Search results for: manual data inquiry

Authors: A. U. Ugwu

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Post-Apartheid South African education system had witnessed waves of curriculum reforms. Accordingly, there have been evidences of responsiveness towards local and global challenges of sustainable development over the past decade. In other words, the curriculum shows sensitivity towards issues of Sustainable Development (SD). Moreover, the paradigm of Sustainable Development Goals (SDGs) was introduced by the UNESCO in year 2015. The SDGs paradigm is essentially a vision towards actualizing sustainability in all aspects of the global society. Education for Sustainable Development (ESD) in retrospect entails teaching and learning to actualize the intended UNESCO 2030 SDGs. This paper explores how teaching and learning of ESD can be improved, by drawing from local context of the South African schooling system. Preservice natural sciences and technology teachers in their 2nd to 4th years of study at a university’s college of education in South Africa were contacted as participants of the study. Using qualitative case study research design, the study drew from the views and experiences of five (5) purposively selected participants from a broader study, aiming to closely understating how ESD is implemented pedagogically in teaching and learning. The inquiry employed questionnaires and a focus group discussion as qualitative data generation tools. A qualitative data analysis of generated data was carried out using content and thematic analysis, underpinned by interpretive paradigm. The result of analyzed data, suggests that ESD pedagogy at the location where this research was conducted is largely influenced by contextual factors. Furthermore, the result of the study shows that there is a critical need to employ/adopt local experiences or occurrences while teaching sustainable development. Certain pedagogical approaches such as the use of videos relative to local context should also be considered in order to achieve a more realistic application. The paper recommends that educational institutions through teaching and learning should implement ESD by drawing on local contexts and problems, thereby foregrounding constructivism, appreciating and fostering students' prior knowledge and lived experiences.

Keywords: context, education for sustainable development, natural sciences and technology preservice teachers, qualitative research, sustainable development goals

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Authors: Dohun Kim

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Technological innovations have stimulated flipped learning in many disciplines, including language teaching. It is a specific type of blended learning, which combines onsite (i.e. face-to-face) with online experiences to produce effective, efficient and flexible learning. Flipped learning literally ‘flips’ conventional teaching and learning activities upside down: it leverages technologies to deliver a lecture and direct instruction—other asynchronous activities as well—outside the classroom to reserve onsite time for interaction and activities in the upper cognitive realms: applying, analysing, evaluating and creating. Unlike the conventional flipped approaches, which focused on video lecture, followed by face-to-face or on-site session, new innovative methods incorporate various means and structures to serve the needs of different academic disciplines and classrooms. In the light of such innovations, this study adopted ‘student-engaged’ approaches to interpreter training and contrasts them with traditional classrooms. To this end, students were also encouraged to engage in asynchronous activities online, and innovative technologies, such as Telepresence, were employed. Based on the class implementation, a thorough examination was conducted to examine how we can structure and implement flipped classrooms for language and interpreting training while actively engaging learners. This study adopted a quantitative research method, while complementing it with a qualitative one. The key findings suggest that the significance of the instructor’s role does not dwindle, but his/her role changes to a moderator and a facilitator. Second, we can apply flipped learning to both theory- and practice-oriented modules. Third, students’ integration into the community of inquiry is of significant importance to foster active and higher-order learning. Fourth, cognitive presence and competence can be enhanced through strengthened and integrated teaching and social presences. Well-orchestrated teaching presence stimulates students to find out the problems and voices the convergences and divergences, while fluid social presence facilitates the exchanges of knowledge and the adjustment of solutions, which eventually contributes to consolidating cognitive presence—a key ingredient that enables the application and testing of the solutions and reflection thereon.

Keywords: blended learning, Community of Inquiry, flipped learning, interpreter training, student-centred learning

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Authors: Rony Reátegui, Cesar Chácara, Benjamin Castañeda, Rafael Aguilar

