Search results for: automated embedded assessment

Authors: Taleb Hosni Abderrahmane, Berga Abdelmadjid

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The development of numerical analysis and its application to geomechanics problems have provided geotechnical engineers with extremely powerful tools. One of the most important problems in geotechnical engineering is the slope stability assessment. It is a very difficult task due to several aspects such the nature of the problem, experimental consideration, monitoring, controlling, and assessment. The main objective of this paper is to perform a comparative numerical study between the following methods: The Limit Equilibrium (LEM), Finite Element (FEM), Limit Analysis (LAM) and Distinct Element (DEM). The comparison is conducted in terms of the safety factors and the critical slip surfaces. Through the results, we see the feasibility to analyse slope stability by many methods.

Keywords: comparison, factor of safety, geomechanics, numerical methods, slope analysis, slip surfaces

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Authors: Modupe C. Alasa

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One of the major parameters for ensuring a country’s economic growth and development is the extent to which the citizens are involved in agriculture. The general objective of this study is to determine the assessment of vocational rehabilitation of visually impaired persons in poultry farming at blind center, Ogbomoso, Nigeria. A total number of 70 students will be selected randomly through the use of structured questionnaire out of the total number of students which is 120. Data will be collected from the farmers’ personal characteristics and other specific objectives related to the work. The results will be analyzed with the use of simple statistical tools as frequency, percentage, means and standard deviations. Conclusion and recommendations will be suggested based on result findings of the study.

Keywords: assessment, impair, poultry, rehabilitation, vocational

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Authors: Ananya Sharma

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International Relations is a discipline of paradoxes. The State is the dominant political institution, with mainstream analysis theorizing the State, but theory remains at best a reactionary monolith. Critical Theorists have been pushing the envelope and to that extent, there has been a clear shift in the dominant discourse away from State-centrism to individuals and group-level behaviour. This paradigm shift has been accompanied with more nuanced conceptualizations of other variables at play–power, security, and trust, to name a few. Yet, the ambit of “what is discussed” remains primarily embedded in realist conceptualizations. With this background in mind, this paper will attempt to understand, juxtapose and evaluate how “order” has been conceptualized in International Relations theory. This paper is a tentative attempt to present a “state of the art” and in the process, set the stage for a deeper study to draw attention to what the author feels is a gaping lacuna in IR theory. The paper looks at how different branches of international relations theory envisage world order and the silences embedded therein. Further, by locating order and disorder inhabiting the same reality along a continuum, alternative readings of world orders are drawn from the critical theoretical traditions, in which various articulations of justice impart the key normative pillar to the world order.

Keywords: global justice, international relations theory, legitimacy, world order

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Authors: Celeste Lawson

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Learning to embrace and value teamwork assessment at a university level is critical for students, as graduates enter a real-world working environment where teamwork is likely to occur virtually. Student disdain for teamwork exercises is an area often overlooked or disregarded by academics. This research explored the implementation of an online teamwork assessment approach at a regional Australian university with a significant cohort of Distance Education students. Students had disliked teamwork for three reasons: it was not relevant to their study, the grading was unfair amongst team members, and managing the task was challenging in a virtual environment. Teamwork assessment was modified so that the task was an authentic task that could occur in real-world practice; team selection was based on the task topic rather than randomly; grading was based on the individual’s contribution to the task, and students were provided virtual team management skills as part of a the assessment. In this way, management of the team became an output of the task itself. Data was gathered over three years from student satisfaction surveys, failure rates, attrition figures, and unsolicited student comments. In one unit where this approach was adopted (Advanced Public Relations), student satisfaction increased from 3.6 (out of 5) in 2012 to 4.6 in 2016, with positive comments made about the teamwork approach. The attrition rate for another unit (Public Relations and the Media) reduced from 20.7% in 2012 to 2.2% in 2015. In 2012, criticism of teamwork assessment made up 50% of negative student feedback in Public Relations and the Media. By 2015, following the successful implementation of the teamwork assessment approach, only 12.5% of negative comments on the student satisfaction survey were critical of teamwork, while 33% of positive comments related to a positive teamwork experience. In 2016, students explicitly nominated teamwork as the best part of this unit. The approach is transferable to other disciplines and was adopted by other academics within the institution with similar results.

