicants’ intentions. Besides, during our research, we figured out the social background; therefore, we could distinguish intertextual connections between certain types of polycode texts. As the sources of the research material, we used 20 public channels in the popular messenger Telegram and data extracted from smartphones, which belonged to arrested members of antisocial groups. Findings: This investigation let us assert that polycode texts can be characterized as highly intertextual language unit. Moreover, we could outline the classification of these texts based on communicants’ intentions. The most common types of antisocial polycode texts are a call to illegal actions and agitation. What is more, each type has its own semantic core: it depends on the sphere of communication. However, syntactic structure is universal for most of the polycode texts. Conclusion: Polycode texts play important role in online communication. The results of this investigation demonstrate that in some social groups using these texts has a destructive influence on the younger generation and obviously needs further researches.

Keywords: text, polycode text, internet linguistics, text analysis, context, semiotics, sociolinguistics

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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Authors: Ramesh Bhat, Ammu Somanath, A. K. Nayanatara

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Background: The increasing prevalence of overweight and obesity is a critical public health problem for women. The negative effect of stress on memory and cognitive functions has been widely explored for decades in numerous research projects using a wide range of methodology. Deterioration of memory and other brain functions are hallmarks of Alzheimer’s disease. Estrogen fluctuations and withdrawal have myriad direct effects on the central nervous system that have the potential to influence cognitive functions. Aim: The present study aims to compare the effect of stress on the cognitive functions in overweight/obese women before and after menopause. Material and Methods: A total of 142 female subjects constituting women before menopause between the age group of 18–44 years and women after menopause between the age group of 45–60 years were included in the sample. Participants were categorized into overweight/obese groups based on the body mass index. The Perceived Stress Scale (PSS) the major tool was used for measuring the perception of stress. Based on the stress scale measurement each group was classified into with stress and without stress. Addenbrooke’s cognitive Examination-III was used for measuring the cognitive functions. Results: Premenopausal women with stress showed a significant (P<0.05) decrease in the cognitive parameters such as attention and orientation Fluency, language and visuospatial ability. Memory did not show any significant change in this group. Whereas, in the postmenopausal stressed women all the cognitive functions except fluency showed a significant (P<0.05) decrease after menopause stressed group. Conclusion: Stress is a significant factor on the cognitive functions of obese and overweight women before and after menopause. Practice of Yoga, Encouragement in activities like gardening, embroidery, games and relaxation techniques should be recommended to prevent stress. Insights into the neurobiology before and after menopause can be gained from future studies examining the effect on the HPA axis in relation to cognition and stress.

Keywords: cognition, stress, premenopausal, body mass index

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Authors: Fiona Gibson

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This study is on sustainable capacity building in tourism management of the touristic destination of forts and castles within the Accra Metropolis, of the Greater Accra Region of Ghana, notably, the Christianbough Castle, the James and Ussher Forts. These forts and castle mentioned above have a rich colonial historical past that emerged from the 17th century onwards on the Gulf Coast of Guinea of the West Africa Sub-Region. Unfortunately, apart from the Christianbough Castle, which used to be the seat of government until recently, the environment of James and Ussher Forts are in a deployable state of decay due to years of neglect. Jamestown and Usshertown fishing communities with historical colonial past of a rich touristic heritage sites are predominantly indigenous Gas who speak only the Ga language, one of the languages of the six local languages spoken in Ghana, as a medium for sustainable tourism management. The purpose of this study is to investigate the reasons for years of decay and neglect, using both qualitative and quantitative research approach for individual interviews, to develop a rich picture of life situational story of the people of James and Ussher Forts environs and finding solutions to their predicaments through internal generated funds for sustainability of tourism management within the communities. The study recommends nation-wide educational campaigns and programmes on culture of maintenance and management for sustainable tourism development and management at all historical heritage sites in the country, specifically with the aim of promoting tourism in Ghana, using the indigenous local languages. The study also recommends formal and informal education for the residents, especially the youth to help them learn skills, either through local training or the formal education and this call for collaboration between the government of Ghana and other local and international bodies.