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Nowadays, heritage building information modeling (HBIM) is considered an efficient tool to represent and manage information of cultural heritage (CH). The basis of this tool relies on a 3D model generally obtained from a cloud-to-BIM procedure. There are different methods to create an HBIM model that goes from manual modeling based on the point cloud to the automatic detection of shapes and the creation of objects. The selection of these methods depends on the desired level of development (LOD), level of information (LOI), grade of generation (GOG), as well as on the availability of commercial software. This paper presents the 3D modeling of a stone masonry chapel using Recap Pro, Revit, and Dynamo interface following a three-step methodology. The first step consists of the manual modeling of simple structural (e.g., regular walls, columns, floors, wall openings, etc.) and architectural (e.g., cornices, moldings, and other minor details) elements using the point cloud as reference. Then, Dynamo is used for generative modeling of complex structural elements such as vaults, infills, and domes. Finally, semantic information (e.g., materials, typology, state of conservation, etc.) and pathologies are added within the HBIM model as text parameters and generic models families, respectively. The application of this methodology allows the documentation of CH following a relatively simple to apply process that ensures adequate LOD, LOI, and GOG levels. In addition, the easy implementation of the method as well as the fact of using only one BIM software with its respective plugin for the scan-to-BIM modeling process means that this methodology can be adopted by a larger number of users with intermediate knowledge and limited resources since the BIM software used has a free student license.

Keywords: cloud-to-BIM, cultural heritage, generative modeling, HBIM, parametric modeling, Revit

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Authors: Theertha Chandroth

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This paper presents a comparative study on how to check JSON (JavaScript Object Notation) data against XML (eXtensible Markup Language) data from a software testing point of view. JSON and XML are widely used data interchange formats, each with its unique syntax and structure. The objective is to explore various techniques and methodologies for validating comparison and integration between JSON data to XML and vice versa. By understanding the process of checking JSON data against XML data, testers, developers and data practitioners can ensure accurate data representation, seamless data interchange, and effective data validation.

Keywords: XML, JSON, data comparison, integration testing, Python, SQL

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Authors: Bolin Hua

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In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

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Authors: Ali Mohammadi

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The present study is an attempt to investigate the influence of mythology on J.R.R. Tolkien's literary works in general and on Middle-Earth in particular. Moreover, despite the fact that mythology is usually regarded as a thing of the past predominantly found in the early works of literature, this inquiry reveals that how modern literary works can artistically benefit from mythological elements of Old English Era so as to enrich their content and stand out as innovative masterpieces. Indeed, having been a philologist and well-acquainted with mythological literature, Tolkien paved the way for a novel understanding of literature by bridging the gap between the old and the new. In the end, it was concluded that had mythology not been utilised by Tolkien, his works, and on top of all, Middle-Earth, would not have turned into a modern literary showpiece.

Keywords: literature, Middle-Earth, mythology, Tolkien

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Authors: Sajjad Baghernezhad, Saeideh Baghernezhad

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Nowadays considering human involved in increasing data development some methods such as data mining to extract science are unavoidable. One of the discussions of data mining is inherent distribution of the data usually the bases creating or receiving such data belong to corporate or non-corporate persons and do not give their information freely to others. Yet there is no guarantee to enable someone to mine special data without entering in the owner’s privacy. Sending data and then gathering them by each vertical or horizontal software depends on the type of their preserving type and also executed to improve data privacy. In this study it was attempted to compare comprehensively preserving data methods; also general methods such as random data, coding and strong and weak points of each one are examined.

Keywords: data mining, distributed data mining, privacy protection, privacy preserving

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Authors: C. Brierley, H. El-Farahaty, A. Farhan

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The Leeds Parallel Corpus of Arabic-English Constitutions is a parallel corpus for the Arabic legal domain. Analysis of legal language via Corpus Linguistics techniques is an important development. In legal proceedings, a corpus-based approach to disambiguating meaning is set to replace the dictionary as an interpretative tool, and legal scholarship in the States is now attuned to the potential for Text Analytics over vast quantities of text-based legal material, following the business and medical industries. This trend is reflected in Europe: the interdisciplinary research group in Computer Assisted Legal Linguistics mines big data collections of legal and non-legal texts to analyse: legal interpretations; legal discourse; the comprehensibility of legal texts; conflict resolution; and linguistic human rights. This paper focuses on ‘dignity’ as an important aspect of the overarching concept of human rights in current constitutions across the Arab world. We have compiled a parallel, Arabic-English raw text corpus (169,861 Arabic words and 205,893 English words) from reputable websites such as the World Intellectual Property Organisation and CONSTITUTE, and uploaded and queried our corpus in Sketch Engine. Our most challenging task was sentence-level alignment of Arabic-English data. This entailed manual intervention to ensure correspondence on a one-to-many basis since Arabic sentences differ from English in length and punctuation. We have searched for morphological variants of ‘dignity’ (رامة ك, karāma) in the Arabic data and inspected their English translation equivalents. The term occurs most frequently in the Sudanese constitution (10 instances), and not at all in the constitution of Palestine. Its most frequent collocate, determined via the logDice statistic in Sketch Engine, is ‘human’ as in ‘human dignity’.

