Search results for: conventional learning method

Authors: Sadegh Abedi, Ali Yaghoubi, Hamidreza Mashatzadegan

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This paper proposes an approach to identify key processes required by an organization in the field of knowledge management and aligning them with organizational objectives. For this purpose, first, organization’s most important non-financial objectives which are impacted by knowledge management processes are identified and then, using a quality house, are linked with knowledge management processes which are regarded as technical elements. Using this method, processes that are in need of improvement and more attention are prioritized based on their significance. This means that if a process has more influence on organization’s objectives and is in a dire situation comparing to others, is prioritized for choice and improvement. In this research process dominance is considered to be an influential element in process ranking (in addition to communication matrix). This is the reason for utilizing DEA techniques for prioritizing processes in quality house. Results of implementing the method in Khuzestan steel company represents this method’s capability of identifying key processes that require improvements in organization’s knowledge management system.

Keywords: knowledge management, organizational performance, fuzzy data, envelopment analysis

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Authors: Muhammad Hikmah

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Based on the population census in 2015, Indonesia consists of 254.9 millions of people, and 80% of them are Muslims (Data of Central Bureau of Statistic). Indonesia becomes the highest number of Muslims civilization in the world. The question would be, is the number of population proportional to the growth of Syariah transaction in Indonesia? It is going to be discussed in this research. The problem limitation of this research is in Syariah Banking. Therefore, Syariah transaction in this study is described as transaction only in Syariah Banking. The researcher focused on the study in Yogyakarta, a city in Indonesia. The development of Syariah Bank assets until January 2016, based on statistic data launched by Financial Services Authority (FSA), has increased Rp 287.44 trillion, however, a total amount of bank achieves Rp 6.198,15 trillions. It means that the assets of Syariah Bank are only 4.64% from the total amount of banking assets in Indonesia, though, Syariah Banking was first established in 1991, known as Bank Muamalat. As we can see that in these 25 years, Syariah Banking could only reach that number. Based on the press conference of FSA and Syariah Banking Exhibition iB Vaganza in 2015, the number of Syariah Bank’s customers are under 10 millions. With 80% of Muslims, Syariah Bank is not able to be a market leader in Indonesia. This will be answered in this research, how much the interest if Muslims in Yogyakarta towards Syariah Bank compared to conventional bank. This study will be conducted in Yogyakarta. The sampling will represent to the muslims having good knowledge of Islam, such as dawn prayer worshipers in some mosques in Yogyakarta. There are some reasons why Indonesian muslims are not interested in Syariah Bank, such as the people do not put trust in Syariah Bank; there are some obligation where they work to have conventional bank; business matters services which is not covered by Syariah Bank where most of them are limited to the laws authorities; and there is no sufficient knowledge about the importance of syariah transaction from religion point of view. Each of them is going to be discussed in this research. The suggestions of this study are we should share our knowledge about Islamic transaction anywhere and we need to support Syariah Bank to have Syariah principles. For those who have the authority should be active as well to announce the rules of the constitution supporting the development of syariah transaction in order to be apply perfectly. We hope that trust from the people will increase, and we should provide Syariah Banking products which fulfill business needs. Finally, syariah transaction will be the solution for all people in the world in bussiness transaction.

Keywords: shariah, Islamic, banking, Indonesia

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Authors: Yanhua Ma, Lu Zhai, Xinchen Wang, Hongyu Liang

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In this paper, by understanding the development status of the human-machine interface in today's automobile cab, a subjective and objective evaluation system for evaluating the optimization of human-machine interface matching in automobile cab was established. The man-machine interface of the car cab was divided into a software interface and a hard interface. Objective evaluation method of software human factor analysis is used to evaluate the hard interface matching; The analytic hierarchy process is used to establish the evaluation index system for the software interface matching optimization, and the multi-level fuzzy comprehensive evaluation method is used to evaluate hard interface machine. This article takes Dongfeng Sokon (DFSK) C37 model automobile as an example. The evaluation method given in the paper is used to carry out relevant analysis and evaluation, and corresponding optimization suggestions are given, which have certain reference value for designers.

Keywords: analytic hierarchy process, fuzzy comprehension evaluation method, human-machine interface, matching optimization, software human factor analysis

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Authors: Rafał Kamiński, Joel Rech, Philippe Bertrand, Christophe Desrayaud

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Additive manufacturing is a hot topic for industry. Among the additive techniques, Selective Laser Melting (SLM) becomes even more popular, especially for making parts for aerospace applications, thanks to its design freedom (customized and light structures) and its reduced time to market. However, some functional surfaces have to be machined to achieve small tolerances and low surface roughness to fulfill industry specifications. The complex shapes designed for SLM (ex: titanium turbine blades) necessitate the use of ball end milling operations like in the conventional process after forging. However, the metallurgical state of TA6V is very different from the one obtained usually from forging, because of the laser sintering layer by layer. So this paper aims to investigate the influence of new TA6V metallurgies produced by SLM on the machinability in ball end milling. Machinability is considered as the property of a material to obtain easily and by a cheap way a functional surface. This means, for instance, the property to limit cutting tool wear rate and to get smooth surfaces. So as to reach this objective, SLM parts have been produced and heat treated with various conditions leading to various metallurgies that are compared with a standard equiaxed α+β wrought microstructure. The machinability is analyzed by measuring surface roughness, tool wear and cutting forces for a range of cutting conditions (depth of cut 'ap', feed per tooth 'fz', spindle speed 'N') in accordance with industrial practices. This work has revealed that TA6V produced by SLM can lead to a better machinability that standard wrought alloys.