Keywords: sustainable capacity building, tourism management, forts, castles

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Authors: Poteet Frances, Glovinski Ira

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INTRODUCTION: The interoceptive nervous system continuously senses chemical and anatomical changes and helps you recognize, understand, and feel what’s going on inside your body so it is important for energy regulation, memory, affect, and sense of self. A newborn needs predictable routines rather than confusion/chaos to make connections between internal experiences and emotions. AIM: Current legal protocols of removing babies from drug-addicted mothers impact the critical window of bonding. The newborn’s brain is social and the attachment process influences a child’s development which begins immediately after birth through nourishment, comfort, and protection. DESCRIPTION: Our project aims to educate drug-addicted mothers, and medical, nursing, and social work professionals on interoceptive concepts and practices to sustain the mother/newborn relationship. A mother’s interoceptive knowledge predicts children’s emotion regulation and social skills in middle childhood. CONCLUSION: When mothers develop an awareness of their inner bodily sensations, they can self-regulate and be emotionally available to co-regulate (support their newborn during distressing emotions and sensations). Our project has enhanced relationship preservation (mothers understand how their presence matters) and the overall mother/newborn connection.

Keywords: drug-addiction, interoception, legal, mothers, newborn, self-regulation

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Authors: Paolo Fantozzi, Luigi Laura, Umberto Nanni

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The problem of Entity relation discovery in structured data, a well covered topic in literature, consists in searching within unstructured sources (typically, text) in order to find connections among entities. These can be a whole dictionary, or a specific collection of named items. In many cases machine learning and/or text mining techniques are used for this goal. These approaches might be unfeasible in computationally challenging problems, such as processing massive data streams. A faster approach consists in collecting the cooccurrences of any two words (entities) in order to create a graph of relations - a cooccurrence graph. Indeed each cooccurrence highlights some grade of semantic correlation between the words because it is more common to have related words close each other than having them in the opposite sides of the text. Some authors have used sliding windows for such problem: they count all the occurrences within a sliding windows running over the whole text. In this paper we generalise such technique, coming up to a Weighted-Distance Sliding Window, where each occurrence of two named items within the window is accounted with a weight depending on the distance between items: a closer distance implies a stronger evidence of a relationship. We develop an experiment in order to support this intuition, by applying this technique to a data set consisting in the text of the Bible, split into verses.

Keywords: cooccurrence graph, entity relation graph, unstructured text, weighted distance

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Authors: Rashmi Gupta

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Rewarding stimuli capture attention involuntarily as a result of an association process that develops quickly during value learning, referred to as the reward or value-driven attentional capture. It is essential to compare reward with punishment processing to get a full picture of value-based modulation in visual attention processing. Hence, the present study manipulated both valence/value (reward as well as punishment) and motivational salience (probability of an outcome: high vs. low) together. Series of experiments were conducted, and there were two phases in each experiment. In phase 1, participants were required to learn to associate specific face stimuli with a high or low probability of winning or losing points. In the second phase, these conditioned stimuli then served as a distractor or prime in a speeded letter search task. Faces with high versus low outcome probability, regardless of valence, slowed the search for targets (specifically the left visual field target) and suggesting that the costs to performance on non-emotional cognitive tasks were only driven by motivational salience (high vs. loss) associated with the stimuli rather than the valence (gain vs. loss). It also suggests that the processing of motivationally salient stimuli is right-hemisphere biased. Together, results of these studies strengthen the notion that our visual attention system is more sensitive to affected by motivational saliency rather than valence, which termed here as motivational-driven attentional capture.

Keywords: attention, distractors, motivational salience, valence

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Authors: Baohua Yu

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In line with wider tends in the expansion of international student mobility, the number of international higher degree research students has grown at a significant rate in recent years. In particular, Australia has become a hub for attracting international higher degree research students from around the world. However, research has identified that international higher degree research students often encounter a wide range of academic and socio-cultural challenges in adapting to their new environment. Moreover, this can have a significant bearing on their levels of satisfaction with their studies. This paper outlines the findings of a mixed method study exploring the experiences and perceptions of international higher degree research students in Australia. Findings revealed that IRHD students’ overall and academic satisfaction in Australia were highly related to each other, and they were strongly influenced by their learning and research, moderately influenced by co-national support and intercultural contact ability. Socio-cultural satisfaction seemed to belong to a different domain from academic satisfaction because it was explained by a different set of variables such as living and adaptation and intercultural contact ability. In addition, the most important issues in terms of satisfaction were not directly related to academic studies. Instead, factors such as integration into the community, interacting with other students, relationships with supervisors, and the provision of adequate desk space were often given the greatest weight. Implications for how university policy can better support international doctoral students are discussed.

