Search results for: immersive learning BIM

Authors: Sara Cumming, Julianne DiSanto, Leah Burton

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Homelessness in Canada is a persistent problem. It has been widely argued that the best tactic for eradicating homelessness is to approach social issues from a Housing First perspective—an approach that centers on quickly moving people into permanent and independent housing and then providing them additional support and services as needed. It is recognized that life skills training is both necessary and an effective way to reduce cyclical homelessness; however, there is a scarcity of research on effective ways to teach life skills; this problem was exacerbated in a pandemic context, where in-person delivery was severely restricted or no longer possible. Very little attention has been paid to the diverse cultural needs of clients in a multicultural context and the need to foster cultural knowledge/awareness in individuals to successfully contribute to the cultural safety of communities. This research attempts to fill these gaps in the literature and in practice by employing a community-engaged research (CER) approach. Academic, government, funders, front-line staff, and clients at 15 not-for-profits from across the Greater Toronto Area in Ontario, Canada, collaborated to co-create a virtual, client-centric, equity, diversity, and inclusion (EDI) informed life skill learning management system. We employed a triangulation methodology for this research. An environmental scan was conducted for best practices. Two separate Creative Problem Solving Sessions were held with over 100 front-line workers, managers, and executive directors who work with homeless populations. Quantitative and open-ended surveys were completed by over 200 individuals with experience with homelessness. All sections of this research aimed to discover the areas of skills that individuals need to maintain housing and to ascertain what a more client-driven EDI approach to life skills training should include. This research will showcase which life skills are deemed essential for homeless and precariously housed individuals.

Keywords: homelessness, Housing First, life skills, community engaged research

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Authors: Kuo-Chun Chien, Chia-Hui Chang, Ren-Der Sun

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Legal Judgment Prediction (LJP) is a subtask for legal AI. Its main purpose is to use the facts of a case to predict the judgment result. In Taiwan's criminal procedure, when prosecutors complete the investigation of the case, they will decide whether to prosecute the suspect and which article of criminal law should be used based on the facts and evidence of the case. In this study, we collected 305,240 indictments from the public inquiry system of the procuratorate of the Ministry of Justice, which included 169 charges and 317 articles from 21 laws. We take the crime facts in the indictments as the main input to jointly learn the prediction model for law source, article, and charge simultaneously based on the pre-trained Bert model. For single article cases where the frequency of the charge and article are greater than 50, the prediction performance of law sources, articles, and charges reach 97.66, 92.22, and 60.52 macro-f1, respectively. To understand the big performance gap between articles and charges, we used a bipartite graph to visualize the relationship between the articles and charges, and found that the reason for the poor prediction performance was actually due to the wording precision. Some charges use the simplest words, while others may include the perpetrator or the result to make the charges more specific. For example, Article 284 of the Criminal Law may be indicted as “negligent injury”, "negligent death”, "business injury", "driving business injury", or "non-driving business injury". As another example, Article 10 of the Drug Hazard Control Regulations can be charged as “Drug Control Regulations” or “Drug Hazard Control Regulations”. In order to solve the above problems and more accurately predict the article and charge, we plan to include the article content or charge names in the input, and use the sentence-pair classification method for question-answer problems in the BERT model to improve the performance. We will also consider a sequence-to-sequence approach to charge prediction.

Keywords: legal judgment prediction, deep learning, natural language processing, BERT, data visualization

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Authors: Gabriela Macera DiFilippo

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The world watched in disbelief as George Floyd was killed by a policeman. The images from the scene were made more memorable by Mr. Floyd’s pleas and cries for his mother. In the aftermath of this tragedy, the Black Lives Matter movement gained momentum. Weeks and months after the protests, global interest in learning about tackling systemic racism erupted. One must wonder how school children of color viewed and processed this trauma. This study will examine the kinds of trauma experienced by children of color and the opportunity for school mental health providers to support these children. This study used literature searches that were previously conducted for proven and practical assessment methods that can help deal with racial trauma for children. As part of the assessment, trauma symptoms experienced by children of color were summarized and characterized in a non-imperial manner. The research was also will be done in practical ways to make adequate and effective mental health services available in schools and lessen the stigma. This research study found that there is a need to provide an analysis of the ongoing racial trauma of children of color after the death of George Floyd. Impactful and appropriate assessment methods, such as surveys, were presented to all school professionals. Lastly, this paper attempted to provide mental health professionals with the tools to screen and provide guidance based on unequivocal, unbiased methods for helping these children. There is a need for both schools and community leaders to ensure that every child has access to mental health care and is being assessed for their overall well-being. There is a need to educate the communities about racial trauma and its impact on individuals, especially children. School mental health professionals are encouraged to offer and educate schools and communities about racial trauma awareness, its importance, and ways to cope with it in different settings. The delivery of these informed services should focus on behavioral health and must be sensitive to children of color and different ways of self-care.