Keywords: Arabic constitution, corpus-based legal linguistics, human rights, parallel Arabic-English legal corpora

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Authors: Pruthvi Nath Palleti, Sarmada Madhulika Kone

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Communities are formed based on the commonalities that exist in a set of individuals and when the group comes together on identifying those commonalities and to achieve their common goals. Thus, community planning with its vision to strengthen the community mostly involves with making or remaking of commons, which results in making or remaking of communities. This paper looks into different practices of planning around the world and tried to establish a link between commoning (the act of exercising the rights over commons by commoners) and participatory approach to community planning.

Keywords: commoners, commoning, community, participatory planning, urban local bodies

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Authors: Shuo Mu, Guangzhi Jiang, Jinsa Chen

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The analysis of Indel for RNA sequencing of clinical samples is easily affected by sequencing experiment errors and software selection. In order to improve the efficiency and accuracy of analysis, we developed an automatic reporting system for Indel recognition and annotation based on image snapshot of transcriptome reads alignment. This system includes sequence local-assembly and realignment, target point snapshot, and image-based recognition processes. We integrated high-confidence Indel dataset from several known databases as a training set to improve the accuracy of image processing and added a bioinformatical processing module to annotate and filter Indel artifacts. Subsequently, the system will automatically generate data, including data quality levels and images results report. Sanger sequencing verification of the reference Indel mutation of cell line NA12878 showed that the process can achieve 83% sensitivity and 96% specificity. Analysis of the collected clinical samples showed that the interpretation accuracy of the process was equivalent to that of manual inspection, and the processing efficiency showed a significant improvement. This work shows the feasibility of accurate Indel analysis of clinical next-generation sequencing (NGS) transcriptome. This result may be useful for RNA study for clinical samples with microsatellite instability in immunotherapy in the future.

Keywords: automatic reporting, indel, next-generation sequencing, NGS, transcriptome

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Authors: Roman Bieda

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The General Data Protection Regulation (GDPR) will come into force on 25 May 2018 which will create a new legal framework for the protection of personal data in the European Union. Article 20 of GDPR introduces a right to data portability. This right allows for data subjects to receive the personal data which they have provided to a data controller, in a structured, commonly used and machine-readable format, and to transmit this data to another data controller. The right to data portability, by facilitating transferring personal data between IT environments (e.g.: applications), will also facilitate changing the provider of services (e.g. changing a bank or a cloud computing service provider). Therefore, it will contribute to the development of competition and the digital market. The aim of this paper is to discuss the right to data portability and its influence on the development of new digital services.

Keywords: data portability, digital market, GDPR, personal data

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Authors: Zzibu Mark Brian

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As software systems become increasingly complex, ensuring code security is a growing concern. Traditional vulnerability detection methods often rely on manual code reviews or static analysis tools, which can be time-consuming and prone to errors. This paper presents a distinct approach to enhancing code security by leveraging artificial intelligence (AI) and machine learning (ML) techniques. Our proposed system utilizes a combination of natural language processing (NLP) and deep learning algorithms to identify and classify vulnerabilities in real-world codebases. By analyzing vast amounts of open-source code data, our AI-powered tool learns to recognize patterns and anomalies indicative of security weaknesses. We evaluated our system on a dataset of over 10,000 open-source projects, achieving an accuracy rate of 92% in detecting known vulnerabilities. Furthermore, our tool identified previously unknown vulnerabilities in popular libraries and frameworks, demonstrating its potential for improving software security.

Keywords: AI, machine language, cord security, machine leaning

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation

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Authors: George Kassar, Phillip A. Cartwright