Keywords: assessment, distance education, teamwork, virtual

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Authors: Pavan Shah

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In an Embedded system, Virtualization and visualization technology can provide us an effective response and measurable work in a software development environment. In addition to work of virtualization and virtualization can be easily deserved to provide the best resource sharing between real-time hardware applications and a healthy environment. However, the virtualization is noticeable work to minimize the I/O work and utilize virtualization & virtualization technology for either a software development environment (SDE) or a runtime environment of real-time embedded systems (RTMES) or real-time operating system (RTOS) eras. In this Paper, we particularly focus on virtualization and visualization overheads data of network which generates the I/O and implementation of standardized I/O (i.e., Virto), which can work as front-end network driver in a real-time operating system (RTOS) hardware module. Even there have been several work studies are available based on the virtualization operating system environment, but for the Virto on a general-purpose OS, my implementation is on the open-source Virto for a real-time operating system (RTOS). In this paper, the measurement results show that implementation which can improve the bandwidth and latency of memory management of the real-time operating system environment (RTMES) for getting more accuracy of the trained model.

Keywords: virtualization, visualization, network driver, operating system

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Authors: Evangelos G. Ilias, Panagiotis G. Ilias, Vasileios T. Popotas

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The United Kingdom has one of the oldest railway networks in the world dating back to 1825 when the world’s first passenger railway was opened. The network has some 40,000 bridges of various construction types using a wide range of materials including masonry, steel, cast iron, wrought iron, concrete and timber. It is commonly accepted that the successful operation of the network is vital for the economy of the United Kingdom, consequently the cost effective maintenance of the existing infrastructure is a high priority to maintain the operability of the network, prevent deterioration and to extend the life of the assets. Every bridge on the railway network is required to be assessed every eighteen years and a structured approach to assessments is adopted with three main types of progressively more detailed assessments used. These assessment types include Level 0 (standardized spreadsheet assessment tools), Level 1 (analytical hand calculations) and Level 2 (generally finite element analyses). There is a degree of conservatism in the first two types of assessment dictated to some extent by the relevant standards which can lead to some structures not achieving the required load rating. In these situations, a Level 2 Assessment is often carried out using finite element analysis to uncover ‘latent strength’ and improve the load rating. If successful, the more sophisticated analysis can save on costly strengthening or replacement works and avoid disruption to the operational railway. This paper presents the ‘strengthening by assessment’ achieved by Level 2 analyses. The use of more accurate analysis assumptions and the implementation of non-linear modelling and functions (material, geometric and support) to better understand buckling modes and the structural behaviour of historic construction details that are not specifically covered by assessment codes are outlined. Metallic bridges which are susceptible to loss of section size through corrosion have largest scope for improvement by the Level 2 Assessment methodology. Three case studies are presented, demonstrating the effectiveness of the sophisticated Level 2 Assessment methodology using finite element analysis against the conservative approaches employed for Level 0 and Level 1 Assessments. One rail overbridge and two rail underbridges that did not achieve the required load rating by means of a Level 1 Assessment due to the inadequate restraint provided by U-Frame action are examined and the increase in assessed capacity given by the Level 2 Assessment is outlined.

Keywords: assessment, bridges, buckling, finite element analysis, non-linear modelling, strengthening

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Authors: Nukarova Marjona Kayimovna

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This article examines Uzbekistan's participation in the Programme for International Student Assessment (PISA) 2022, as the country took part in the assessment for the first time. The analysis delves into the initial results and performance metrics reported by the Organisation for Economic Co-operation and Development (OECD). By exploring Uzbekistan's data, the article highlights key findings, trends, and areas of strength and improvement. The aim is to provide a comprehensive understanding of how Uzbekistan's education system compares on the international stage and to offer insights into potential implications for future educational policies and reforms.

Keywords: PISA, OECD, data analysis of Uzbekistan, results, critical thinking.