Keywords: trauma, children, black psychology, students

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Authors: Gbone Akou Sophie

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Lome state in Togo is considered to have the highest HIV prevalence in Togo according to NAIIS 2023, with the prevalence of 5.5%, Female Sex Workers (FSW) are one of the most vulnerable population, and they are vital in HIV programming. They have the highest HIV prevalence compared to others such as HRM, PWID and Transgender in lome State, Togo. Evidence from Integrated Biological Behavioral Surveillance Survey shows increasing burden of HIV infection from 13.7% in 20018 to 17.2% in 2020 and now 22.9% in 2021 among Female Sex Workers (FSW). This shows their HIV prevalence has been rising over time. The vulnerability status of the FSW in the riverine areas of lome is heightened because of cultural and economic issues where there is exchange of sex for commodities with cross border traders as well as limited access to HIV prevention information. Methods:A cross sectional study which recruited 120 FSW from two Riverine LGAs of Agoe and Kpehenou LGA of Lome State using both snowballing and simple random sampling technique. While semi-structured questionnaire was used as an instrument for data collection among the 120 FSW respondents. Additional information was also elicited from 10 FSW key opinion leaders and community members through in-depth interviews (IDI). Results: 44(36%) of respondents were willing to receive regular HIV care and services as well as visit for STI check-ups at any service point. However, 47(40%) were willing to receive services at private facilities alone, 10 (8%) were willing to receive services at public facilities, 6 (5%) were willing to access services in their homes rather than in the health facility. 13 (11%) were also willing to have peers assist in getting HIV testing services. Conclusion: integrated differentiated model of care for HIV services helps improve HIV services uptake among FSW community especially in the hard- to reach riverine areas which will further lead to epidemic control. Also targeted HIV information should be designed to suit the learning needs of the hard-to reach communities like the riverine areas. More peer educators should be engaged to ensure information and other HIV services reach the riverine communities.

Keywords: female sex workers ( FSW), human immuno-deficiency virus(HIV), prevanlence, service delivery

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Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

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Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

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Authors: Manish Madappa, Madhavi Gayathri Raman

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The primary vehicle of human communication is language. A breakdown occurring in any aspect of communication may lead to frustration and isolation among the learners and the teachers. Over seven percent of the population in the world currently experience limitations and those children who exhibit a deviant/deficient language acquisition curve even when being in a language rich environment as their peers may be at risk of having a language disorder or language impairment. The difficulty may be in the word level [vocabulary/word knowledge] and/or the sentence level [syntax/morphology) Children with SLI appear to be developing normally in all aspects except for their receptive and/or expressive language skills. Thus, it is utmost importance to identify children with or at risk of SLI so that an early intervention can foster language and social growth, provide the best possible learning environment with special support for language to be explicitly taught and a step in providing continuous and ongoing support. The present study looks at Kannada English bilingual children and works towards identifying children at risk of “specific language impairment”. The study was conducted through an exploratory study which systematically enquired into the narratives of young Kannada-English bilinguals and to investigate the data for story structure in their narrative formulations. Oral narrative offers a rich source of data about a child’s language use in a relatively natural context. The fundamental objective is to ensure comparability and to be more universal and thus allows for the evaluation narrative text competence. The data was collected from 10 class three students at a primary school in Mysore, Karnataka and analyzed for macrostructure component reflecting the goal directed behavior of a protagonist who is motivated to carry out some kind of action with the intention of attaining a goal. The results show that the children exhibiting a deviation of -1.25 SD are at risk of SLI. Two learners were identified to be at risk of Specific Language Impairment with a standard deviation of more the 1.25 below the mean score.

Keywords: bilingual, oral narratives, SLI, macrostructure

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Authors: Angelis P. Barlampas

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Purpose of Learning Objective: This case depicts the need for cooperation between the emergency department and the radiologist to achieve the best diagnostic result for the patient. The clinical picture must correlate well with the radiology report and when it does not, this is not necessarily someone’s fault. Careful interpretation and good knowledge of the limitations, advantages and disadvantages of each imaging procedure are essential for the final diagnostic goal. Methods or Background: A patient was brought to the emergency department by their relatives. He was suddenly confused and his mental status was altered. He hadn't any history of mental illness and was otherwise healthy. A computing tomography scan without contrast was done, but it was unremarkable. Because of high clinical suspicion of probable neurologic disease, he was admitted to the hospital. Results or Findings: Another T was done after 48 hours. It showed a hypodense region in both thalamic areas. Taking into account that the first CT was normal, but the initial clinical picture of the patient was alerting of something wrong, the repetitive CT exam is highly suggestive of a probable diagnosis of bilateral thalamic infractions. Differential diagnosis: Primary bilateral thalamic glioma, Wernicke encephalopathy, osmotic myelinolysis, Fabry disease, Wilson disease, Leigh disease, West Nile encephalitis, Greutzfeldt Jacob disease, top of the basilar syndrome, deep venous thrombosis, mild to moderate cerebral hypotension, posterior reversible encephalopathy syndrome, Neurofibromatosis type 1. Conclusion: As is the case of limitations for any imaging procedure, the same applies to CT. The acute ischemic attack can not depict on CT. A period of 24 to 48 hours has to elapse before any abnormality can be seen. So, despite the fact that there are no obvious findings of an ischemic episode, like paresis or imiparesis, one must be careful not to attribute the patient’s clinical signs to other conditions, such as toxic effects, metabolic disorders, psychiatric symptoms, etc. Further investigation with MRI or at least a repeated CT must be done.