Keywords: international higher degree research students, academic adaptation, socio-cultural adaptation, student satisfaction

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Authors: Renee Moten

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Introduction: Knee pain becomes chronic because the therapy used focuses only on the symptoms of knee pain and not the causes of knee pain. Preventing knee injuries is not in the toolbox of the traditional practitioner. This research was done to show that we must reduce the inflammation (holistically), reduce the swelling and regain flexibility before considering any type of exercise. This method of performing the correct exercise stops the bowing of the knee, corrects the walking gait, and starts to relieve knee, hip, back, and shoulder pain. Method: The holistic method that is used to heal knees is called the Knee Pain Recipe. It’s a six step system that only uses alternative medicine methods to reduce, relieve and restore knee joint mobility. The system is low cost, with no hospital bills, no physical therapy, and no painkillers that can cause damage to the kidneys and liver. This method has been tested on 200 women with knee, back, hip, and shoulder pain. Results: All 200 women reduce their knee pain by 50%, some by as much as 90%. Learning about ankle and foot flexibility, along with understanding the kinetic chain, helps improve the walking gait, which takes the pressure off the knee, hip and back. The knee pain recipe also has helped to reduce the need for a cortisone injection, stem cell procedures, to take painkillers, and surgeries. What has also been noted in the research was that if the women's knees were too far gone, the Knee Pain Recipe helped prepare the women for knee replacement surgery. Conclusion: It is believed that the Knee Pain Recipe, when performed by men and women from around the world, will give them a holistic alternative to drugs, injections, and surgeries.

Keywords: knee, surgery, healing, holistic

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Authors: Dylan Elliott, Katya Pertsova

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Preposition errors are some of the most common errors created by L2 speakers. In addition, improving error correction and detection methods remains an open issue in the realm of Natural Language Processing (NLP). This research investigates whether the bidirectional encoder representations from the transformers model (BERT) have the potential to correct preposition errors accurately enough to be useful in error correction software. This research finds that BERT performs strongly when the scope of its error correction is limited to preposition choice. The researchers used an open-source BERT model and over three hundred thousand edited sentences from Wikipedia, tagged for part of speech, where only a preposition edit had occurred. To test BERT’s ability to detect errors, a technique known as multi-level masking was used to generate suggestions based on sentence context for every prepositional environment in the test data. These suggestions were compared with the original errors in the data and their known corrections to evaluate BERT’s performance. The suggestions were further analyzed to determine if BERT more often agreed with the judgements of the Wikipedia editors. Both the untrained and fined-tuned models were compared. Finetuning led to a greater rate of error-detection which significantly improved recall, but lowered precision due to an increase in false positives or falsely flagged errors. However, in most cases, these false positives were not errors in preposition usage but merely cases where more than one preposition was possible. Furthermore, when BERT correctly identified an error, the model largely agreed with the Wikipedia editors, suggesting that BERT’s ability to detect misused prepositions is better than previously believed. To evaluate to what extent BERT’s false positives were grammatical suggestions, we plan to do a further crowd-sourcing study to test the grammaticality of BERT’s suggested sentence corrections against native speakers’ judgments.

Keywords: BERT, grammatical error correction, preposition error detection, prepositions

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Authors: Carmen Avilés Palacios, Camilo Muñoz Arenas, Joaquín García Alfonso, Jesús González Arteaga, Alberto Alcalde Calonge

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There is a need for review of the consumption and production models of industrialized states in accordance with the Paris Agreement and the Sustainable Development Goals (1) (OECD, 2016). This constitutes the basis of the bioeconomy (2) that is focused on striking a balance between economic development, social development and environmental protection. Bioeconomy promotes the adequate use and consumption of renewable natural resources (3) and involves developing new products and services adapted to the principles of circular economy: more sustainable (reusable, biodegradable, renewable and recyclable) and with a lower carbon footprint (4). In this context, Urban Forest Innovation Lab (UFIL) grows, an Urban Laboratory for experimentation focused on promoting entrepreneurship in forest bioeconomy (www.uiacuenca.es). UFIL generates local wellness taking sustainable advantage of an endogenous asset, forests. UFIL boosts forest bioeconomy opening its doors of knowledge to pioneers in this field, giving the opportunity to be an active part of a change in the way of understanding the exploitation of natural resources, discovering business, learning strategies and techniques and incubating business ideas So far now, 100 entrepreneurs are incubating their nearly 30 new business plans. UFIL has promoted an ecosystem to connect the rural-urban world that promotes sustainable rural development around the forest.