Keywords: ball milling, selective laser melting, surface roughness, titanium, wear

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Authors: Kazeem Oluwatoyin Ajape

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The study is concerned with the problem of how to improve the teaching of Arabic as a foreign language in Nigerian Higher Education System. The paper traces the historical background of Arabic education in Nigeria and also outlines the problems facing the language in Nigerian Institutions. It lays down some of the essential foundation work necessary for bringing about systematic and constructive improvements in the Teaching of Arabic as a Foreign Language (TAFL) by giving answers to the following research questions: what is the appropriate medium of instruction in teaching a foreign or second language? What is the position of English language in the teaching and learning of Arabic/Islamic education? What is the relevance of the present curriculum of Arabic /Islamic education in Nigerian institutions to the contemporary society? A survey of the literature indicates that a revolution is currently taking place in FL teaching and that a new approach known as the Communicative Approach (CA), has begun to emerge and influence the teaching of FLs in general, over the last decade or so. Since the CA is currently being adapted to the teaching of most major FLs and since this revolution has not yet had much impact on TAPL, the study explores the possibility of the application of the CA to the teaching of Arabic as a living language and also makes recommendations towards the development of the language in Nigerian Institutions of Higher Learning.

Keywords: Arabic Language, foreign language, Nigerian institutions, curriculum, communicative approach

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Authors: Daniel James Pitchforth, Timothy James Rogers, Ulf Tyge Tygesen, Elizabeth Jane Cross

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Wave loading is a primary cause of fatigue within offshore structures and its quantification presents a challenging and important subtask within the SHM framework. The accurate representation of physics in such environments is difficult, however, driving the development of data-driven techniques in recent years. Within many industrial applications, empirical laws remain the preferred method of wave loading prediction due to their low computational cost and ease of implementation. This paper aims to develop an approach that combines data-driven Gaussian process models with physical empirical solutions for wave loading, including Morison’s Equation. The aim here is to incorporate physics directly into the covariance function (kernel) of the Gaussian process, enforcing derived behaviors whilst still allowing enough flexibility to account for phenomena such as vortex shedding, which may not be represented within the empirical laws. The combined approach has a number of advantages, including improved performance over either component used independently and interpretable hyperparameters.

Keywords: offshore structures, Gaussian processes, Physics informed machine learning, Kernel design

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Authors: Muhammad Iqbal, Edi Istiyono

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Misconceptions are one of the problems in physics learning where students' understanding is not in line with scientific theory. The aim of this research is to find diagnostic tools to identify misconceptions and how to remediate physics misconceptions. In this research, the articles that will be reviewed come from the Scopus database related to physics misconceptions from 2013-2023. The articles obtained from the Scopus database were then selected according to the Prisma model, so 29 articles were obtained that focused on discussing physics misconceptions, especially regarding diagnostic tools and remediation methods. Currently, the most widely used diagnostic tool is the four-tier test, which is able to measure students' misconceptions in depth by knowing whether students are guessing or not and from then on, there is also a trend toward five-tier diagnostic tests with additional sources of information obtained. So that the origin of students' misconceptions is known. There are several ways to remediate student misconceptions, namely 11 ways and one of the methods used is digital practicum so that abstract things can be visualized into real ones. This research is limited to knowing what tools are used to diagnose and remediate misconceptions, so it is not yet known how big the effect of remediation methods is on misconceptions. The researcher recommends that in the future further research can be carried out to find out the most appropriate remediation method for remediating student misconceptions.

Keywords: misconception, remediation, systematic review, tools

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Authors: Juan-Pedro Rica-Peromingo

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The important change taking place with respect to the media and the audiovisual world in Europe needs to benefit all populations, in particular those with special needs, such as the deaf and hard-of-hearing population (SDH) and blind and partially-sighted population (AD). This recent interest in the field of audiovisual translation (AVT) can be observed in the teaching and learning of the different modes of AVT in the degree and post-degree courses at Spanish universities, which expand the interest and practice of AVT linguistic accessibility. We present a research project led at the UCM which consists of the compilation of AVT activities for teaching purposes and tries to analyze the creation and reception of SDH and AD: the AVLA Project (Audiovisual Learning Archive), which includes audiovisual materials carried out by the university students on different AVT modes and evaluations from the blind and deaf informants. In this study, we present the materials created by the students. A group of the deaf and blind population has been in charge of testing the student's SDH and AD corpus of audiovisual materials through some questionnaires used to evaluate the students’ production. These questionnaires include information about the reception of the subtitles and the audio descriptions from linguistic and technical points of view. With all the materials compiled in the research project, a corpus with both the students’ production and the recipients’ evaluations is being compiled: the CALING (Corpus de Accesibilidad Lingüística) corpus. Preliminary results will be presented with respect to those aspects, difficulties, and deficiencies in the SDH and AD included in the corpus, specifically with respect to the length of subtitles, the position of the contextual information on the screen, and the text included in the audio descriptions and tone of voice used. These results may suggest some changes and improvements in the quality of the SDH and AD analyzed. In the end, demand for the teaching and learning of AVT and linguistic accessibility at a university level and some important changes in the norms which regulate SDH and AD nationally and internationally will be suggested.