Keywords: CNS, CT, thalamus, emergency department

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Authors: Mohamed Karodia

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Accountancy as a subject is one of the sciences that for many years has been perceived as a difficult subject to study and teach. Yet, it continuously attracts scholars graduating from school and entering Higher Education Institutions as a subject of choice and career. The teaching and learning of this subject have not been easy and has evolved and progressed over the past few decades however students still find it difficult to study and this has resulted in poor student achievement. In search of solutions, this study has considered the effect and efficacy that study skills have on the performance of Accountancy students and in particular students studying Second Year Diploma in Accountancy at the University of Johannesburg. These students appear to have a lack of appropriate study skills and as a result of these impacts on their performance in the courses, they are studying. This study also focuses on strategies to enhance Second Year Diploma Accountancy students’ academic performance. A literature review was conducted to investigate what scholarly literature suggests about study skills, in general, and in particular for Accountancy to be successful. In order to determine what study skills Second Year Accountancy students are applying when they learn and why they are failing the Accountancy examinations and formal class tests, the study adopted the quantitative research method. A questionnaire addressing various aspects of study skills, studying accountancy and studying, in general, was provided to 800 students studying Second Year Diploma in Accountancy at the University of Johannesburg’s Soweto Campus. The quantitative data collected were analyzed using descriptive statistics in the form of proportions, frequencies, means, and standard deviations, t-tests to compare differences between two groups as well as correlations between variables. Based on the findings of this study, it is recommended that students are provided with courses in time management, procrastination, reading, note taking and writing, test preparation techniques as well as study attitude. Lecturers spend more time teaching students how to study in general as well as accountancy specifically preferably at the first-year level before proceeding to the second year. It is also recommended that the University implements a study skills course to assist the students with studying.

Keywords: accountancy, skills, strategies, study

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Authors: Chingwen Yeh, I. Chen Huang

Abstract:

This paper aims to conduct a case study on kinesthetic intelligence development intervention with a child who has Asperger symptom identified by physician. First, the characteristics of Asperger were defined based on the related literature. Some Asperger's people are born with outstanding insight and are good at solving complex and difficult problems. In contrast to high-functioning autistic, Asperger children do not lose their ability to express themselves verbally. However in the cognitive function, they focus mainly on the things they are interested in instead of paying attention to the whole surrounding situation. Thus it is difficult for them not only to focus on things that they are not interesting in, but also to interact with people. Secondly, 8-weeks of kinesthetic intelligence development courses were designed within a series of physical action that including the following sections: limbs coordination, various parts of body rhythm changes, strength and space awareness and breathing practice. In classroom observations were recorded both on words and with video as the qualitative research data. Finally, in-depth interview with the case child’s teachers, parents and other in class observers were documented on a weekly base in order to examine the effectiveness of before and after the kinesthetic intelligence development course and to testify the usefulness of the lesson plan. This research found that the case child has improved significantly in terms of attention span and body movement creativity. In the beginning of intervention, the case child made less eyes contact with others. The instructor needed to face the case child to confirm the eyes contact. And the instructor also used various adjective words as guiding language for all kinds of movement sequence practice. The result can cause the case child’s attention and learning motivation. And the case child understand what to do to enhance kinesthetic intelligence. These authors hope findings of this study can contribute as reference for the further research on the related topic.

Keywords: asperger symptom, body rhythm, kinesthetic intelligence, space awareness

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Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Ali Akbar Jabbari

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The present study assessed the acquisition of L3 French direct objects by Persian speakers who had already learned English as their L2. The ultimate goal of this paper is to extend the current knowledge about the CLI phenomenon in the realm of third language acquisition by examining the role of Persian and English as background languages and learners’ English level of proficiency in their performance on French direct object. To fulfill this, the assumptions of three L3 hypotheses, namely L1 Transfer, L2 Status Factor, and Cumulative Enhancement Model, were examined. The research sample was comprised of 40 undergraduate students in the fields of English language and literature and translation studies at Birjand University in Iran. According to the English proficiency level of learners revealed by the Quick Oxford English Placement test, the participants were grouped as upper intermediate and lower intermediate. A grammaticality judgment and a translation test were administered to gather the required data on learners' comprehension and production of the desired structure in French. It was demonstrated that the rate of positive transfer from previously learned languages was more potent than the rate of negative transfer. A Comparison of groups' performances revealed a significant difference between upper and lower intermediate groups in positing French direct objects correctly. However, the upper intermediate group did not significantly differ from the lower intermediate group in negative transfer. It can be said that by increasing the L2 proficiency of the learners, they could use their previous linguistic knowledge more efficiently. Although further examinations are needed, the current study contributed to a better characterization of cross-linguistic influence in third language acquisition. The findings help French teachers and learners to positively exploit the prior knowledge of Persian and English and apply it in in the multilingual context of French direct object's teaching and learning process.

Keywords: Cross-Linguistic Influence, Persian, French & English Direct Object, Third Language Acquisition, Language Transfer

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Authors: Ivan Gunass Govender, Andrea Giampiccoli

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A developmental state should use community engagement to facilitate socio-economic development for disadvantaged groups and individual members of society through empowerment, social justice, sustainability, and self-reliance. In this regard, community-based tourism (CBT) as a growing market should be an indigenous effort aided by external facilitation. Since this form of tourism presents its own preconditions, characteristics, and challenges, it could be guided by higher education institutions engagement. In particular, the facilitation should not only serve to assist the community members to reach their own goals; but rather also focus on learning through knowledge creation and sharing with the engagement of higher education institutions. While the increased relevance of CBT has produced various CBT manuals (or handbooks/guidelines) documents aimed to ‘teach’ and assist various entities in CBT development, this research aims to analyse the current monitoring & evaluation (M&E) manuals and thereafter, propose an M&E model for CBT. It is important to mention that all too often effective monitoring is seldom carried out thus risking the long-term sustainability and improvement of the CBT ventures. Therefore, the proposed model will also consider some inputs external to the tourism field, but in relation to local economic development (LED) matters from the previously proposed development monitoring and evaluation system framework. M&E should be seen as fundamental components of any CBT initiative, and the whole CBT intervention should be evaluated. In this context, M&E in CBT should go beyond strict ‘numerical’ economic matters and should be understood in a holistic development. In addition, M&E in CBT should not consider issues in various ‘compartments’ such as tourists, tourism attractions, CBT owners/participants, and stakeholder engagement but as interdependent components of a macro-ecosystem. Finally, the external facilitation process should be structured in a way to promote community self-reliance in both the intervention and the M&E process. The research will attempt to propose an M&E model for CBT so as to enhance the CBT possibilities of long-term growth and success through effective collaborations with key stakeholders.