Keywords: bioeconomy, forestry, innovation, entrepreneurship

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Authors: Laleh Golamrej Eliasi

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Finland is the second most violent country for women in the European Union (EU). 47% of women in Finland claimed to have experienced domestic violence against women (DVAW), compared to an average of 33% in the EU. Although the statistics in Finland are transparent, to the author’s best knowledge, there are no statisticsonDV by nationality in Finland. On the other hand, being a Muslim woman in a non-Muslim-majority country represents a position of double vulnerability to violence. There are 10404 Afghan refugees in Finland who are Muslim. Barriers such as unfamiliarity with support services, fear of the police, racism, language, economic and practical dependence, social isolation, and family commitments all lead to a lack of reporting of DVAW among migrants. Although witnessing and experiencing DV have devastating effects on women’s and children’s health and well-being, there is a lack of studies about DVAW among Afghan families in Finland. To fill this knowledge gap, Afghan women living in Finland are selected as the target group to assess their views on DVAW and child protection. This study is implemented in the socio-ecological approach framework to assess the impacts of individual characteristics, interpersonal relationships, community, and society components on DVAW in Afghan families. Interviews with Afghan women and content analysis are used to find out participants' views on DVAW, its risk factors, and approaches and methods to improve protection for women and children. Main purpose is to obtain information about participants' views on the subject. The findings can be used to improve culturally safe social work knowledge and practices with a bottom-up approach to reduce DV and increase child protection. Therefore, this research can have important effects on the sustainable development of services and supports the welfare and inclusion of immigrant families. The expected results will contribute to sustainable gender equality, which is in line with the fifth goal of the Sustainable Development Goals.

Keywords: domestic violence, immigrant women, immigrant child protection, social work

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Authors: Fabianna Bacil, Zenathan Hasannundin, Clovis Freire

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The green transition opens green windows of opportunity – temporary moments in which there are lower barriers and shorter learning periods for developing countries to enter emerging technologies and catch-up. However, taking advantage of these windows requires capabilities in national sectoral systems to adopt and develop technologies linked to green sectors as well as strong responses to build the required knowledge, skills, and infrastructure and foster the growth of targeted sectors. This paper uses UNCTAD’s frontier technology readiness index to analyse the current position of Latin America and the Caribbean to use, adopt, and adapt frontier technologies, examining the preconditions in the region to take up windows of opportunity that arise with the green transition. The index highlights the inequality across countries in the region, as well as gaps in capabilities dimensions, especially in terms of R&D. Moving to responses, it highlights industrial policies implemented to foster the growth of green technologies, emphasising the essential role played by the state to build and strengthen capabilities and provide infant industry protection that enables the growth of these sectors. Overall, while there are exceptions, especially in the Brazilian case, countries in Latin America and the Caribbean should focus on strengthening their capabilities to be better positioned, especially in terms of knowledge creation, infrastructure, and financing availability.

Keywords: Green technologies, Industrial policy, Latin America, windows of opportunity

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Authors: Hsin-Yi Lo, Huang-Ju Jiun, Yu-Chiao Chu

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Hemodynamic monitoring is an important in the intensive care unit. Advances in medical technology in recent years, more diversification of intensive care equipment, there are many kinds of instruments available for monitoring of hemodynamics, Edwards Lifesciences Hemodynamic Monitoring (FloTrac) is one of them. The recent medical safety incidents in parameters were changed, nurses have not to notify doctor in time, therefore, it is hoped to analyze the current problems and find effective improvement strategies. In August 2021, the survey found that only 74.0% of FloTrac correctness of operation, reasons include lack of education, the operation manual is difficulty read, lack of audit mechanism, nurse doesn't know those numerical changes need to notify doctor, work busy omission, unfamiliar with operation and have many nursing records then omissions. Improvement methods include planning professional nurse education, formulate the secret arts of FloTrac, enacting an audit mechanism, establish FloTrac action learning, make「follow the sun」care map, hold simulated training and establish monitoring data automatically upload nursing records. After improvement, FloTrac correctness of operation increased to 98.8%. The results are good, implement to the ICU of the hospital.