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Authors: Murat Gunduz, Mustafa Ozdemir

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In this research, a framework is to be proposed to model the safety performance in construction sites. Determinants of safety performance are to be defined through extensive literature review and a multidimensional safety performance model is to be developed. In this context, a questionnaire is to be administered to construction companies with sites. The collected data through questionnaires including linguistic terms are then to be defuzzified to get concrete numbers by using fuzzy set theory which provides strong and significant instruments for the measurement of ambiguities and provides the opportunity to meaningfully represent concepts expressed in the natural language. The validity of the proposed safety performance model, relationships between determinants of safety performance are to be analyzed using the structural equation modeling (SEM) which is a highly strong multi variable analysis technique that makes possible the evaluation of latent structures. After validation of the model, a safety performance index assessment tool is to be proposed by the help of software. The proposed safety performance assessment tool will be based on the empirically validated theoretical model.

Keywords: Fuzzy set theory, safety performance assessment, safety index, structural equation modeling (SEM), construction sites

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Authors: George N. Zaimes, Valasia Iakovoglou, Paschalis Koutalakis, Konstantinos Ioannou, Ioannis Kosmadakis, Panagiotis Tsardaklis, Theodoros Laopoulos

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The advancements in technology allow the development of a new system that can continuously measure surface soil erosion. Continuous soil erosion measurements are required in order to comprehend the erosional processes and propose effective and efficient conservation measures to mitigate surface erosion. Mitigating soil erosion, especially in Mediterranean countries such as Greece, is essential in order to maintain environmental and agricultural sustainability. In this paper, we present the Automated Soil Erosion Monitoring System (ASEMS) that measures surface soil erosion along with other factors that impact erosional process. Specifically, this system measures ground level changes (surface soil erosion), rainfall, air temperature, soil temperature and soil moisture. Another important innovation is that the data will be collected by remote communication. In addition, stakeholder’s awareness is a key factor to help reduce any environmental problem. The different dissemination activities that were utilized are described. The overall outcomes were the development of an innovative system that can measure erosion very accurately. These data from the system help study the process of erosion and find the best possible methods to reduce erosion. The dissemination activities enhance the stakeholder's and public's awareness on surface soil erosion problems and will lead to the adoption of more effective soil erosion conservation practices in Greece.

Keywords: soil management, climate change, new technologies, conservation practices

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Authors: Abdal-Hafeez Alhussein

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Artificial Intelligence (AI) has become a transformative force in the field of information technologies, reshaping how data is processed, analyzed, and utilized across various domains. This paper explores the multifaceted applications of AI within information technology, focusing on three key areas: automation, scalability, and data-driven decision-making. We delve into how AI-powered automation is optimizing operational efficiency in IT infrastructures, from automated network management to self-healing systems that reduce downtime and enhance performance. Scalability, another critical aspect, is addressed through AI’s role in cloud computing and distributed systems, enabling the seamless handling of increasing data loads and user demands. Additionally, the paper highlights the use of AI in cybersecurity, where real-time threat detection and adaptive response mechanisms significantly improve resilience against sophisticated cyberattacks. In the realm of data analytics, AI models—especially machine learning and natural language processing—are driving innovation by enabling more precise predictions, automated insights extraction, and enhanced user experiences. The paper concludes with a discussion on the ethical implications of AI in information technologies, underscoring the importance of transparency, fairness, and responsible AI use. It also offers insights into future trends, emphasizing the potential of AI to further revolutionize the IT landscape by integrating with emerging technologies like quantum computing and IoT.

Keywords: artificial intelligence, information technology, automation, scalability

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Authors: K. Sindhu, V. Shubha Rao

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The goal of every faculty is to guide students to learn fundamental concepts and also improve thinking skills. Curriculum questionnaires must be framed, which would facilitate students to improve their thinking skills. Improving thinking skill is a difficult task and one of the ways to achieve this is to frame questionnaires using Bloom’s Taxonomy. Bloom’s Taxonomy helps the faculty to assess the students in a systematic approach which involves students performing successfully at each level in a systematic manner. In this paper, we have discussed on Revised Bloom’s Taxonomy and how to frame our questions based on the taxonomy for assessment. We have also presented mapping the questions with the taxonomy table which shows the mapping of the questions in knowledge and cognitive domain.