Keywords: community-based tourism, community-engagement, monitoring and evaluation, stakeholders

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Authors: Yu-Ching Cheng, Yi-Kai Juan, Daniel Castro

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Energy consumption of buildings has been an increasing concern for researchers and practitioners in the last decade. Sustainable building renovation can reduce energy consumption and carbon dioxide emissions; meanwhile, it also can extend existing buildings useful life and facilitate environmental sustainability while providing social and economic benefits to the society. School buildings are different from other designed spaces as they are more crowded and host the largest portion of daily activities and occupants. Strategies that focus on reducing energy use but also improve the students’ learning environment becomes a significant subject in sustainable school buildings development. A decision model is developed in this study to solve complicated and large-scale combinational, discrete and determinate problems such as school renovation projects. The task of this model is to automatically search for the most cost-effective (lower cost and higher quality) renovation strategies. In this study, the search process of optimal school building renovation solutions is by nature a large-scale zero-one programming determinate problem. A* is suitable for solving deterministic problems due to its stable and effective search process, and genetic algorithms (GA) provides opportunities to acquire global optimal solutions in a short time via its indeterminate search process based on probability. These two algorithms are combined in this study to consider trade-offs between renovation cost and improved quality, this decision model is able to evaluate current school environmental conditions and suggest an optimal scheme of sustainable school buildings renovation strategies. Through adoption of this decision model, school managers can overcome existing limitations and transform school buildings into spaces more beneficial to students and friendly to the environment.

Keywords: decision model, school buildings, sustainable renovation, genetic algorithm, A* search algorithm

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Authors: Hadj Sahraoui Omar, Kebir Lahcen Wahib, Bennia Ahmed

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Interferometric Synthetic Aperture Radar (InSAR) coherence is a crucial parameter for accurately monitoring ground deformation and environmental changes. However, coherence can be degraded by various factors such as temporal decorrelation, atmospheric disturbances, and geometric misalignments, limiting the reliability of InSAR measurements (Omar Hadj‐Sahraoui and al. 2019). To address this challenge, we propose an innovative hybrid approach that combines artificial intelligence (AI) with advanced filtering techniques to optimize interferometric coherence in InSAR data. Specifically, we introduce a Convolutional Neural Network (CNN) integrated with the Lee filter to enhance the performance of radar interferometry. This hybrid method leverages the strength of CNNs to automatically identify and mitigate the primary sources of decorrelation, while the Lee filter effectively reduces speckle noise, improving the overall quality of interferograms. We develop a deep learning-based model trained on multi-temporal and multi-frequency SAR datasets, enabling it to predict coherence patterns and enhance low-coherence regions. This hybrid CNN-SAR with Lee filtering significantly reduces noise and phase unwrapping errors, leading to more precise deformation maps. Experimental results demonstrate that our approach improves coherence by up to 30% compared to traditional filtering techniques, making it a robust solution for challenging scenarios such as urban environments, vegetated areas, and rapidly changing landscapes. Our method has potential applications in geohazard monitoring, urban planning, and environmental studies, offering a new avenue for enhancing InSAR data reliability through AI-powered optimization combined with robust filtering techniques.

Keywords: CNN-SAR, Lee Filter, hybrid optimization, coherence, InSAR phase unwrapping, speckle noise reduction

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Authors: D. Zhigulskaya, V. Anisimov, A. Pikunov, K. Babanova, S. Zuev, A. Latyshkova, K. Сhernozatonskiy, A. Revazov

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Electrophysiology of information processing in reading is certainly a popular research topic. Natural reading, however, has been relatively poorly studied, despite having broad potential applications for learning and education. In the current study, we explore the relationship between text categories and spontaneous electroencephalogram (EEG) while reading. Thirty healthy volunteers (mean age 26,68 ± 1,84) participated in this study. 15 Russian-language texts were used as stimuli. The first text was used for practice and was excluded from the final analysis. The remaining 14 were opposite pairs of texts in one of 7 categories, the most important of which were: interesting/boring, fiction/non-fiction, free reading/reading with an instruction, reading a text/reading a pseudo text (consisting of strings of letters that formed meaningless words). Participants had to read the texts sequentially on an Apple iPad Pro. EEG was recorded from 12 electrodes simultaneously with eye movement data via ARKit Technology by Apple. EEG spectral amplitude was analyzed in Fz for theta-band (4-8 Hz) and in C3, C4, P3, and P4 for alpha-band (8-14 Hz) using the Friedman test. We found that reading an interesting text was accompanied by an increase in theta spectral amplitude in Fz compared to reading a boring text (3,87 µV ± 0,12 and 3,67 µV ± 0,11, respectively). When instructions are given for reading, we see less alpha activity than during free reading of the same text (3,34 µV ± 0,20 and 3,73 µV ± 0,28, respectively, for C4 as the most representative channel). The non-fiction text elicited less activity in the alpha band (C4: 3,60 µV ± 0,25) than the fiction text (C4: 3,66 µV ± 0,26). A significant difference in alpha spectral amplitude was also observed between the regular text (C4: 3,64 µV ± 0,29) and the pseudo text (C4: 3,38 µV ± 0,22). These results suggest that some brain activity we see on EEG is sensitive to particular features of the text. We propose that changes in theta and alpha bands during reading may serve as electrophysiological tools for assessing the reader’s cognitive state as well as his or her attitude to the text and the perceived information. These physiological markers have prospective practical value for developing technological solutions and biofeedback systems for reading in particular and for education in general.