Keywords: audiovisual translation, corpus linguistics, linguistic accessibility, teaching

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Authors: Haofei Li

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To support academic growth and foster love of learning, MathMates has been introduced for grade 6-8 students at Andrew Hamilton public school in 2022. The program is targeted at students from diverse backgrounds, particularly those underperforming in Pennsylvania System of School Assessment (PSSA) exams. Then, this study aims to evaluate the efficacy of MathMates by comparing student performance on the PSSA test, before and after the intervention. Through a randomized control trial, the study will collect associated costs using the ingredients method and measure the effectiveness for cost-effectiveness analysis. Text messages will be sent to parents/guardians as a reminder of the program and to encourage student participation. The findings of this study will provide valuable insights for funding organizations seeking to understand the impact and costs of math tutoring interventions on student academic achievement, which also emphasizes the importance of the collaborative efforts between higher education and local public schools.

Keywords: mathematics education, mathematics tutoring, college-community initiative, middle schools, Philadelphia public schools, after-school program, PSSA

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Authors: Nihar Kanta Patra, Akhtar Hussain

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This comprehensive study, through the perspective of librarians, explores the library as a metaphor and its profound significance in representing knowledge and learning. It delves into how librarians perceive the library as a metaphor and the ways in which it symbolizes the acquisition, preservation, and dissemination of knowledge. The research investigates the most common metaphors used to describe libraries, as witnessed by librarians, and analyzes how these metaphors reflect the evolving role of libraries in society. Furthermore, the study examines how the library metaphor influences the perception of librarians regarding academic libraries as physical places and academic library websites as virtual spaces, exploring their potential for learning and exploration. It investigates the evolving nature of the library as a metaphor over time, as seen by librarians, considering the changing landscape of information and technology. The research explores the ways in which the library metaphor has expanded beyond its traditional representation, encompassing digital resources, online connectivity, and virtual realms, and provides insights into its potential evolution in the future. Drawing on the experiences of librarians in their interactions with library users, the study uncovers any specific cultural or generational differences in how people interpret or relate to the library as a metaphor. It sheds light on the diverse perspectives and interpretations of the metaphor based on cultural backgrounds, educational experiences, and technological familiarity. Lastly, the study investigates the evolving roles of libraries as observed by librarians and explores how these changing roles can influence the metaphors we use to represent them. It examines the dynamic nature of libraries as they adapt to societal needs, technological advancements, and new modes of information dissemination. By analyzing these various dimensions, this research provides a comprehensive understanding of the library as a metaphor through the lens of librarians, illuminating its significance, evolution, and its transformative impact on knowledge, learning, and the changing role of libraries in society.

Keywords: library, librarians, metaphor, perception

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Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

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Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

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Authors: Introducing Principles of Land Surveying by Assigning a Practical Project

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A practical project is used in an engineering surveying course to expose sophomore and junior civil engineering students to several important issues related to the use of basic principles of land surveying. The project, which is the design of a two-lane rural highway to connect between two arbitrary points, requires students to draw the profile of the proposed highway along with the existing ground level. Areas of all cross-sections are then computed to enable quantity computations between them. Lastly, Mass-Haul Diagram is drawn with all important parts and features shown on it for clarity. At the beginning, students faced challenges getting started on the project. They had to spend time and effort thinking of the best way to proceed and how the work would flow. It was even more challenging when they had to visualize images of cut, fill and mixed cross sections in three dimensions before they can draw them to complete the necessary computations. These difficulties were then somewhat overcome with the help of the instructor and thorough discussions among team members and/or between different teams. The method of assessment used in this study was a well-prepared-end-of-semester questionnaire distributed to students after the completion of the project and the final exam. The survey contained a wide spectrum of questions from students' learning experience when this course development was implemented to students' satisfaction of the class instructions provided to them and the instructor's competency in presenting the material and helping with the project. It also covered the adequacy of the project to show a sample of a real-life civil engineering application and if there is any excitement added by implementing this idea. At the end of the questionnaire, students had the chance to provide their constructive comments and suggestions for future improvements of the land surveying course. Outcomes will be presented graphically and in a tabular format. Graphs provide visual explanation of the results and tables, on the other hand, summarize numerical values for each student along with some descriptive statistics, such as the mean, standard deviation, and coefficient of variation for each student and each question as well. In addition to gaining experience in teamwork, communications, and customer relations, students felt the benefit of assigning such a project. They noticed the beauty of the practical side of civil engineering work and how theories are utilized in real-life engineering applications. It was even recommended by students that such a project be exercised every time this course is offered so future students can have the same learning opportunity they had.