Keywords: bloom’s taxonomy, assessment, questions, engineering education

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Authors: Ian Walsh, Terry Nguyen-Khuong, Christopher H. Taron, Pauline M. Rudd

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Glycoproteins and their covalently bonded glycans play critical roles in the immune system, cell communication, disease and disease prognosis. Ultra performance liquid chromatography (UPLC) coupled with mass spectrometry is conventionally used to qualitatively and quantitatively characterise glycan structures in a given sample. Exoglycosidases are enzymes that catalyze sequential removal of monosaccharides from the non-reducing end of glycans. They naturally have specificity for a particular type of sugar, its stereochemistry (α or β anomer) and its position of attachment to an adjacent sugar on the glycan. Thus, monitoring the peak movements (both in the UPLC and MS1) after application of exoglycosidases provides a unique and effective way to annotate sugars with high detail - i.e. differentiating positional and linkage isomers. Manual annotation of an exoglycosidase experiment is difficult and time consuming. As such, with increasing sample complexity and the number of exoglycosidases, the analysis could result in manually interpreting hundreds of peak movements. Recently, we have implemented pattern recognition software for automated interpretation of UPLC-MS1 exoglycosidase digestions. In this work, we explain the software, indicate how much time it will save and provide example usage showing the annotation of positional and linkage isomers in Immunoglobulin G, apolipoprotein J, and simple glycan standards.

Keywords: bioinformatics, automated glycan assignment, liquid chromatography, mass spectrometry

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Authors: Nabil El Kadhi, Minerva M. Bunagan

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The dynamism in education, particularly in the area of teaching, learning and assessment has caused Higher Education Institutions (HEIs) worldwide to seek for ways to continuously improve their educational processes. HEIs use outcomes of institutional audits, assessments and accreditations, for improvement. In this study, the published institutional audit reports of HEIs in the Sultanate of Oman were analyzed to produce features of good practice; identify challenges along Teaching, Learning Assessment (TLA); and propose a framework that puts major emphasis in having a quality-assured TLA, including a set of principles that can be used as basis in succeeding an institutional visit. The TLA framework, which shows the TLA components, characteristics of the components, related expectation, including implementation tool/ strategy and pitfalls can be used by HEIs to have an adequate understanding of the scope of audit and be able to satisfy institutional audit requirements. The scope of this study can be widened by exploring the other requirements of the Institutional Audits in the Sultanate of Oman, particularly the area on Governance and Management and Student Support Services.

Keywords: accreditation, audit, teaching, learning and assessment, quality assurance

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Authors: Hanan M. Alghamdi, Kholud E. Alsalami, Manal I. Alshaikhi, Nouf M. Alsalami, Sara A. Awad, Ruqaya A. Alrabei

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Tourism in Saudi Arabia is one of the emerging sectors with rapid growth. The Kingdom of Saudi Arabia is characterized by its wonderful and historical areas, which constitute important cultural and tourist landmarks. These landmarks attract the attention of the government of Saudi Arabia; hence the improvement of the tourism sector becomes one of the important axes of Saudi Arabia's vision 2030. There is a need to enhance the tourist experience by facilitating the tourism process for visitors to the Kingdom of Saudi Arabia. This project aims to design an application to serve domestic tourists and visitors from outside the Kingdom of Saudi Arabia. This application will contain an automated tourist generate plan service by sentiment analysis of comments in Google Map using Lexicon for method Rule-based approach. There are thirteen regions in the kingdom of Saudi Arabia. The regions supported in this application will be Makkah and Asir regions. According to the output of the sentiment analysis, the application will recommend restaurants and cafes, activities (parks, museums) and shopping (shopping centers) in the generated plan. After that, the system will show the user a drop-down list of “Mega-events in Saudi Arabia” containing a link to the site of events in the Kingdom of Saudi Arabia. and “important information for you” public decency regulations.