Keywords: EEG, natural reading, reader's cognitive state, theta-rhythm, alpha-rhythm

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Authors: Prima Gusti Yanti, Fairul Zabadi

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The purpose of the study is to find out relation of moral massage with the authority ang globalization in proverb. Proverb is one of the many forms of cultural identity of the Indonesian/Malay people fulled with moral values. The values contained within those proverbs are beneficial not only to the society, but also to those who held power amidst on this era of globalization. The method being used is qualitative research by using content analysis which is done by describing and uncovering the forms and meanings of proverbs used within Indonesia Minangkabau society. Sources for this study’s data were extracted from a Minangkabau native speaker in the subdistrict of Tanah Abang, Jakarta. Said sources were retrieved through a series of interviews with the Minangkabau native speaker, whose speech is still adorned with idiomatic expressions. The research findings show that there existed 30 proverbs or idiomatic expressions in the Minangkabau language that are often used by its indigenous people. The thirty data contain moral values that are closely interwoven with the matter of power and globalization. Analytical results show that there are fourteen moral values contained within proverbs reflect a firm connection between rule and power in globalization; such as: responsible, brave, togetherness and consensus,tolerance, politeness, thorough and meticulous,honest and keeping promise, ingenious and learning, care, self-correction, be fair, alert, arbitrary, self-awareness. Structurally, proverbs possess an unchangeably formal construction; symbolically, proverbs possess meanings that are clearly decided through ethnographic communicative factors along with situational and cultural contexts. Values contained within proverbs may be used as a guide in social management, be it between fellow men, men between nature, or even men between their Creator. Therefore, the meanings and values contained within the morals of proverbs could also be utilized as a counsel for those who rule and in charge of power in order to stem the tides of globalization that had already spread into sectoral, territorial and educational continuums.

Keywords: continuum, globalization, identity, proverb, rule-power

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Authors: M. P. Dandekar, A. P. Bharne, P. T. Borkar, D. M. Kokare, N. K. Subhedar

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Ethanol ingestion by the mother ensue adverse consequences for her offspring. Herein, we examine the behavioral phenotype and neural substrate of the offspring of the mother on ethanol. Female rats were fed with ethanol-containing liquid diet from 8 days prior of conception and continued till 25 days post-parturition to coincide with weaning. Behavioral changes associated with anxiety, depression and learning and memory were assessed in the offspring, after they attained adulthood (day 85), using elevated plus maze (EPM), forced swim (FST) and novel object recognition tests (NORT), respectively. The offspring of the alcoholic mother, compared to those of the pair-fed mother, spent significantly more time in closed arms of EPM and showed more immobility time in FST. Offspring at the age of 25 and 85 days failed to discriminate between novel versus familiar object in NORT, thus reflecting anxiogenic, depressive and amnesic phenotypes. Neuropeptide cocaine- and amphetamine-regulated transcript peptide (CART) is known to be involved in central effects of ethanol and hence selected for the current study. Twenty-five days old pups of the alcoholic mother showed significant augmentation in CART-immunoreactivity in the cells of Edinger-Westphal (EW) nucleus and lateral hypothalamus. However, a significant decrease in CART-immunoreactivity was seen in nucleus accumbens shell (AcbSh), lateral part of bed nucleus of the stria terminalis (BNSTl), locus coeruleus (LC), hippocampus (CA1, CA2 and CA3), and arcuate nucleus (ARC) of the pups and/or adults offspring. While no change in the CART-immunoreactive fibers of AcbSh and BNSTl, CA2 and CA3 was noticed in the 25 days old pups, the CART-immunoreactive cells in EW and paraventricular nucleus (PVN), and fibers in the central nucleus of amygdala of 85 days old offspring remained unaffected. We suggest that the endogenous CART system in these discrete areas, among other factors, may be a causal to the abnormalities in the next generation of an alcoholic mother.

Keywords: anxiety, depression, CART, ethanol, immunocytochemistry

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Authors: Leandros A. Maglaras, Jianmin Jiang

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The protection of the national infrastructures from cyberattacks is one of the main issues for national and international security. The funded European Framework-7 (FP7) research project CockpitCI introduces intelligent intrusion detection, analysis and protection techniques for Critical Infrastructures (CI). The paradox is that CIs massively rely on the newest interconnected and vulnerable Information and Communication Technology (ICT), whilst the control equipment, legacy software/hardware, is typically old. Such a combination of factors may lead to very dangerous situations, exposing systems to a wide variety of attacks. To overcome such threats, the CockpitCI project combines machine learning techniques with ICT technologies to produce advanced intrusion detection, analysis and reaction tools to provide intelligence to field equipment. This will allow the field equipment to perform local decisions in order to self-identify and self-react to abnormal situations introduced by cyberattacks. In this paper, an intrusion detection module capable of detecting malicious network traffic in a Supervisory Control and Data Acquisition (SCADA) system is presented. Malicious data in a SCADA system disrupt its correct functioning and tamper with its normal operation. OCSVM is an intrusion detection mechanism that does not need any labeled data for training or any information about the kind of anomaly is expecting for the detection process. This feature makes it ideal for processing SCADA environment data and automates SCADA performance monitoring. The OCSVM module developed is trained by network traces off line and detects anomalies in the system real time. The module is part of an IDS (intrusion detection system) developed under CockpitCI project and communicates with the other parts of the system by the exchange of IDMEF messages that carry information about the source of the incident, the time and a classification of the alarm.