Keywords: land surveying, highway project, assessment, evaluation, descriptive statistics

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Authors: Javier Barrachina, Piedad Garrido, Manuel Fogue, Julio A. Sanguesa, Francisco J. Martinez

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It is very common to observe, especially in Computer Science studies that students have difficulties to correctly understand how some mechanisms based on Artificial Intelligence work. In addition, the scope and limitations of most of these mechanisms are usually presented by professors only in a theoretical way, which does not help students to understand them adequately. In this work, we focus on the problems found when teaching Evolutionary Algorithms (EAs), which imitate the principles of natural evolution, as a method to solve parameter optimization problems. Although this kind of algorithms can be very powerful to solve relatively complex problems, students often have difficulties to understand how they work, and how to apply them to solve problems in real cases. In this paper, we present two interactive graphical applications which have been specially designed with the aim of making Evolutionary Algorithms easy to be understood by students. Specifically, we present: (i) TSPS, an application able to solve the ”Traveling Salesman Problem”, and (ii) FotEvol, an application able to reconstruct a given image by using Evolution Strategies. The main objective is that students learn how these techniques can be implemented, and the great possibilities they offer.

Keywords: education, evolutionary algorithms, evolution strategies, interactive learning applications

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Authors: Y. Xu, L. Xiong, Z. Xu

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In order to protect data privacy, image with sensitive or private information needs to be encrypted before being outsourced to the cloud. However, this causes difficulties in image retrieval and data management. A secure image retrieval method based on orthogonal decomposition is proposed in the paper. The image is divided into two different components, for which encryption and feature extraction are executed separately. As a result, cloud server can extract features from an encrypted image directly and compare them with the features of the queried images, so that the user can thus obtain the image. Different from other methods, the proposed method has no special requirements to encryption algorithms. Experimental results prove that the proposed method can achieve better security and better retrieval precision.

Keywords: secure image retrieval, secure search, orthogonal decomposition, secure cloud computing

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Authors: Asrarul H. Jeelani

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Arsenic contamination of groundwater and its’ health implications in lower Gangetic plain of Indian states started reporting in the 1980s. The same period was declared as the first water decade (1981-1990) to achieve ‘water for all.’ To fulfill the aim, the Indian government, with the support of international agencies installed millions of hand-pumps through water resources development programs. The hand-pumps improve the accessibility if the groundwater, but over-extraction of it increases the chances of mixing of trivalent arsenic which is more toxic than pentavalent arsenic of dug well water in Gangetic plain and has different physical manifestations. Now after three decades, Bihar (middle Gangetic plain) is also facing arsenic contamination of groundwater and its’ health implications. Objective: This interdisciplinary research attempts to understand the health and social implications of arsenicosis among different castes in Haldi Chhapra village and to find the association of ramifications with water resources development. Methodology: The Study used concurrent quantitative dominant mix method (QUAN+qual). The researcher had employed household survey, social mapping, interviews, and participatory interactions. However, the researcher used secondary data for retrospective analysis of hand-pumps and implications of arsenicosis. Findings: The study found 88.5% (115) household have hand-pumps as a source of water however 13.8% uses purified supplied water bottle and 3.6% uses combinations of hand-pump, bottled water and dug well water for drinking purposes. Among the population, 3.65% of individuals have arsenicosis, and 2.72% of children between the age group of 5 to 15 years are affected. The caste variable has also emerged through quantitative as well as geophysical locations analysis as 5.44% of arsenicosis manifested individual belong to scheduled caste (SC), 3.89% to extremely backward caste (EBC), 2.57% to backward caste (BC) and 3% to other. Among three clusters of arsenic poisoned locations, two belong to SC and EBC. The village as arsenic affected is being discriminated, whereas the affected individual is also facing discrimination, isolation, stigma, and problem in getting married. The forceful intervention to install hand-pumps in the first water decades and later restructuring of the dug well destroyed a conventional method of dug well cleaning. Conclusion: The common manifestation of arsenicosis has increased by 1.3% within six years of span in the village. This raised the need for setting up a proper surveillance system in the village. It is imperative to consider the social structure for arsenic mitigation program as this research reveals caste as a significant factor. The health and social implications found in the study; retrospectively analyzed as the collateral impact of water resource development programs in the village.

Keywords: arsenicosis, caste, collateral impact, water resources

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Authors: Reyhan Tekin Sitrava

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Teachers should have robust and comprehensive content knowledge for effective mathematics teaching. It was explained that content knowledge includes knowing the facts, truths, and concepts; explaining the reasons behind these facts, truths and concepts, and making relationship between the concepts and other disciplines. By virtue of its importance, it will be significant to explore teachers and prospective teachers’ content knowledge related to variety of topics in mathematics. From this point of view, the purpose of this study was to investigate prospective mathematics teachers’ content knowledge. Particularly, it was aimed to reveal the prospective teachers’ knowledge regarding the definition of limit and derivate. To achieve the purpose and to get in-depth understanding, a qualitative case study method was used. The data was collected from 34 prospective mathematics teachers through a questionnaire containing 2 questions. The first question required the prospective teachers to define the limit and the second one required to define the derivative. The data was analyzed using content analysis method. Based on the analysis of the data, although half of the prospective teachers (50%) could write the definition of the limit, nine prospective teachers (26.5%) could not define limit. However, eight prospective teachers’ definition was regarded as partially correct. On the other hand, twenty-seven prospective teachers (79.5%) could define derivative, but seven of them (20.5%) defined it partially. According to the findings, most of the prospective teachers have robust content knowledge on limit and derivative. This result is important because definitions have a virtual role in learning and teaching of mathematics. More specifically, definition is starting point to understand the meaning of a concept. From this point of view, prospective teachers should know the definitions of the concepts to be able to teach them correctly to the students. In addition, they should have knowledge about the relationship between limit and derivative so that they can explain these concepts conceptually. Otherwise, students may memorize the rules of calculating the derivative and the limit. In conclusion, the present study showed that most of the prospective mathematics teachers had enough knowledge about the definition of derivative and limit. However, the rest of them should learn their definition conceptually. The examples of correct, partially correct, and incorrect definition of both concepts will be presented and discussed based on participants’ statements. This study has some implications for instructors. Instructors should be careful about whether students learn the definition of these concepts or not. In order to this, the instructors may give prospective teachers opportunities to discuss the definition of these concepts and the relationship between the concepts.