Keywords: tourist automated plan, sentiment analysis, comments in google map, tourism in Saudi Arabia

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Wonkyung Na, Namhun Kim, Heeyeop Chae

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Quantum dots (QDs) are getting attentions due to their excellent optical properties in display, solar cell, biomolecule detection and lighting applications. Energy band gap can be easilty controlled by controlling their size and QDs are proper to apply in light-emitting-diode(LED) and lighting application, especially. Typically cadmium (Cd) containing QDs show a narrow photoluminescence (PL) spectrum and high quantum yield. However, Cd is classified as a hazardous materials and the use of Cd is being tightly regulated under 100ppm level in many countries.InP and CuInS2 (CIS) are being investigated as Cd-free QD materials and it is recently demonstrated that the performance of those Cd-free QDs is comparable to their Cd-based rivals.Due to a broad emission spectrum, CuInS2 QDs are also proper to be applied to white LED.4 For the lighting applications, the QD should be made in forms of color conversion films. Various film processes are reported with QDs in polymer matrixes. In this work, we synthesized the CuInS2 (CIS) QDs and QD embedded polystyrene color conversion films were fabricated for white color emission with electro-spinning process. As a result, blue light from blue LED is converted to white light with high color rendering index (CRI) of 72 by the color conversion films.

Keywords: CuInS2/ZnS, electro-spinning, color conversion films, white light emitting diodes

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Authors: Wakayama Shunya, Okubo Kazuya, Fujii Toru, Sakata Daisuke, Kado Noriyuki, Furutachi Hiroshi

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The purpose of this study is to propose an effective method to improve frictional coefficient of modified shoe rubber soles with added glass fibers onto the icy and snowy road surfaces in order to prevent slip-and-fall accidents by the users. Added fibers in the rubber were uniformly tilted to the perpendicular direction of the frictional surface, where tilting angle was -60, -30, +30, +60, 90 degrees and 0 for usual specimen, respectively. It was found that horizontal arraignment was effective to improve the frictional coefficient when glass fibers were embedded in the shoe rubber, while the standing in normal direction of the embedded glass fibers on the shoe surface was also effective to do that once after they were exposed from the shoe rubber with its abrasion. These improvements were explained by the increase of stiffness against the shear deformation of the rubber at the critical frictional state and the enlargement of resistance force for extracting exposed fibers from the ice and snow, respectively. Current study suggested that effective arraignments in the tilting angle of the added fibers should be applied in designing rubber shoe soles to keep the safeties for uses in regions of cold climates.

Keywords: frictional coefficient, shoe soles, icy and snowy road, glass fibers, tilting angle

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Authors: Ailvy Faith Zamora, Serj Donn David, Michael Anderson

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There are a number of decades-old piers and wharves in Manila, Philippines, that are currently being used for container and bulk cargo handling port operations. These structures fulfill a very important role in the economy and hence have undergone rehabilitation and assessment of capacity to accommodate current and future operational requirements. The capacity assessment would include structural and pile geotechnical evaluation. Unfortunately, old marine structures in the Philippines may not have a complete set of as-built information. In certain instances, critical information, such as pile toe levels, is missing in the documentation. A combination of direct tests, geophysical tests, and numerical analysis/modelling has been performed to estimate existing pile toe levels of open-type piers and anchored quay wall wharves in Manila. These techniques were applied to both concrete and steel piles. This paper presents the tools utilized, testing setup, and techniques used for estimating toe levels of existing piles for certain structures, including the challenges encountered and applied solutions.

Keywords: geophysical testing, pile toe level, structural assessment, piers, wharves

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Authors: Felipe Magalhaes Lemos

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Functional behavior analysis is a procedure that has been studied for several decades by behavior analysts. In Brazil, we still have few studies in the area, so it was decided to carry out a systematic review of the articles published in the area by Brazilians. A search was done on the following scientific article registration sites: PsycINFO, ERIC, ISI Web of Science, Virtual Health Library. The research includes (a) peer-reviewed studies that (b) have been carried out in Brazil containing (c) functional assessment as a pre-treatment through (d) experimental procedures, direct or indirect observation and measurement of behavior problems (e) demonstrating a relationship between environmental events and behavior. During the review, 234 papers were found; however, only 9 were included in the final analysis. Of the 9 articles extracted, only 2 presented functional analysis procedures with manipulation of environmental variables, while the other 7 presented different procedures for a descriptive behavior assessment. Only the two studies using "functional analysis" used graphs to demonstrate the prevalent function of the behavior. Other studies described procedures and did not make clear the causal relationship between environment and behavior. There is still confusion in Brazil regarding the terms "functional analysis", "descriptive assessment" and "contingency analysis," which are generally treated in the same way. This study shows that few articles are published with a focus on functional analysis in Brazil.