Keywords: cyber-security, SCADA systems, OCSVM, intrusion detection

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Authors: Mahmoud B. Rokaya

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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

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Authors: Nopparet Thammasaranyakun

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This research objects are: 1: To study the biodiversity of medicinal plants used for food and medicinal tourism economies along the Phu Sing district Sisaket province. 2: To study the use of medicinal plants used for food and medicinal tourism economies along the Phu Sing district Sisaket province. 3: To provide a database of information on biodiversity for food and medicinal plants and medicinal tourism economies along the Phu Sing district Sisaket province. 4: Learn to create a biodiversity of medicinal plants used as food and treatment by Journeys economic Phu Sing district Sisaket province Boundaries used in this study was the Phu Sing district. Population and Agricultural Development Center, rayong Mun due to the initiative for youth Local, Government Health officials, community leaders, teachers, students, schools, the local people and tourists. Sage wisdom to know the herbs and women's groups, OTOP Phu Sing district in SiisaKet province. By selecting the specific data that way. The process of participatory action research (PAR) is a community-based research. The method of collecting qualitative data. (Qualitative) tool is used from context, Community areas, interview and Taped recordings. Observation and focus group data was statistically analyzed using descriptive statistics (Descriptive Statistics). The results findings: 1- A study of the biodiversity of plants used for food and medicinal tourism economies along the Phu Sing district Sisaket province. Were used in the dry season and the rainy season find the medicinal plants of 251 species 41 types of drugs. 2- The study utilized medicinal plants used as food and the treatment of indigenous Phu Sing Sisaket province. Found 251 species have medicinal properties that are used for food and medicinal purposes 41 types of drugs. 3- Of the database technology of biodiversity for food and medicinal plants used by local treatment Phu Sing district Sisaket province. A data base of 251 medicinal species 41 types of drugs is used for food and medicinal properties Sisaket province. 4- learning the biodiversity of medicinal plants used for food and medicinal tourism economies along the Phu Sing district Sisaket province.

Keywords: utilization of biodiversity, peaces herbals, used as Food, Sing district, sisaket

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Authors: Kathryn Redmond, Mojdeh Asadollahi Pajouh, Grace Panther, Rick Evans, Stacey Kulesza, Jia Liang

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An on-going focus in engineering education research is on increasing the number of women in engineering. While the number of women participating in engineering project teams has increased over the past five years, the number of women enrolled in engineering colleges remains stagnant. Previous studies have explored why the number of women enrolled in engineering colleges remains small. In doing so, researchers focused primarily on negative experiences women encountered. Instead of looking at negative experiences, which can further deter women from entering the field, the aim of this study is to explore the personal and institutional factors that allow women to succeed and thrive in undergraduate engineering programs. There are two research questions addressed in this paper. The first is: what are the personal traits and characteristics that allow women to thrive in engineering? The other is: what are the institutional policies and culture, as well as micro-level behaviors on project teams, that influence the environment for women to thrive in engineering? Two women studying engineering at an R1 university were interviewed. Each woman was interviewed three times for a total of six interviews. The phenomenographic interviews focused on the lived experiences of the participants to better understand thriving in engineering. The first interview focused on the women’s personal life and background, the second on their learning journey and project team experiences, and the third focused on videos the women took through a method called Photovoice. Interviews were transcribed, and an inductive thematic analysis was conducted. Four themes were identified. Multiple coders were utilized to ensure trustworthiness and increase interrater reliability. Results indicate that thriving women have supportive families, experienced gender biases, and enjoy hands-on engineering and creating a final product. These traits and experiences may help inspire younger women to pursue engineering degrees and can help inform institutions as they make policy changes to support women. Additional women will be recruited from four different universities to further develop a theoretical framework to help inform institutions in how they can support women to thrive in engineering.

Keywords: diversity, inclusion, project teams, women in engineering

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Authors: Ryan Villafuerte Lansangan

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Assessing students’ understanding in the microscopic level of an abstract subject like chemistry poses a challenge to teachers. Literature reveals that the use of representations serves as an essential avenue of measuring the extent of understanding in the discipline as an alternative to traditional assessment methods. This undertaking explored the representational competence profile of high school students from the University of Santo Tomas High School in understanding selected chemical principles and correlate this with their academic profile in chemistry based on their performance in the academic achievement examination in chemistry administered by the Center for Education Measurement (CEM). The common misconceptions of the students on the selected chemistry principles based on their representations were taken into consideration as well as the students’ views regarding their understanding of the role of chemical representations in their learning. The students’ level of representation task instrument consisting of the main lessons in chemistry with a corresponding scoring guide was prepared and utilized in the study. The study revealed that most of the students under study are unanimously rated as Level 2 (symbolic level) in terms of their representational competence in understanding the selected chemical principles through the use of chemical representations. Alternative misrepresentations were most observed on the students’ representations on chemical bonding concepts while the concept of chemical equation appeared to be the most comprehensible topic in chemistry for the students. Data implies that teachers’ representations play an important role in helping the student understand the concept in a microscopic level. Results also showed that the academic achievement in the chemistry of the students based on the standardized CEM examination has a significant association with the students’ representational competence. In addition, the students’ responses on the students’ views in chemical representations questionnaire evidently showed a good understanding of what a chemical representation or a mental model is by drawing a negative response that these tools should be an exact replica. Moreover, the students confirmed a greater appreciation that chemical representations are explanatory tools.