Keywords: hemodynamic monitoring, edwards lifesciences hemodynamic monitoring, multiple strategies, intensive care

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

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Authors: B. Likar, K. Širok

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The paper presents a new method for efficient innovation process management. Even though the innovation management methods, tools and knowledge are well established and documented in literature, most of the companies still do not manage it efficiently. Especially in SMEs the front end of innovation - problem identification, idea creation and selection - is often not optimally performed. Our eMIPS methodology represents a sort of "umbrella methodology"- a well-defined set of procedures, which can be dynamically adapted to the concrete case in a company. In daily practice, various methods (e.g. for problem identification and idea creation) can be applied, depending on the company's needs. It is based on the proactive involvement of the company's employees supported by the appropriate methodology and external experts. The presented phases are performed via a mixture of face-to-face activities (workshops) and online (eLearning) activities taking place in eLearning Moodle environment and using other e-communication channels. One part of the outcomes is an identified set of opportunities and concrete solutions ready for implementation. The other also very important result is connected to innovation competences for the participating employees related with concrete tools and methods for idea management. In addition, the employees get a strong experience for dynamic, efficient and solution oriented managing of the invention process. The eMIPS also represents a way of establishing or improving the innovation culture in the organization. The first results in a pilot company showed excellent results regarding the motivation of participants and also as to the results achieved.

Keywords: creativity, distance learning, front end, innovation, problem

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Authors: Ada Yurman

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Using the case of Israeli Atomic Spy Mordechai Vanunu as an example, this study sought to examine social response to political deviance whereby social response can be mobilized in order to achieve social control. Mordechai Vanunu, a junior technician in the Dimona Atomic Research Center, played a normative role in the militaristic discourse while working in the “holy shrine” of the Israeli defense system for many years. At a certain stage, however, Vanunu decided to detach himself from this collective and launched an assault on this top-secret circle. Israeli society in general and the security establishment in particular found this attack intolerable and unforgivable. They presented Vanunu as a ticking time bomb, delegitimized him and portrayed him as “other”. In addition, Israeli enforcement authorities imposed myriad prohibitions and sanctions on Vanunu even after his release from prison – “as will be done to he who desecrates holiness.” Social response to Vanunu at the time of his capture and trial was studied by conducting a content analysis of six contemporary daily newspapers. The analysis focused on use of language and forms of expression. In contrast with traditional content analysis methodology, this study did not just look at frequency of expressions of ideas and terms in the text and covert content; rather, the text was analyzed as a structural whole, and included examination of style, tone and unusual use of imagery, and more, in order to uncover hidden messages within the text. The social response to this case was extraordinarily intense, not only because in this case of political deviance, involving espionage and treason, Vanunu’s actions comprised a real potential threat to the country, but also because of the threat his behavior posed to the symbolic universe of society. Therefore, the response to this instance of political deviance can be seen as being part of a mechanism of social control aiming to protect world view of society as a whole, as well as to punish the criminal.

Keywords: militarism, political deviance, social construction, social control

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Authors: Navneet Kaur, S. D. Tiwari