Keywords: behavior, contingency, descriptive assessment, functional analysis

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

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The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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Authors: Chan Kwong Tung

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Since Baddeley and Hitch’s seminal research in 1974 on working memory (WM), this topic has been of great interest to language educators. Although there are some variations in the definitions of WM, recent findings in WM have contributed vastly to our understanding of language learning, especially its effects on second language acquisition (SLA). For example, the phonological component of WM (PWM) and the executive component of WM (EWM) have been found to be positively correlated with language learning. This paper discusses two general, yet highly relevant WM findings that could directly affect the effectiveness of Chinese Language (CL) vocabulary teaching and learning, as well as the quality of its assessment. First, PWM is found to be critical for the long-term learning of phonological forms of new words. Second, EWM is heavily involved in interpreting the semantic characteristics of new words, which consequently affects the quality of learners’ reading comprehension. These two ideas are hardly discussed in the Chinese literature, both conceptual and empirical. While past vocabulary acquisition studies have mainly focused on the cognitive-processing approach, active processing, ‘elaborate processing’ (or lexical elaboration) and other effective learning tasks and strategies, it is high time to balance the spotlight to the WM (particularly PWM and EWM) to ensure an optimum control on the teaching and learning effectiveness of such approaches, as well as the validity of this language assessment. Given the unique phonological, orthographical and morphological properties of the CL, this discussion will shed some light on the vocabulary acquisition of this Sino-Tibetan language family member. Together, these two WM concepts could have crucial implications for the design, development, and planning of vocabularies and ultimately reading comprehension teaching and assessment in language education. Hopefully, this will raise an awareness and trigger a dialogue about the meaning of these findings for future language teaching, learning, and assessment.

Keywords: Chinese Language, working memory, vocabulary assessment, vocabulary teaching

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Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

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The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

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Authors: Radzuan Junin, Dayang Zulaika A. Hasbollah

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The increasing amount of greenhouse gasses in the atmosphere recently has become one of the discussed topics in relation with world’s concern on climate change. Developing countries’ emissions (such as Malaysia) are now seen to surpass developed country’s emissions due to rapid economic development growth in recent decades. This paper presents the potential storage sites suitability and storage capacity assessment for CO2 sequestration in sedimentary basins of Malaysia. This study is the first of its kind that made an identification of potential storage sites and assessment of CO2 storage capacity within the deep saline aquifers in the country. The CO2 storage capacity in saline formation assessment was conducted based on the method for quick assessment of CO2 storage capacity in closed, and semi-closed saline formations modified to suit the geology setting of Malaysia. Then, an integrated approach that involved geographic information systems (GIS) analysis and field data assessment was adopted to provide the potential storage sites and its capacity for CO2 sequestration. This study concentrated on the assessment of major sedimentary basins in Malaysia both onshore and offshore where potential geological formations which CO2 could be stored exist below 800 meters and where suitable sealing formations are present. Based on regional study and amount of data available, there are 14 sedimentary basins all around Malaysia that has been identified as potential CO2 storage. Meanwhile, from the screening and ranking exercises, it is obvious that Malay Basin, Central Luconia Province, West Baram Delta and Balingian Province are respectively ranked as the top four in the ranking system for CO2 storage. 27% of sedimentary basins in Malaysia were evaluated as high potential area for CO2 storage. This study should provide a basis for further work to reduce the uncertainty in these estimates and also provide support to policy makers on future planning of carbon capture and sequestration (CCS) projects in Malaysia.

Keywords: CO₂ storage, deep saline aquifer, GIS, sedimentary basin

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Authors: Guofan Shao, Lina Tang, Hao Zhang

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The values of image classification accuracy are affected by class size distributions and classification schemes, making it difficult to compare the performance of classification algorithms across different remote sensing data sources and classification systems. Based on the term efficacy from medicine and pharmacology, we have developed the metrics of image classification efficacy at the map and class levels. The novelty of this approach is that a baseline classification is involved in computing image classification efficacies so that the effects of class statistics are reduced. Furthermore, the image classification efficacies are interpretable and comparable, and thus, strengthen the assessment of image data classification methods. We use real-world and hypothetical examples to explain the use of image classification efficacies. The metrics of image classification efficacy meet the critical need to rectify the strategy for the assessment of image classification performance as image classification methods are becoming more diversified.