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Based on data collected from The Jones Learning Center (JLC), University of the Ozarks, Arkansas, U.S., this study explores the impact of inclusive classroom practices on neuro-diverse college students’ and their consequent academic performance having participated in integrative therapies designed to support students who are intellectually capable of obtaining a college degree, but who require support for learning challenges owing to disabilities, AD/HD, or ASD. The purpose of this study is two-fold. The first objective is to explore the general process, special techniques, and practices of the (JLC) inclusive program. The second objective is to identify and analyze the effectiveness of the processes, techniques, and practices in supporting the academic performance of enrolled college students with learning disabilities following integration into mainstream university learning. Integrity, transparency, and confidentiality are vital in the research. All questions were shared in advance and confirmed by the concerned management at the JLC. While administering the questionnaire as well as conducted the interviews, the purpose of the study, its scope, aims, and objectives were clearly explained to all participants prior starting the questionnaire / interview. Confidentiality of all participants assured and guaranteed by using encrypted identification of individuals, thus limiting access to data to only the researcher, and storing data in a secure location. Respondents were also informed that their participation in this research is voluntary, and they may withdraw from it at any time prior to submission if they wish. Ethical consent was obtained from the participants before proceeding with videorecording of the interviews. This research uses a mixed methods approach. The research design involves collecting, analyzing, and “mixing” quantitative and qualitative methods and data to enable a research inquiry. The research process is organized based on a five-pillar approach. The first three pillars are focused on testing the first hypothesis (H1) directed toward determining the extent to the academic performance of JLC students did improve after involvement with comprehensive JLC special program. The other two pillars relate to the second hypothesis (H2), which is directed toward determining the extent to which collective and applied knowledge at JLC is distinctive from typical practices in the field. The data collected for research were obtained from three sources: 1) a set of secondary data in the form of Grade Point Average (GPA) received from the registrar, 2) a set of primary data collected throughout structured questionnaire administered to students and alumni at JLC, and 3) another set of primary data collected throughout interviews conducted with staff and educators at JLC. The significance of this study is two folds. First, it validates the effectiveness of the special program at JLC for college-level students who learn differently. Second, it identifies the distinctiveness of the mix of techniques, methods, and practices, including the special individualized and personalized one-on-one approach at JLC.

Keywords: education, neuro-diverse students, program effectiveness, Jones learning center

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Authors: Ana Lucia Molina

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Introduction: Fine motor skills refer to the use of the hands and coordination of the small muscles that control the fingers. A deficiency in fine motor skills is as important as a change in global movements, as fine motor skills directly affect activities of daily living. Fine movements are involved in some functions, such as motor control of the extremities, sensitivity, strength and tonus of the hands. A growing interest in the effects of non-invasive neuromodulation, such as transcranial stimulation technologies, through transcranial magnetic stimulation (TMS), has been observed in the scientific literature, with promising results in fine motor rehabilitation, as it provides modulation of the corresponding cortical activity in the area primary motor skills of the hands in both hemispheres (according to the International System 10-20, corresponding to C3 and C4). Objectives: to carry out a literature review about the effects of TMS on the cortical motor area corresponding to hand motricity. Methodology: This is a bibliographic survey carried out between October 2022 and March 2023 at Pubmed, Google Scholar, Lillacs and Virtual Health Library (BVS), with a national and international database. Some books on neuromodulation were included. Results: 28 articles and 5 books were initially found, and after reading the abstracts, only 14 articles and 3 books were selected, with publication dates between 2008 and 2022, to compose the literature review since it suited the purpose of this study. Conclusion: TMS has shown promising results in the treatment of fine motor rehabilitation, such as improving coordination, muscle strength and range of motion of the hands, being a complementary technique to existing treatments and thus providing more potent results for manual skills in activities of daily living. It is important to emphasize the need for more specific studies on the application of TMS for the treatment of manual disorders, which describe the uniqueness of each movement.

Keywords: transcranial magnetic stimulation, fine motor skills, motor rehabilitation, non-invasive neuromodulation

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Authors: Rosa Tiziana Bruno

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The connection between education and sustainability has been posited to have benefit for realizing a social development compatible with environmental protection. However, an educational paradigm based on the passage of information or on the fear of a catastrophe might not favor the acquisition of eco-identity. To build a sustainable world, it is necessary to "become people" in harmony with other human beings, being aware of belonging to the same human community that is part of the natural world. This can only be achieved within an authentic educating community and the most effective tools for building educating communities are reading literacy and storytelling. This paper is the report of a research-action carried out in this direction, in agreement with the sociology department of the University of Salerno, which involved four hundred children and their teachers in a path based on the combination of reading literacy, storytelling, autobiographical writing and outdoor education. The goal of the research was to create an authentic educational community within the school, capable to encourage the acquisition of an eco-identity by the pupils, that is, personal and relational growth in the full realization of the Self, in harmony with the social and natural environment, with a view to an authentic education for sustainability. To ensure reasonable validity and reliability of findings, the inquiry started with participant observation and a process of triangulation has been used including: semi-structured interview, socio-semiotic analysis of the conversation and time budget. Basically, a multiple independent sources of data was used to answer the questions. Observing the phenomenon through multiple "windows" helped to comparing data through a variety of lenses. All teachers had the experience of implementing a socio-didactic strategy called "Fiabadiario" and they had the possibility to use it with approaches that fit their students. The data being collected come from the very students and teachers who are engaged with this strategy. The educational path tested during the research has produced sustainable relationships and conflict resolution within the school system and between school and families, creating an authentic and sustainable learning community.