Keywords: content knowledge, derivative, limit, prospective mathematics teachers

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Authors: S. C. Lin, W. W. Cheng, M. S. Wu

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This study attempted to investigate the connection between teacher professional development program and students’ Learning. This study took Readers’ Theater Teaching Program (RTTP) for professional development as an example to inquiry how participants apply their new knowledge and skills learned from RTTP to their teaching practice and how the impact influence students learning. The goals of the RTTP included: 1) to enhance teachers RT content knowledge; 2) to implement RT instruction in teachers’ classrooms in response to their professional development. 2) to improve students’ ability of reading fluency in professional development teachers’ classrooms. This study was a two-year project. The researchers applied mixed methods to conduct this study including qualitative inquiry and one-group pretest-posttest experimental design. In the first year, this study focused on designing and implementing RTTP and evaluating participants’ satisfaction of RTTP, what they learned and how they applied it to design their English reading curriculum. In the second year, the study adopted quasi-experimental design approach and evaluated how participants RT instruction influenced their students’ learning, including English knowledge, skill, and attitudes. The participants in this study composed two junior high school English teachers and their students. Data were collected from a number of different sources including teaching observation, semi-structured interviews, teaching diary, teachers’ professional development portfolio, Pre/post RT content knowledge tests, teacher survey, and students’ reading fluency tests. To analyze the data, both qualitative and quantitative data analysis were used. Qualitative data analysis included three stages: organizing data, coding data, and analyzing and interpreting data. Quantitative data analysis included descriptive analysis. The results indicated that average percentage of correct on pre-tests in RT content knowledge assessment was 40.75% with two teachers ranging in prior knowledge from 35% to 46% in specific RT content. Post-test RT content scores ranged from 70% to 82% correct with an average score of 76.50%. That gives teachers an average gain of 35.75% in overall content knowledge as measured by these pre/post exams. Teachers’ pre-test scores were lowest in script writing and highest in performing. Script writing was also the content area that showed the highest gains in content knowledge. Moreover, participants hold a positive attitude toward RTTP. They recommended that the approach of professional learning community, which was applied in RTTP was benefit to their professional development. Participants also applied the new skills and knowledge which they learned from RTTP to their practices. The evidences from this study indicated that RT English instruction significantly influenced students’ reading fluency and classroom climate. The result indicated that all of the experimental group students had a big progress in reading fluency after RT instruction. The study also found out several obstacles. Suggestions were also made.

Keywords: teacher’s professional development, program evaluation, readers’ theater, english reading instruction, english reading fluency

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Authors: Federico Garrido, Mostafa El Hayani, Ahmed Shams

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The exploration of the potential of artificial intelligence (AI) in architecture is still embryonic, however, its latent capacity to change design disciplines is significant. 'Synthetic Classism' is a research project that questions the underlying aspects of classically organized architecture not just in aesthetic terms but also from a geometrical and morphological point of view, intending to generate new architectural information using historical examples as source material. The main aim of this paper is to explore the uses of artificial intelligence and machine learning algorithms in architectural design while creating a coherent narrative to be contained within a design process. The purpose is twofold: on one hand, to develop and train machine learning algorithms to produce architectural information of small pavilions and on the other, to synthesize new information from previous architectural drawings. These algorithms intend to 'interpret' graphical information from each pavilion and then generate new information from it. The procedure, once these algorithms are trained, is the following: parting from a line profile, a synthetic 'front view' of a pavilion is generated, then using it as a source material, an isometric view is created from it, and finally, a top view is produced. Thanks to GAN algorithms, it is also possible to generate Front and Isometric views without any graphical input as well. The final intention of the research is to produce isometric views out of historical information, such as the pavilions from Sebastiano Serlio, James Gibbs, or John Soane. The idea is to create and interpret new information not just in terms of historical reconstruction but also to explore AI as a novel tool in the narrative of a creative design process. This research also challenges the idea of the role of algorithmic design associated with efficiency or fitness while embracing the possibility of a creative collaboration between artificial intelligence and a human designer. Hence the double feature of this research, both analytical and creative, first by synthesizing images based on a given dataset and then by generating new architectural information from historical references. We find that the possibility of creatively understand and manipulate historic (and synthetic) information will be a key feature in future innovative design processes. Finally, the main question that we propose is whether an AI could be used not just to create an original and innovative group of simple buildings but also to explore the possibility of fostering a novel architectural sensibility grounded on the specificities on the architectural dataset, either historic, human-made or synthetic.