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Superparamagnetism is an interesting phenomenon and observed in small particles of magnetic materials. It arises due to a reduction in particle size. In the superparamagnetic state, as the thermal energy overcomes magnetic anisotropy energy, the magnetic moment vector of particles flip their magnetization direction between states of minimum energy. Superparamagnetic nanoparticles have been attracting the researchers due to many applications such as information storage, magnetic resonance imaging, biomedical applications, and sensors. For information storage, thermal fluctuations lead to loss of data. So that nanoparticles should have high blocking temperature. And to achieve this, nanoparticles should have a higher magnetic moment and magnetic anisotropy constant. In this work, the magnetic anisotropy constant of the antiferromagnetic nanoparticles system is determined. Magnetic studies on nanoparticles of NiO (nickel oxide) are reported well. This antiferromagnetic nanoparticle system has high blocking temperature and magnetic anisotropy constant of order 105 J/m3. The magnetic study of NiO nanoparticles in the superparamagnetic region is presented. NiO particles of two different sizes, i.e., 6 and 8 nm, are synthesized using the chemical route. These particles are characterized by an x-ray diffractometer, transmission electron microscope, and superconducting quantum interference device magnetometry. The magnetization vs. applied magnetic field and temperature data for both samples confirm their superparamagnetic nature. The blocking temperature for 6 and 8 nm particles is found to be 200 and 172 K, respectively. Magnetization vs. applied magnetic field data of NiO is fitted to an appropriate magnetic expression using a non-linear least square fit method. The role of particle size distribution and magnetic anisotropy is taken in to account in magnetization expression. The source code is written in Python programming language. This fitting provides us the magnetic anisotropy constant for NiO and other magnetic fit parameters. The particle size distribution estimated matches well with the transmission electron micrograph. The value of magnetic anisotropy constants for 6 and 8 nm particles is found to be 1.42 X 105 and 1.20 X 105 J/m3, respectively. The obtained magnetic fit parameters are verified using the Neel model. It is concluded that the effect of magnetic anisotropy should not be ignored while studying the magnetization process of nanoparticles.

Keywords: anisotropy, superparamagnetic, nanoparticle, magnetization

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Authors: Daodu Joshua Rotimi

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This study investigated the Efficacy of Self-Assessment Metacognitive Strategy on Academic performance in Energy Concepts among Upper Basic Science Students in Ankpa, Kogi State, Nigeria. The research design adopted for the study was a Quasi-experimental control group design which employed a pretest, posttest of the experimental and control groups. The population of the study consisted of one hundred and twenty-four (124) JSSII Students; sixty-five (65) for the experimental group and (59) for the control group. The instrument used for the study was the Energy Concept Performance Test (ECPT), with a reliability coefficient of 0.80. Two research questions were answered using descriptive statistics of mean and standard deviation, while two hypotheses were tested using a t-test at P≤0.05 level of significance. The findings of the study revealed that the use of the Self-Assessment Metacognitive Strategy has a positive effect on students’ performance in energy concepts among upper Basic Science Students leading to high academic performance; also, there is no significant difference in the mean Academic Performance scores between Male and Female students taught Energy Concept using Self-Assessment Metacognitive Strategy. Based on the research findings, recommendations were made, which include that Secondary school teachers should be encouraged the use Self-Assessment Metacognitive strategy so as to make the learning process attractive, interactive and enriching to the learners.

Keywords: metacognition, self-assessment, performance, efficacy

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Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: Sukrita Mukherjee, Anindita Chaudhuri

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Soft skills are a crucial aspect for employees, and these skills are not confined to any particular field rather, it guarantees further career growth and job opportunities for employees who are seeking growth. Soft skills are also regarded as personality-specific skills that are observable and are qualitative in nature, which determines an employee’s strengths as a leader. When an employee intends to hold his job, then the person must make effective use of his personal resources, that, in turn, impacts his employability in a positive manner. An employee at his workplace is expected to make effective use of his personal resources. The resources that are to be used by the employee are generally of two types. First type of resources are occupation related, which is related with the educational background of the employee, and the second type of resources are the psychological resources of the employee, such as self-knowledge, career orientation awareness, sense of purpose and emotional literacy, that are considered crucial for an employee in his workplace. The present study is a qualitative study which includes 10 individuals working in IT Sector and Service Industry, respectively. For IT sector, graduate people are considered, and for the Service Industry, individuals who have done a Professional course in order to get into the industry are considered. The emerging themes from the findings after thematic analysis reveal that different aspect of Soft skills such as communication, decision making, constant learning, keeping oneself updated with the latest technological advancement, emotional intelligence are some of the important factors that helps an employee not only to sustain his job, but also grow in his workplace.