Keywords: educating community, education for sustainability, literature in education, social relations

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Authors: Alan Collins

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This study explains how The People’s Tribunal empowered survivors of child abuse. It examines how People’s tribunals can be effective mean of empowerment; the challenges of empowerment – expectation v. reality; the findings and how they reflect other inquiry findings; and the importance of listening and learning from survivors. UKCSAPT “The People’s Tribunal” was established by survivors of child sex abuse and members of civil society to investigate historic cases of institutional sex abuse. The independent inquiry, led by a panel of four judges, listened to evidence spanning four decades from survivors and experts. A common theme throughout these accounts showed that a series of institutional failures prevented abuse from being reported; and that there are clear links between children being rendered vulnerable by these failures and predatory abuse on an organised scale. It made a series of recommendations including the establishment of a permanent and open forum for victims to share experiences and give evidence, better links between mental health services and police investigations, and training for police and judiciary professionals on the effects of undisclosed sexual abuse. The main findings of the UKCSAPT report were:-There are clear links between children rendered vulnerable by institutional failures and predatory abuse on an organised scale, even if these links often remain obscure. -UK governmental institutions have failed to provide survivors with meaningful opportunities for either healing or justice. -The vital mental health needs of survivors are not being met and this undermines both their psychological recovery and access to justice. -Police and other authorities often lack the training to understand the complex reasons for the inability of survivors to immediately disclose a history of abuse. -Without far-reaching changes in institutional culture and practices, the sexual abuse of children will continue to be a significant scourge in the UK. The report also outlined a series of recommendations for improving reporting and mental health provision, and access to justice for victims were made, including: -A permanent, government-funded popular tribunal should be established to enable survivors to come forward and tell their stories. -Survivors giving evidence should be assigned an advocate to assist their access to justice. -Mental health services should be linked to police investigations to help victims disclose abuse. -Victims who fear reprisals should be provided with a channel though which to give evidence anonymously.

Keywords: empowerment, survivors, sexual, abuse

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Authors: Abdelaadim Bidaoui

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As one of the most important linguistic inquiries, the topic of the intertwined relationship between language, the mind, and the world has attracted many scholars. In the fifties, Sapir and Whorf advocated the hypothesis that language shapes our cultural realities as an early attempt to provide answers to this linguistic inquiry. Later, discursive psychology views the linguistic behavior as “a dynamic form of social practice which constructs the social world, individual selves and identity.” (Jorgensen & Phillips 2002, 118). Discursive psychology also considers discourse as a trigger of social action and change. Building on discursive psychology and motivation theory, this paper examines the impact of linguistic behavior of the Moroccan coach Walid Reggragui on the Moroccan team’s exceptional performance in Qatar 2022 Soccer World Cup. The data used in the research is based on interviews conducted by the Moroccan coach prior and during the World Cup. Using a discourse analysis of the linguistic behavior of Reggragui, this paper shows how the linguistic behavior of Reggragui provided support for the three psychological needs: sense of belonging, competence, and autonomy. As any CDA research, this paper uses a triangulated theoretical framework that includes language, cognition and society.

Keywords: critical discourse analysis, motivation theory, discursive psychology, linguistic behavior

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Authors: Fahad Hanash Alzahrani

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This paper describes some recent advances in a quickly developing area of data storing and processing based on Data Warehouses and Data Mining techniques, which are associated with software, hardware, data mining algorithms and visualisation techniques having common features for any specific problems and tasks of their implementation.

Keywords: data warehouse, data mining, knowledge discovery in databases, on-line analytical processing

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Authors: Zheng Miao, Dennis Fernandez

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CRISPR research has the potential to completely transform life science, agriculture, live-stock and the health care industry. The Intellectual Property derived from its research has raised significant attention in the academic as well as the biopharmaceutical industry culminating an urgent need for strategic IP protection. We review the rudimentary concepts and key competitors of CRISPR technologies as well as the paramount strategies for intellectual property protection. Further, we elaborate on prosecution issues related to CRISPR patents as well as possible solutions to various patent laws, interferences and litigation. Finally, we address how the bioinformatics of the CRISPR technology begs an inquiry into issues of privacy and a host of ethical concerns.