Keywords: architecture, central pavilions, classicism, machine learning

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Authors: Gulfam Haider, sana danish

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Convolutional Neural Networks (CNNs) have emerged as powerful tools for image classification, and the choice of optimizers profoundly affects their performance. The study of optimizers and their adaptations remains a topic of significant importance in machine learning research. While numerous studies have explored and advocated for various optimizers, the efficacy of these optimization techniques is still subject to scrutiny. This work aims to address the challenges surrounding the effectiveness of optimizers by conducting a comprehensive analysis and evaluation. The primary focus of this investigation lies in examining the performance of different optimizers when employed in conjunction with the popular activation function, Rectified Linear Unit (ReLU). By incorporating ReLU, known for its favorable properties in prior research, the aim is to bolster the effectiveness of the optimizers under scrutiny. Specifically, we evaluate the adjustment of these optimizers with both the original Softmax activation function and the modified ReLU activation function, carefully assessing their impact on overall performance. To achieve this, a series of experiments are conducted using a well-established benchmark dataset for image classification tasks, namely the Canadian Institute for Advanced Research dataset (CIFAR-10). The selected optimizers for investigation encompass a range of prominent algorithms, including Adam, Root Mean Squared Propagation (RMSprop), Adaptive Learning Rate Method (Adadelta), Adaptive Gradient Algorithm (Adagrad), and Stochastic Gradient Descent (SGD). The performance analysis encompasses a comprehensive evaluation of the classification accuracy, convergence speed, and robustness of the CNN models trained with each optimizer. Through rigorous experimentation and meticulous assessment, we discern the strengths and weaknesses of the different optimization techniques, providing valuable insights into their suitability for image classification tasks. By conducting this in-depth study, we contribute to the existing body of knowledge surrounding optimizers in CNNs, shedding light on their performance characteristics for image classification. The findings gleaned from this research serve to guide researchers and practitioners in making informed decisions when selecting optimizers and activation functions, thus advancing the state-of-the-art in the field of image classification with convolutional neural networks.

Keywords: deep neural network, optimizers, RMsprop, ReLU, stochastic gradient descent

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Authors: Yasin Akgül, Yusuf Polat, Emine Canbay, Ali Kılıç

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Electrospinning is the most common method to produce nanofibers. However, low production rate is still a big challenge for industrial applications of this method. In this study, morphology of nanofibers obtained from namely centrifugal spinning was investigated. Dominant process parameters acting on the fiber diameter and fiber orientation were discussed.

Keywords: centrifugal spinning, electrospinning, nanofiber, TPU nanofibers

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Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

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Image compression is the heart of several multimedia techniques. It is used to reduce the number of bits required to represent an image. Meteosat Second Generation (MSG) satellite allows the acquisition of 12 image files every 15 minutes and that results in a large databases sizes. In this paper, a novel image compression method based on the arithmetic coding with the sorted Run Length Coding (SRLC) for MSG images is proposed. The SRLC allows us to find the occurrence of the consecutive pixels of the original image to create a sorted run. The arithmetic coding allows the encoding of the sorted data of the previous stage to retrieve a unique code word that represents a binary code stream in the sorted order to boost the compression ratio. Through this article, we show that our method can perform the best results concerning compression ratio and bit rate unlike the method based on the Run Length Coding (RLC) and the arithmetic coding. Evaluation criteria like the compression ratio and the bit rate allow the confirmation of the efficiency of our method of image compression.

Keywords: image compression, arithmetic coding, Run Length Coding, RLC, Sorted Run Length Coding, SRLC, Meteosat Second Generation, MSG

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Authors: David Robert Irvine

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In the dental restoration sector, there has been a shift to using zirconia. With the ever increasing need to decrease lead times to deliver restorations faster the zirconia is machined in its pre-sintered state instead of grinding the very hard sintered state. As with all machining, there is tool wear and while investigating the tooling used to machine pre-sintered zirconia it became apparent that the wear rate is based more on material build up and abrasion than it is on plastic deformation like conventional metal machining. It also came to light that the tool material can currently not be selected based on wear resistance, as there is no data. Different works have analysed the effect of the individual wear mechanism separately using similar if not the same material. In this work, the testing method used to analyse the wear was a modified from ISO 8688:1989 to use the pre-sintered zirconia and the cutting conditions used in dental to machine it. This understanding was developed through a series of tests based in machining operations, to give the best representation of the multiple wear factors that can occur in machining of pre-sintered zirconia such as 3 body abrasion, material build up, surface welding, plastic deformation, tool vibration and thermal cracking. From the testing, it found that carbide grades with low trans-granular rupture toughness would fail due to abrasion while those with high trans-granular rupture toughness failed due to edge chipping from build up or thermal properties. The results gained can assist the development of these tools and the restorative dental process. This work was completed with the aim of assisting in the selection of tool material for future tools along with a deeper understanding of the properties that assist in abrasive wear resistance and material build up.