Keywords: chemical representations, representational competence, academic profile in chemistry, secondary students

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Authors: Emir Alaca, Hasbi Apaydin, Rohullah Rahmatullah, Necibe Fusun Oyman Serteller

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In recent years, Permanent Magnet Synchronous Motors (PMSMs) have found extensive applications in various industrial sectors, including electric vehicles, wind turbines, and robotics, due to their high performance and low losses. Accurate mathematical modeling of PMSMs is crucial for advanced studies in electric machines. To enhance the effectiveness of graduate-level education, incorporating virtual or real experiments becomes essential to reinforce acquired knowledge. Virtual laboratories have gained popularity as cost-effective alternatives to physical testing, mitigating the risks associated with electrical machine experiments. This study presents a MATLAB-based Graphical User Interface (GUI) for PMSMs. The GUI offers a visual interface that allows users to observe variations in motor outputs corresponding to different input parameters. It enables users to explore healthy motor conditions and the effects of short-circuit faults in the one-phase winding. Additionally, the interface includes menus through which users can access equivalent circuits related to the motor and gain hands-on experience with the mathematical equations used in synchronous motor calculations. The primary objective of this paper is to enhance the learning experience of graduate and doctoral students by providing a GUI-based approach in laboratory studies. This interactive platform empowers students to examine and analyze motor outputs by manipulating input parameters, facilitating a deeper understanding of PMSM operation and control.

Keywords: magnet synchronous motor, mathematical modelling, education tools, winding inter-turn fault

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Authors: Efe Çukur

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This study aims to discuss and compare i) widespread and generic design, particularly industrial design education in relation to the specific needs of the automotive/transportation industry, and ii) an automotive/transportation design education model within and under to provide the conditions of design education and automotive industry, especially in Turkey and T.R.N.C. The automotive industry is the 11th largest in the world ($1.51 trillion). One of the most important departments in this industry, along with sales, marketing and engineering, is the design department. The automotive industry is known as the locomotive industry, but there is a non-automotive design department on the academic side of Turkey. This suggestion; includes the presentation of a program proposal that meets the needs of the industry for Turkey and T.R.N.C., the second largest automobile manufacturing country in Europe. On the education side, industrial design education has become a generic title. Automotive design studios are divided into several subgroups. Even in the higher graduate education, the automotive design departments get their subgroups like exterior design and interior design. Transportation design, which is a subfield of industrial design, is offered as higher education in transportation design departments, particularly in America and Europe. In these departments, the curriculum is shaped to the needs of the sectors. Higher education transportation design programs began in the mid-20th century. Until those high education programs...Until these high education programs, the industry has adapted architectures and engineers for designer workloads. Still today transportation design graduates are not the majority of the design studios. The content of the study is an in-depth comparison of these institutions and how the requirements, demands of the industry are met in this regard and revealed. Some of the institutions are selected from Europe and US. To be analyzed under the headings of staff, courses, syllabus, University-Industry collaboration, and location selection. The study includes short, mid, and long term proposals and a hypothesis for discussion. In short, the study will not only provide a wide comparative scope of information on generic and specialized aspects of design education in different countries but also propose a higher education model for automotive / transportation design with solid data of requirements, methodology, and structure regarding learning outcomes, and especially industry cooperation.

Keywords: design education, automotive - transportation design programs, transportation design, automotive industry in Turkey /T.R.N.C., automotive design education in Turkey /T.R.N.C.

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Authors: Natalia Uribe Corrales, Santiago Henao Villegas

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Introduction: The management of pigs in the holding pens at the slaughterhouses is a key point to minimize levels of stress and fear, improve efficiency, maintain a good quality of meat and avoid economic losses. Holding pens should guarantee drinking water continuously, a minimum space of 1.2 m2/ animal; As well as an adequate management in the conduction of the animals towards stun. Objective: To characterize the management practices in holding pens in slaughterhouses in the Valle de Aburrá. Methods: A descriptive cross - sectional study was carried out in Valle de Aburrá benefit plants, which were authorized by National Institute for Food and Medicine Surveillance (INVIMA). Variables such as management mechanisms to the pens, time of housing, water supply, load density, vocalization, slips and falls of the animals in the pens and mechanism of conduction towards desensitization were analyzed. Results: 225 pigs were analyzed, finding that 35.6% were lowered with slaps from the trucks to the waiting pens; The lairage time was greater than 10 hours in 16% of the animals; 12.9% of pigs had no water permanently; 40.9% was subjected to a high load density, while 19.6% had a low load density. Regarding aspects of animal welfare, 37.3% presented high vocalizations; 29.3% and 14.2% presented slips or falls respectively. Regarding the mechanism of conduction towards desensitization, slapping was used in 56% and electrical prod in 4%. Conclusions: It is necessary to continue promoting the learning of the densities of load, since both high and low densities generate inconveniences in animal welfare, favoring the appearance of lesions and stress in the animals. Also, to promote the rule of permanent water in the pens and a time of housing less than 10 hours. In relation to the driving mechanisms, it is necessary to continue animal husbandry campaigns, encouraging the use of other alternatives such as boards or panels to assist the movement of pigs.