Keywords: bioinformatics, CRISPR, biotechnology, intellectual property

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Authors: Fadil Elmenfi

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Edward Said, in his book Culture and Imperialism, devotes the introduction to the Arabic translation. He claims that the fading echo of Orientalism in the Arab world is unlike the positive reflections of its counterpart elsewhere in the world. The probable reason behind his inquiry would be that the methodology Abu Deeb applied in translating Said's book contributed to the book having the limited impact which Said is referring to. The paper adds new insights to the body of theory and the effectiveness of the performance of translation from culture to culture. It presents a survey that can provide the reader with an overview of Said's Orientalism and the two Arabic translations of the book. It investigates some of the problems of translating cultural texts, more specifically translating features of Said's style.

Keywords: Orientalism, retranslation, Arabic Language, Muhammad Enani, Kamal Abu Deeb, Edward Said

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Authors: Mehmet Akif Aslan, Mehmet Simsek, Eyup Sensoy

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Big Data stands for today’s cutting-edge technology. As the technology becomes widespread, so does Data. Utilizing massive data sets enable companies to get competitive advantages over their adversaries. Out of many area of Big Data usage, logistics has significance role in both commercial sector and military. This paper lays out what big data is and how it is used in both military and commercial logistics.

Keywords: big data, logistics, operational efficiency, risk management

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Authors: Nicky Wilson, Graeme Ralph

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Legacy aerostructure assembly is defined by large components, low build rates, and manual assembly methods. With an increasing demand for commercial aircraft and emerging markets such as the eVTOL (electric vertical take-off and landing) market, current methods of manufacturing are not capable of efficiently hitting these higher-rate demands. This project will look at how legacy manufacturing processes can be rate enabled by taking a holistic view of data usage, focusing on how data can be collected to enable fully integrated digital factories and supply chains. The study will focus on how data is flowed both up and down the supply chain to create a digital thread specific to each part and assembly while enabling machine learning through real-time, closed-loop feedback systems. The study will also develop a bespoke architecture to enable connectivity both within the factory and the wider PLM (product lifecycle management) system, moving away from traditional point-to-point systems used to connect IO devices to a hub and spoke architecture that will exploit report-by-exception principles. This paper outlines the key issues facing legacy aircraft manufacturers, focusing on what future manufacturing will look like from adopting Industry 4 principles. The research also defines the data architecture of a PLM system to enable the transfer and control of a digital thread within the supply chain and proposes a standardised communications protocol to enable a scalable solution to connect IO devices within a production environment. This research comes at a critical time for aerospace manufacturers, who are seeing a shift towards the integration of digital technologies within legacy production environments, while also seeing build rates continue to grow. It is vital that manufacturing processes become more efficient in order to meet these demands while also securing future work for many manufacturers.

Keywords: Industry 4, digital transformation, IoT, PLM, automated assembly, connected factories

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Authors: Priya Arora, Ashutosh Mishra

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Gene identification, towards the pursuit of mutated genes, leading to Parkinson’s disease, puts forward a challenge towards proactive cure of the disorder itself. Computational analysis is an effective technique for exploring genes in the form of protein sequences, as the theoretical and manual analysis is infeasible. The limitations and effectiveness of a particular computational method are entirely dependent on the previous data that is available for disease identification. The article presents a sequence-based classification method for the identification of genes responsible for Parkinson’s disease. During the initiation phase, the physicochemical properties of amino acids transform protein sequences into a feature vector. The second phase of the method employs Jaccard distances to select negative genes from the candidate population. The third phase involves artificial neural networks for making final predictions. The proposed approach is compared with the state of art methods on the basis of F-measure. The results confirm and estimate the efficiency of the method.

Keywords: disease gene identification, Parkinson’s disease, physicochemical properties of amino acid, protein sequences

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Authors: Mark Joseph Quinto, Roan Beronilla, Guiller Damian, Eliza Camaso, Ronaldo Alberto