Keywords: abrasive wear, cemented carbide, pre-sintered zirconia, tool wear

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Authors: Catherine Alex Agbor

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The modern Nigerian society is dynamic, divided in zones based on economic, political and educational resources often shared across the zones. The Six Geopolitical Zones in Nigeria is a major division in modern Nigeria, created during the regime of president Ibrahim Badamasi Babangida. They are North Central, North East, North West, South East, South South and South West. However, the zone used in this study is known as former South-Eastern State of Akwa-Ibom State and Cross-River State; former Rivers State of Bayelsa State and Rivers State; and former Mid-Western Region, Nigeria of Delta State and Edo State. Many reforms have taken place overtime, particularly in the education sector. Education is constantly presenting new ideas and innovative approaches which act to facilitate the rapid exchange of knowledge and provide quality basic education for learners. The Federal Government of Nigeria in accordance with its National Council on Education directed the Nigerian Educational Research and Development Council to restructure its basic education curriculum with the hope to enable the nation meet national and global developmental goals. One of the goals of the 9-year Basic Education Programme is developing in the entire citizenry a strong consciousness for education and a strong commitment to its vigorous promotion. Another is ensuring the acquisition of appropriate levels of literacy, numeracy, manipulative, communicative and life-skills as well as the ethical, moral and civic values for laying a solid foundation for lifelong learning. Therefore, this article at the introductory stage is aimed to describe some key issues in Nigeria’s experience in the basic education curriculum. In this study, particular attention is paid to this very recent educational policy of the Nigerian government known as Universal Basic Education, its challenges and what can be done to make the policy achieve its desired objectives. It progresses to analyze modern requirements for second language teaching; and presents the challenges of second language teaching in Nigeria. Finally, it reports a study which investigated special efforts for appropriate achievement of quality education in language classroom in the south-south zone of Nigeria. One fundamental research question was posed on what educational practices can contribute to current understanding of the structure of language curriculum. More explicitly, the study was designed to analyze the extent to which quality content contributes to current understanding of the structure of school curriculum in the zone. Otherwise stated, it investigated how student-centred educational practices impact on their learning of French language. One hundred and eighty (180) participants (teachers) were purposefully sampled for the study. Qualitative technique was used to elicit information from participants. The qualitative method used was Focus Group Discussion (FGD). Participants were divided into six groups comprising of 30 teachers from each zone. Group discussions were based mainly on curriculum contents and practices. Information from participants revealed that the curriculum content, among others is inadequate and should be re-examined. Recommendations were proffered as a panacea to concrete implementation of the basic education in Nigeria.

Keywords: basic education, quality contents, second language, south-south states

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Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

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Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

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Authors: Evelyn Osehontue Uroro, Richard Bright, Jing Yang Quek, Krasimir Vasilev

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Bacterial infections have been a challenge both in the public and private sectors. The colonization of bacteria often occurs in medical devices such as catheters, heart valves, respirators, and orthopaedic implants. When biomedical devices are inserted into patients, the deposition of macromolecules such as fibrinogen and immunoglobin on their surfaces makes it easier for them to be prone to bacteria colonization leading to the formation of biofilms. The formation of biofilms on medical devices has led to a series of device-related infections which are usually difficult to eradicate and sometimes cause the death of patients. These infections require surgical replacements along with prolonged antibiotic therapy, which would incur additional health costs. It is, therefore, necessary to prevent device-related infections by inhibiting the formation of biofilms using intelligent technology. Antibiotic resistance of bacteria is also a major threat due to overuse. Different antimicrobial agents have been applied to microbial infections. They include conventional antibiotics like rifampicin. The use of conventional antibiotics like rifampicin has raised concerns as some have been found to have hepatic and nephrotoxic effects due to overuse. Hence, there is also a need for proper delivery of these antibiotics. Different techniques have been developed to encapsulate and slowly release antimicrobial agents, thus reducing host cytotoxicity. Examples of delivery systems are solid lipid nanoparticles, hydrogels, micelles, and polymeric nanoparticles. The different ways by which drugs are released from polymeric nanoparticles include diffusion-based release, elution-based release, and chemical/stimuli-responsive release. Polymeric nanoparticles have gained a lot of research interest as they are basically made from biodegradable polymers. An example of such a biodegradable polymer is polycaprolactone (PCL). PCL degrades slowly by hydrolysis but is often sensitive and responsive to stimuli like enzymes to release encapsulants for antimicrobial therapy. This study presents the synthesis of PCL nanoparticles loaded with rifampicin and the on-demand release of rifampicin for treating staphylococcus aureus infections.

Keywords: enzyme, Staphylococcus aureus, PCL, rifampicin

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Authors: Faizah Almalki, Simeon Gill, Steve G. Hayes, Lisa Taylor

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A core element of cultural identity is the traditional costumes that provide insight into the heritage that has been acquired over time. This heritage is apparent in the use of colour, the styles and the functions of the clothing and it also reflects the skills of those who created the items and the time taken to produce them. Modern flat pattern drafting methods for making garment patterns are simple in comparison to the relatively laborious traditional approaches that would require personal interaction with the wearer throughout the production process. The current study reflects on the main elements of the pattern cutting system and how this has evolved in Saudi Arabia to affect the design of the Sawan garment. Analysis of the traditional methods for constructing Sawan garments was undertaken through observation of the practice and the garments and consulting documented guidance. This provided a foundation through which to explore how modern technology can be applied to improve the process. In this research, modern methods are proposed for producing traditional Saudi garments more efficiently while retaining elements of the conventional style and design. The current study has documented the vital aspects of Sawan garment style. The result showed that the method had been used to take the body measurements and pattern making was elementary and offered simple geometric shape and the Sawan garment is composed of four pieces. Consequently, this research allows for classical pattern shapes to be embedded in garments now worn in Saudi Arabia and for the continuation of cultural heritage.