Keywords: employabiliy, soft skils, employees, resources, workplace

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Authors: Muhammad Nouman, Fahad Tiwana, Muhammad Irfan, Mohsin Tiwana

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Traffic congestion has been increasing significantly in major metropolitan areas as a result of increased motorization, urbanization, population growth and changes in the urban density. Traffic congestion compromises efficiency of transport infrastructure and causes multiple traffic concerns; including but not limited to increase of travel time, safety hazards, air pollution, and fuel consumption. Traffic management has become a serious challenge for federal and provincial governments, as well as exasperated commuters. Effective, flexible, efficient and user-friendly traffic information/database management systems characterize traffic conditions by making use of traffic counts for storage, processing, and visualization. While, the emerging data collection technologies continue to proliferate, its accuracy can be guaranteed through the comparison of observed data with the manual handheld counters. This paper presents the design of tablet based manual traffic counting application and framework for development of traffic database management system for Pakistan. The database management system comprises of three components including traffic counting android application; establishing online database and its visualization using Google maps. Oracle relational database was chosen to develop the data structure whereas structured query language (SQL) was adopted to program the system architecture. The GIS application links the data from the database and projects it onto a dynamic map for traffic conditions visualization. The traffic counting device and example of a database application in the real-world problem provided a creative outlet to visualize the uses and advantages of a database management system in real time. Also, traffic data counts by means of handheld tablet/ mobile application can be used for transportation planning and forecasting.

Keywords: manual count, emerging data sources, traffic information quality, traffic surveillance, traffic counting device, android; data visualization, traffic management

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Authors: Aamna Tufail, Catherine Anyanwu

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Introduction/Aims: Neurosensory deficits following third molar removal affect the quality of life markedly. The purpose of this audit was to evaluate the incidence of IDN and LN damage and to compare departmental rates to an established standard. A secondary objective was to provide a descriptive summary of identified cases for clinical learning. Materials and Methods: A retrospective audit was conducted by a telephone survey of 101 patients who had third molar extractions performed under LA, IVS, or GA from January 2019 to June 2020 at a District General Hospital. The results were compared to a clinical standard identified as Cheng et al1. Data collection included mode of surgery, mode of anaesthesia, grade of clinician, assessment of difficulty, severity, and duration of symptoms. Results/Statistics: A total of 101 patients had 136 third molars extracted. Age range was 18-84 years. 44% extractions were under LA, 52% under GA, and 4% under IV sedation. 30% were simple extractions, 68% were surgical removals, 2% were unspecified. 89% extractions were performed by an Associate Specialist, 5% by a consultant, and 6% by unspecified grade of clinician. The rate of IDN injuries was 2.9% (n=4), higher than standard (0.3%). The rate of LN injuries was 0.7% (n=1), same as standard (0.7%). The 5 cases of neurosensory deficits are discussed in detail. Conclusions/Clinical Relevance: The rate of ID nerve injuries was higher than the standard. The rate of LN complications was lower than the standard.

Keywords: inferior dental nerve, lingual nerve, nerve injuries, third molars

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Authors: Walter Bernhofer, Peter Haber, Tobias Mayer, Manfred Mayr, Markus Ziegler

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Current preventive maintenance measures are cost intensive and not efficient. With the available sensor data of state of the art internet of things devices new possibilities of automated data processing emerge. Current advances in data science and in machine learning enable new, so called predictive maintenance technologies, which empower data scientists to forecast possible system failures. The goal of this approach is to cut expenses in preventive maintenance by automating the detection of possible failures and to improve efficiency and quality of maintenance measures. Additionally, a centralization of the sensor data monitoring can be achieved by using this approach. This paper describes the approach of three students to define a reference architecture for a predictive maintenance solution in the internet of things domain with a connected smartphone app for service technicians. The reference architecture is validated by a case study. The case study is implemented with current Microsoft Azure cloud technologies. The results of the case study show that the reference architecture is valid and can be used to achieve a system for predictive maintenance execution with the cloud components of Microsoft Azure. The used concepts are technology platform agnostic and can be reused in many different cloud platforms. The reference architecture is valid and can be used in many use cases, like gas station maintenance, elevator maintenance and many more.