Keywords: accuracy assessment, efficacy, image classification, machine learning, uncertainty

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Authors: Robson C. Santos, Julio C. P. Ribeiro, Iorran M. de Castro, Luan C. F. Rodrigues, Sandro R. L. Silva, Diego M. Quesada

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The work aims to develop a robot in the form of autonomous vehicle to detect, inspection and mapping of underground pipelines through the ATmega328 Arduino platform. Hardware prototyping very similar to C / C ++ language that facilitates its use in robotics open source, resembles PLC used in large industrial processes. The robot will traverse the surface independently of direct human action, in order to automate the process of detecting buried pipes, guided by electromagnetic induction. The induction comes from coils that sends the signal to the Arduino microcontroller contained in that will make the difference in intensity and the treatment of the information, then this determines actions to electrical components such as relays and motors, allowing the prototype to move on the surface and getting the necessary information. The robot was developed by electrical and electronic assemblies that allowed test your application. The assembly is made up of metal detector coils, circuit boards and microprocessor, which interconnected circuits previously developed can determine, process control and mechanical actions for a robot (autonomous car) that will make the detection and mapping of buried pipelines plates.

Keywords: robotic, metal detector, embedded system, pipeline inspection

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Authors: Elena Even-Simkin

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Attention Deficit Hyperactivity Disorder (ADHD) is one of the most frequently diagnosed disorders in children, but in many cases, the diagnosis is not provided until adulthood. Diagnosing adults with ADHD faces different obstacles due to numerous factors, such as educational or under-resourced familial environment, high intelligence compensating for stress-inducing difficulties, and additional comorbidities. Undiagnosed children and adolescents with ADHD may become undiagnosed adults with ADHD, who miss out on the early treatment and may experience significant social and pragmatic difficulties, leading to functional problems that subsequently affect their lifestyle, education, and occupational functioning. The proposed study presents a cost-effective and unique consideration of the pragmatic aspect among adults with ADHD. It provides a systematic and standardized evaluation of the pragmatic level in adults with ADHD, based on a comprehensive approach introduced by Arcara & Bambini (2016) for the assessment of pragmatic abilities in neuro-typical individuals. This assessment tool can promote the inclusion of pragmatic skills in the cognitive profile in the diagnostic practice of ADHD, and, thus, the proposed instrument can help not only identify the pragmatic difficulties in the ADHD population but also advance effective intervention programs that specifically focus on pragmatic skills in the targeted population.

Keywords: ADHD, adults, assessment, pragmatics

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Authors: Susan Lewis

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The assessment of learning outcomes at the program level has attracted much international interest from the perspectives of quality assurance and ongoing curricular redesign and renewal. This paper examines program-level learning outcomes in the field of music and technology, an area of study that has seen an explosion in program development over the past fifteen years. The Audio Engineering Society (AES) maintains an online directory of educational institutions worldwide, yielding the most comprehensive inventory of programs and courses in music and technology. The inventory includes courses, programs, and degrees in music and technology, music and computer science, music production, and the music industry. This paper focuses on published student learning outcomes for undergraduate degrees in music and technology and analyses commonalities at institutions in North America, the United Kingdom, and Europe. The results of a survey of student learning outcomes at twenty institutions indicates a focus on three distinct student learning outcomes: (1) cross-disciplinary knowledge in the fields of music and technology; (2) the practical application of training through the professional industry; and (3) the acquisition of skills in communication and collaboration. The paper then analyses assessment mechanisms for tracking student learning and achievement of learning outcomes at these institutions. The results indicate highly variable assessment practices. Conclusions offer recommendations for enhancing assessment techniques and better communicating learning outcomes to students.