Keywords: traditional Sawan garment technique, modern pattern cutting technique, the shape of the garment and software, Lectra Modaris

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Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: Mohamed I. D. Helal, Mohamed M. El-Mogy, Hassan A. Khater, Muhammad A. Fathy, Fatma E. Ibrahim, Yuncong C. Li, Zhaohui Tong, Karima F. Abdelgawad

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Minimizing the consumption of agrochemicals, particularly nitrogen, is the ultimate goal for achieving sustainable agricultural production with low cost and high economic and environmental returns. The use of biopolymers instead of petroleum-based synthetic polymers for CRFs can significantly improve the sustainability of crop production since biopolymers are biodegradable and not harmful to soil quality. Lignin is one of the most abundant biopolymers that naturally exist. In this study, controlled-release fertilizers were developed using a biobased nanocomposite of lignin and bentonite clay mineral as a coating material for urea to increase nitrogen use efficiency. Five types of controlled-release urea (CRU) were prepared using two ratios of modified bentonite as well as techniques. The efficiency of the five controlled-release nano-urea (CRU) fertilizers in improving the growth of tomato plants was studied under field conditions. The CRU was applied to the tomato plants at three N levels representing 100, 50, and 25% of the recommended dose of conventional urea. The results showed that all CRU treatments at the three N levels significantly enhanced plant growth parameters, including plant height, number of leaves, fresh weight, and dry weight, compared to the control. Additionally, most CRU fertilizers increased total yield and fruit characteristics (weight, length, and diameter) compared to the control. Additionally, marketable yield was improved by CRU fertilizers. Fruit firmness and acidity of CRU treatments at 25 and 50% N levels were much higher than both the 100% CRU treatment and the control. The vitamin C values of all CRU treatments were lower than the control. Nitrogen uptake efficiencies (NUpE) of CRU treatments were 47–88%, which is significantly higher than that of the control (33%). In conclusion, all CRU treatments at an N level of 25% of the recommended dose showed better plant growth, yield, and fruit quality of tomatoes than the conventional fertilizer.

Keywords: nitrogen use efficiency, quality, urea, nano particles, ecofriendly

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Authors: Xiang-Yao Zheng, Jen-Cheng Wang, Joe-Air Jiang

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Improving the line ampacity while using existing power grids is an important issue that electricity dispatchers are now facing. Using the information provided by the dynamic thermal rating (DTR) of transmission lines, an overhead power grid can operate safely. However, dispatchers usually lack real-time DTR information. Thus, this study proposes a long-short-term memory (LSTM)-based method, which is one of the neural network models. The LSTM-based method predicts the DTR of lines using the weather data provided by Central Weather Bureau (CWB) of Taiwan. The possible thermal bottlenecks at different locations along the line and the margin of line ampacity can be real-time determined by the proposed LSTM-based prediction method. A case study that targets the 345 kV power grid of TaiPower in Taiwan is utilized to examine the performance of the proposed method. The simulation results show that the proposed method is useful to provide the information for the smart grid application in the future.

Keywords: electricity dispatch, line ampacity prediction, dynamic thermal rating, long-short-term memory neural network, smart grid

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Authors: Sofia Serra-Dawa

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Adult relationships accrue on a variety of past social experiences, intentions, and emotions that might predispose and influence the approach to and construction of subsequent relationships. The Adult Attachment Theory (AAT) proposes four types of adult attachment, where attachment is built over two dimensions of anxiety and avoidance: secure, anxious-preoccupied, dismissive-avoidant, and fearful-avoidant. The AAT has been studied in multiple settings such as personal and therapeutic relationships, educational settings, sexual orientation, health, and religion. In music scholarship, the AAT has been used to frame class learning of student singers and study the relational behavior between voice teachers and students. Building on this study, the present inquiry studies how attachment types might characterize learning relationships of music students (in the Western Conservatory tradition), and whether particular instrumental experiences might correlate to given attachment styles. Given certain behavioral cohesive features of established traditions of instrumental playing and performance modes, it is hypothesized that student musicians will display specific characteristics correlated to instrumental traditions, demonstrating clear tendency of attachment style, which in turn has implications on subsequent professional interactions. This study is informed by the methodological framework of Adult Attachment Scale-R (Collins and Read, 1990), which was particularly chosen given its non-invasive questions and classificatory validation. It is further hypothesized that the analytical comparison of musicians’ profiles has the potential to serve as the baseline for other comparative behavioral observation studies [this component is expected to be verified and completed well before the conference meeting]. This research may have implications for practitioners concerned with matching and improving musical teaching and learning relationships and in (professional and amateur) long-term musical settings.

Keywords: adult attachment, music education, musicians attachment profile, musicians relationships

Procedia PDF Downloads 145