Keywords: case study, internet of things, predictive maintenance, reference architecture

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Authors: S. B. Rathna Kumar, Sandya K. Varudhini, Aparna Ravichandran

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Telugu is a south central Dravidian language spoken in Andhra Pradesh, a southern state of India. The available speech identification tests in Telugu have been developed to determine the communication problems of individuals having a flat frequency hearing loss. These conventional speech audiometric tests would provide redundant information when used on individuals with high-frequency sloping hearing loss because of better hearing sensitivity in the low- and mid-frequency regions. Hence, conventional speech identification tests do not indicate the true nature of the communication problem of individuals with high-frequency sloping hearing loss. It is highly possible that a person with a high-frequency sloping hearing loss may get maximum scores if conventional speech identification tests are used. Hence, there is a need to develop speech identification test materials that are specifically designed to assess the speech identification performance of individuals with high-frequency sloping hearing loss. The present study aimed to develop speech identification test for individuals with high-frequency sloping hearing loss in Telugu. Individuals with high-frequency sloping hearing loss have difficulty in perception of voiceless consonants whose spectral energy is above 1000 Hz. Hence, the word lists constructed with phonemes having mid- and high-frequency spectral energy will estimate speech identification performance better for such individuals. The phonemes /k/, /g/, /c/, /ṭ/ /t/, /p/, /s/, /ś/, /ṣ/ and /h/are preferred for the construction of words as these phonemes have spectral energy distributed in the frequencies above 1000 KHz predominantly. The present study developed two word lists in Telugu (each word list contained 25 words) for evaluating speech identification performance of individuals with high-frequency sloping hearing loss. The performance of individuals with high-frequency sloping hearing loss was evaluated using both conventional and high-frequency word lists under recorded voice condition. The results revealed that the developed word lists were found to be more sensitive in identifying the true nature of the communication problem of individuals with high-frequency sloping hearing loss.

Keywords: speech identification test, high-frequency sloping hearing loss, recorded voice condition, Telugu

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Authors: P. Sam Vimal Rajkumar, K. Priyanga

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Acoustics is the scientific study of sound which includes the effect of reflection, refraction, absorption, diffraction and interference. Sound can be considered as a wave phenomenon. A sound wave is a longitudinal wave where particles of the medium are temporarily displaced in a direction parallel to energy transport and then return to their original position. The vibration in a medium produces alternating waves of relatively dense and sparse particles –compression and rarefaction respectively. The resultant variation to normal ambient pressure is translated by the ear and perceived as sound. Today much importance is given to the acoustical environment. The noise sources are increased day by day and annoying level is strongly violated in different locations by traffic, sound systems, and industries. There is simple evidence showing that the high noise levels cause sleep disturbance, hearing loss, decrease in productivity, learning disability, lower scholastic performance and increase in stress related hormones and blood pressure. Therefore, achieving a pleasing and noise free environment is one of the endeavours of many a research groups. This can be obtained by using various techniques. One such technique is by using suitable materials with good sound absorbing properties. The conventionally used materials that possess sound absorbing properties are rock wool or glass wool. In this work, an attempt is made to use synthetic material in both fibrous and sheet form and use it for manufacturing of non-woven for sound absorption.

Keywords: acoustics, fibre, non-woven, noise, sound absorption properties, sound absorption coefficient

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Authors: Teresa M. Odipo

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Inclusive physical education and an inclusive educational approach in German schools have received much attention in recent years due to the UN Convention on the rights of persons with disabilities proposals, which came into force in Germany in 2009. The aim of inclusive PE is to include children with disabilities and able bodied children, based on the idea, that all children should attend school together. While PE mostly took place in a heterogeneous environment, introducing children with all kinds of disabilities posed more challenges to the teachers, when children with disabilities were included. Therefore it is important that the educational approach should include pre-service teachers’ (PST) self-efficacy for and their attitudes towards inclusive practices. The PSTs’ self-efficacy for inclusive practices is one of the strongest predictors of the success of the inclusion reforms introduced in 2009, in order to improve PSTs’ ability to handle these very new challenges. PE stands out because the very nature of sport involves the body which means that all children, especially those with special needs should be treated in an appropriate manner. Up till now, it has been mostly English-speaking countries that have been assessed for inclusive practices in PE. Due to the lack of research in Germany, there is a strong need to question PSTs’ prepared-ness. This paper presents results from the 2016 survey conducted on around 100 PSTs by the German University of Sports in Cologne and opens up new directions within PSTs’ education, concerning their attitudes and self-efficacy towards inclusive PE. These new aspects will be included in the construction of new learning and teaching tools to improve pre-service teachers’ education for inclusive Physical Education.

Keywords: attitudes, inclusive physical education, pre-service teachers, self-efficacy

Procedia PDF Downloads 347