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Forest inventories are essential to assess the composition, structure and distribution of forest vegetation that can be used as baseline information for management decisions. Classical forest inventory is labor intensive and time-consuming and sometimes even dangerous. The use of Light Detection and Ranging (LiDAR) in forest inventory would improve and overcome these restrictions. This study was conducted to determine the possibility of using LiDAR derived data in extracting high accuracy forest biophysical parameters and as a non-destructive method for forest status analysis of San Manual, Pangasinan. Forest resources extraction was carried out using LAS tools, GIS, Envi and .bat scripts with the available LiDAR data. The process includes the generation of derivatives such as Digital Terrain Model (DTM), Canopy Height Model (CHM) and Canopy Cover Model (CCM) in .bat scripts followed by the generation of 17 composite bands to be used in the extraction of forest classification covers using ENVI 4.8 and GIS software. The Diameter in Breast Height (DBH), Above Ground Biomass (AGB) and Carbon Stock (CS) were estimated for each classified forest cover and Tree Count Extraction was carried out using GIS. Subsequently, field validation was conducted for accuracy assessment. Results showed that the forest of San Manuel has 73% Forest Cover, which is relatively much higher as compared to the 10% canopy cover requirement. On the extracted canopy height, 80% of the tree’s height ranges from 12 m to 17 m. CS of the three forest covers based on the AGB were: 20819.59 kg/20x20 m for closed broadleaf, 8609.82 kg/20x20 m for broadleaf plantation and 15545.57 kg/20x20m for open broadleaf. Average tree counts for the tree forest plantation was 413 trees/ha. As such, the forest of San Manuel has high percent forest cover and high CS.

Keywords: carbon stock, forest inventory, LiDAR, tree count

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Authors: P. Thachitasing, N. Jansawang, W. Rakrai, T. Santiboon

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The aim of this study is to investigate of the comparing the instructional design models between the Think-Pair-Share and Conventional Learning (5E Inquiry Model) Processes to enhance students’ learning achievements and their problem solving skills on stoichiometry issue for concerning the 2-instructional method with a sample consisted of 80 students in 2 classes at the 11th grade level in Chaturaphak Phiman Ratchadaphisek School. Students’ different learning outcomes in chemistry classes with the cluster random sampling technique were used. Instructional Methods designed with the 40-experimenl student group by Think-Pair-Share process and the 40-controlling student group by the conventional learning (5E Inquiry Model) method. These learning different groups were obtained using the 5 instruments; the 5-lesson instructional plans of Think-Pair-Share and STEM Education Method, students’ learning achievements and their problem solving skills were assessed with the pretest and posttest techniques, students’ outcomes of their instructional the Think-Pair-Share (TPSM) and the STEM Education Methods were compared. Statistically significant was differences with the paired t-test and F-test between posttest and pretest technique of the whole students in chemistry classes were found, significantly. Associations between student learning outcomes in chemistry and two methods of their learning to students’ learning achievements and their problem solving skills also were found. The use of two methods for this study is revealed that the students perceive their learning achievements to their problem solving skills to be differently learning achievements in different groups are guiding practical improvements in chemistry classrooms to assist teacher in implementing effective approaches for improving instructional methods. Students’ learning achievements of mean average scores to their controlling group with the Think-Pair-Share Model (TPSM) are lower than experimental student group for the STEM education method, evidence significantly. The E1/E2 process were revealed evidence of 82.56/80.44, and 83.02/81.65 which results based on criteria are higher than of 80/80 standard level with the IOC, consequently. The predictive efficiency (R2) values indicate that 61% and 67% and indicate that 63% and 67% of the variances in chemistry classes to their learning achievements on posttest in chemistry classes of the variances in students’ problem solving skills to their learning achievements to their chemistry classrooms on Stoichiometry issue with the posttest were attributable to their different learning outcomes for the TPSM and STEMe instructional methods.

Keywords: comparisons, students’ learning achievements, think-pare-share model (TPSM), stem education, problem solving skills, chemistry classes, stoichiometry issue

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Authors: Suppara Charoenpoom

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This study focuses on 1) a good-quality management procedures of buildings and environment in schools 2) designing the management procedures and 3) creating an operation manual for the procedures. This study is the combination of qualitative and quantitative research method. Populations in the research were 83 deans and directors of primary and secondary schools from the 10th educational district in Samut Songkram. Sample group was selected from the voluntary deans and directors. There were 14 participants in sample group. Research tools in this study were divided into 2 categories. The first one was data-collecting tools, which were in-depth interview and questionnaires. The second one was the designing tools to help creating management procedures: quality business, quality work procedure and key quality indicator of each activity in schools. All data were analyzed by mean and standard deviation. The result from this study has found out 1 effective process of building and environment management for basic education schools which is called Quality Business Process (QBP) and 7 Quality Work Procedures (QWP). In terms of academic feasibility checkup by experts, the research had shown that new design of building and environment management was approved unanimously. It means that new process of building and environment management in schools works very well and can be adapted. After examining the possibility of management process being used in schools by calculating the mean value among sample group (14 school deans and directors), the mean value was between 0.64-1.00. It means that the new design of building and environment management can be operated effectively in schools. For the satisfaction part, deans and school directors gave the satisfaction score in the highest level (Mean = 4.7372, S.D. = 0.4385).