Keywords: quality assurance, student learning; learning outcomes, music and technology

Procedia PDF Downloads 186

Authors: Premrudee Promdet, Fan Cui, Gi Byoung Hwang, Ka Chuen To, Sanjayan Sathasivam, Claire J. Carmalt, Ivan P. Parkin

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A novel single-step fabrication of Cu nanoparticle embedded ZnO (Cu.ZnO) thin films was developed by aerosol-assisted chemical vapor deposition for stable and efficient hydrogen production in Photoelectrochemical (PEC) cell. In this approach, the Cu.ZnO nanoplate thin films were grown by using acetic acid to promote preferential growth and enhance surface active sites, where Cu nanoparticles can be formed under chemical deposition by reduction of Cu salt. Studies using photoluminescence spectroscopy indicate the enhanced photocatalytic performance is attributed to hot electron generated from SPR. The Cu metal in the composite material is functioning as a sensitizer to supply electrons to the semiconductor resulting in enhanced electron density for redox reaction. This work not only describes a way to obtain photoanodes with high photocatalytic activity but also suggests a low-cost route towards production of photocatalysts for hydrogen production. This work also supports a vital need to understand electron transfer between photoexcited semiconductor materials and metals, a requirement for tailoring the properties of semiconductor/metal composites.

Keywords: photocatalysis, photoelectrochemical cell (PEC), aerosol-assisted chemical vapor deposition (AACVD), surface plasmon resonance (SPR)

Procedia PDF Downloads 219

Authors: Simone F. Medeiros, Jessica M. Fonseca, Gizelda M. Alves, Danilo M. Santos, Sérgio P. Campana-Filho, Amilton M. Santos

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Stimuli responsive and biocompatible hydrogel nanoparticles have gained special attention as systems for potential applications in controlled release of drugs to improve their therapeutic efficacy while minimizing side effects. In this work, novel solid dispersions based on thermo- and pH-responsive poly(N-vinylcaprolactam-co-itaconic acid-co-ethylene- glycol dimethacrylate) hydrogel nanoparticles embedded in chitosan matrices were prepared via spray drying for controlled release of ketoprofen. Firstly, the hydrogel nanoparticles containing ketoprofen were prepared via precipitation polymerization and their stimuli-responsive behavior, thermal properties, chemical composition, encapsulation efficiency and morphology were characterized. Then, hydrogel nanoparticles with different particles size were embedded into chitosan matrices via spray-drying. Scanning electron microscopy (SEM) analyses were performed to investigate the particles size, dispersity and morphology. Finally, ketoprofen release profiles were studied as a function of pH and temperature. Chitosan/poly(NVCL-co-IA-co-EGDMA)-ketoprofen microparticles presented spherical shape, rough surface and pronounced agglomeration, indicating that hydrogels nanoparticles loaded with ketoprofen modified the surface of chitosan matrix. The maximum encapsulation efficiency of ketoprofen into hydrogel nanoparticles was 57.8% and the electrostatic interactions between amino groups from chitosan and carboxylic groups from hydrogel nanoparticles were able to control ketoprofen release. The hydrogel nanoparticles themselves were capable to retard the release of ketoprofen-loaded until 48h of in vitro release tests, while their incorporation into chitosan matrix achieved a maximum percentage of drug release of 45%, using a mass ratio of chitosan: poly(NVCL-co-IA-co-EGDMA equal to 10:7, and 69%, using a mass ratio of chitosan: poly(NVCL-co-IA-co-EGDMA equal to 5:2.

Keywords: hydrogel nanoparticles, poly(N-vinylcaprolactam-co-itaconic acid-co-ethylene- glycol dimethacrylate), chitosan, ketoprofen, spray-drying

Procedia PDF Downloads 267

Authors: Geraldine O’Neill

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Work-integrated learning is a valuable learning experience for students in higher education. However, the fairness of the assessment process has been identified as a challenge. This study explored solutions to this challenge through interviews with expert authors in the field and workshops across nine different disciplines in Ireland. In keeping with the use of a participatory and action research methodology, the key stakeholders in the process, the students, educators, and practitioners, identified some solutions. The solutions included the need to: clarify the assessments’ expectations; enhance the flexibility of the competencies, reduce the number of competencies; use grading scales with lower specificity; support practitioner training, and empower students in the assessment process. The results are discussed as they relate to interactional, procedural, and distributive fairness.

Keywords: competencies, fairness, grading scales, work-integrated learning

Procedia PDF Downloads 125