Keywords: animal welfare, quality of meat, swine, waiting pens

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Authors: Abdullah Alhaqbani

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Purpose: Implementing continuous improvement is a challenge that public sector organisations face in becoming successful. Many obstacles hinder public organisations from successfully implementing continuous improvement. This paper aims to highlight the key core obstacles that face public organisations to implement continuous improvement programmes. Approach: Based on the literature, this paper reviews 66 papers that were published between 2000 and 2013 and that focused on the concept of continuous improvement and improvement methodologies in the context of public sector organisations. The methodologies for continuous improvement covered in these papers include Total Quality Management, Six Sigma, process re-engineering, lean thinking and Kaizen. Findings: Of the 24 obstacles found in the literature, 11 barriers were seen as core barriers that frequently occurred in public sector organisations. The findings indicate that lack of top management commitment; organisational culture and political issues and resistance to change are significant obstacles for improvement programmes. Moreover, this review found that improvement methodologies share some core barriers to successful implementation within public organisations. These barriers as well are common in the different geographic area. For instance lack of top management commitment and training that found in the education sector in Albanian are common barriers of improvement studies in Kuwait, Saudi Arabia, Spain, UK and US. Practical implications: Understanding these core issues and barriers will help managers of public organisations to improve their strategies with respect to continuous improvement. Thus, this review highlights the core issues that prevent a successful continuous improvement journey within the public sector. Value: Identifying and understanding the common obstacles to successfully implementing continuous improvement in the public sector will help public organisations to learn how to improve in launching and successfully sustaining such programmes. However, this is not the end; rather, it is just the beginning of a longer improvement journey. Thus, it is intended that this review will identify key learning opportunities for public sector organisations in developing nations which will then be tested via further research.

Keywords: continuous improvement, total quality management, obstacles, public sector

Procedia PDF Downloads 351

Authors: Khatuna Buskivadze

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The aim of the present study is to investigate the sociolinguistic and classroom functions and frequency of Teacher’s Code Switching (CS) in the Content and Language Integrated (CLIL) Lesson. Nowadays, Georgian society struggles to become the part of the European world, the English language itself plays a role in forming new generations with European values. Based on our research conducted in 2019, out of all 114 private schools in Tbilisi, full- programs of CLIL are taught in 7 schools, while only some subjects using CLIL are conducted in 3 schools. The goal of the former research was to define the features of Content and Language Integrated learning (CLIL) methodology within the process of teaching English on the Example of Georgian private high schools. Taking the Georgian reality and cultural features into account, the modified version of the questionnaire, based on the classification of using CS in ESL Classroom proposed By Ferguson (2009) was used. The qualitative research revealed students’ and teacher’s attitudes towards teacher’s code-switching in CLIL lesson. Both qualitative and quantitative research were conducted: the observations of the teacher’s lessons (Recording of T’s online lessons), interview and the questionnaire among Math’s T’s 20 high school students. We came to the several conclusions, some of them are given here: Math’s teacher’s CS behavior mostly serves (1) the conversational function of interjection; (2) the classroom functions of introducing unfamiliar materials and topics, explaining difficult concepts, maintaining classroom discipline and the structure of the lesson; The teacher and 13 students have negative attitudes towards using only Georgian in teaching Math. The higher level of English is the more negative is attitude towards using Georgian in the classroom. Although all the students were Georgian, their competence in English is higher than in Georgian, therefore they consider English as an inseparable part of their identities. The overall results of the case study of teaching Math (Educational discourse) in one of the private schools in Tbilisi will be presented at the conference.

Keywords: attitudes, bilingualism, code-switching, CLIL, conversation analysis, interactional sociolinguistics.

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Authors: Dilek Dede

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This study aims at scrutinized the dilemma between education place and working place with professional socialization dimension over the beginning teachers in Turkey is to be found the solution for the dilemma in Turkey. The research question is that how can be explained the gap between education place and working place for beginning teachers in Turkey. That expected to contribute to literature with the solutions for shorting the gap between working area and education area of the teaching profession in Turkey case. The study is constructed in two section. Firstly, socialization of the teaching profession and teaching modules have been discussed through the profession, education, working place indicators. In the second section, Secondly, two educational specialists from Turkey has been interviewed about their observation on trainee teachers compelling to participate the class for candidate teachers after university grade. Then, the dilemma between education area and working area of the teaching profession has been detected by of semi-structured and in-depth interviews, the literature on the relationality of institutions and regulation is discussed. The following outcomes have been accessed in accordance with the data set and literature linkage axis: Firstly, teachers coming from the distinctive programmes as an educational background. Hence, teachers who pertain to distinctive cultures work in the same environment. That cause cultural conflicts and complication of socialization of profession. Secondly, the insufficient partnership between schools and universities besides, the education classes lead to a struggle of culture among these two institutions. Thirdly, the education classes are designed as bureaucratic form instead of coalescence between head teachers and trainee teachers around a common culture. That become deep the dilemma. In conclusion, on condition that applied-oriented education that advocates in-service learning is promoted and this programme is supported with well-structured the in-service training through the partnership of universities and schools, the gap between the working-area and education-area might be shortened.

Keywords: beginning teachers, construction of a common, social mobilization in the teaching profession, teacher training institution, the relationality of the regulations and institutions

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Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

Procedia PDF Downloads 224