Keywords: buildings, environment, procedures, quality management

Procedia PDF Downloads 228

Authors: Khlood F. Salman, Richard Zoucha, Hani Nawafleh

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Introduction: Jordan ranks the fourth highest breast cancer prevalence after Lebanon, Bahrain, and Kuwait. Considerable evidence showed that cultural, ethnic, and economic differences influence a woman’s practice to early detection and prevention of breast cancer. Objectives: To understand women’s health beliefs and values in relation to early detection of breast cancer; and to explore the impact of these beliefs on their decisions regarding reluctance or acceptance of early detection measures such as mammogram screening. Design: A qualitative focused ethnography was used to collect data for this study. Settings: The study was conducted in the second largest city surrounded by a large rural area in Ma’an- Jordan. Participants: A total of twenty seven women, with no history of breast cancer, between the ages of 18 and older, who had prior health experience with health providers, and were willing to share elements of personal health beliefs related to breast health within the larger cultural context. The participants were recruited using the snowball method and words of mouth. Data collection and analysis: A short questionnaire was designed to collect data related to socio demographic status (SDQ) from all participants. A Semi-structured interviews guide was used to elicit data through interviews with the informants. Nvivo10 a data manager was utilized to assist with data analysis. Leininger’s four phases of qualitative data analysis was used as a guide for the data analysis. The phases used to analyze the data included: 1) Collecting and documenting raw data, 2) Identifying of descriptors and categories according to the domains of inquiry and research questions. Emic and etic data is coded for similarities and differences, 3) Identifying patterns and contextual analysis, discover saturation of ideas and recurrent patterns, and 4) Identifying themes and theoretical formulations and recommendations. Findings: Three major themes were emerged within the cultural and religious context; 1. Fear, denial, embarrassment and lack of knowledge were common perceptions of Ma’anis’ women regarding breast health and screening mammography, 2. Health care professionals in Jordan were not quick to offer information and education about breast cancer and screening, and 3. Willingness to learn about breast health and cancer prevention. Conclusion: The study indicated the disparities between the infrastructure and resourcing in rural and urban areas of Jordan, knowledge deficit related to breast cancer, and lack of education about breast health may impact women’s decision to go for a mammogram screening. Cultural beliefs, fear, embarrassments as well as providers lack of focus on breast health were significant contributors against practicing breast health. Health providers and policy makers should provide resources for the establishment health education programs regarding breast cancer early detection and mammography screening. Nurses should play a major role in delivering health education about breast health in general and breast cancer in particular. A culturally appropriate health awareness messages can be used in creating educational programs which can be employed at the national levels.

Keywords: breast health, beliefs, cultural context, ethnography, mammogram screening

Procedia PDF Downloads 283

Authors: Axelle Bertrand, Tom Bauer, Carole Charbuillet, Martin Bonte, Marie Voyer, Nicolas Perry

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The complexity of Life Cycle Assessment (LCA) can be identified as the ultimate obstacle to massification. Due to these obstacles, the diffusion of eco-design and LCA methods in the manufacturing sectors could be impossible. This article addresses the research question: How to adapt the LCA method to generalize it massively and improve its performance? This paper aims to develop an approach for automating LCA in order to carry out assessments on a massive scale. To answer this, we proceeded in three steps: First, an analysis of the literature to identify existing automation methods. Given the constraints of large-scale manual processing, it was necessary to define a new approach, drawing inspiration from certain methods and combining them with new ideas and improvements. In a second part, our development of automated construction is presented (reconciliation and implementation of data). Finally, the LCA case study of a conduit is presented to demonstrate the feature-based approach offered by the developed tool. A computerized environment supports effective and efficient decision-making related to materials and processes, facilitating the process of data mapping and hence product modeling. This method is also able to complete the LCA process on its own within minutes. Thus, the calculations and the LCA report are automatically generated. The tool developed has shown that automation by code is a viable solution to meet LCA's massification objectives. It has major advantages over the traditional LCA method and overcomes the complexity of LCA. Indeed, the case study demonstrated the time savings associated with this methodology and, therefore, the opportunity to increase the number of LCA reports generated and, therefore, to meet regulatory requirements. Moreover, this approach also presents the potential of the proposed method for a wide range of applications.

Keywords: automation, EEE, life cycle assessment, life cycle inventory, massively

Procedia PDF Downloads 78

Authors: Shrabani Ghosh

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Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

Procedia PDF Downloads 100