bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrated Sustainable Development Project for First Year Chemical Engineering Students
Authors: Zakaria Zaki Yamani , Mustaffa Azizul Azri , Rosli Aishah , Yunus Nor Alafiza , M-Yusof Khairiyah , Hassim Mimi Haryani , Sadikin Aziatul Niza , C. Man Siti Hajjar , Abdul Aziz Muhammad Arif , Hasbullah Hasrinah
Published: August 2024

In view of the need to equip students with 21st century attributes, for the past 15 years, first year chemical engineering students undergo specially crafted sustainable problem under the Introduction to Engineering (ITE) and Industrial Seminar and Profession Course (ISP) courses. Recently, in order to improve and create more challenging sustainable problems, the development and execution of the sustainable problem has been integrated with the Introduction to Computer Programming (ICP) course. Under the Smart Consumerism Campaign 2020 (SCC2020), students were given tasks to comprehend, calculate and formulate carbon footprints of normal daily used products. This requires students to grasp the concepts of sustainability and sustainable development, among others, and challenged their critical thinking to come out with an app that could calculate carbon footprint. The integrated effort from three compulsory courses (ITE, ISP and ICP) have helped students develop important engineering skills. It represents an innovative collaboration between courses to develop students’ 21st century attributes and skills. Encouraging feedbacks from students were extracted and analysed from their reflection journals. Thus, the positive impact of course integration has validated the effectiveness and suitability of the established authentic problem based CPBL model for typical engineering courses.
Chaos Based Novel Video Encryption Scheme to Secure Video/Image Information from Any AI-Generated Attacks
Authors: Bajaj Harshita , Das Parnab , Mandal Santanu
Published: August 2024

With the rise of data-intensive activities, methods such as video encryption have gained prominence, paving the way for quantum encryption and AI-powered strategies. It ensures content protection, supports compliance, and enables controlled sharing across sectors like security, satellite & medical imaging, and E-commerce. This study introduces a novel efficient and guarded scheme for encrypting videos as well as images using a 4D hidden chaotic system and application in AI-developed real-time video. A chaotic system is used for developing a unique scrambling process and for the diffusion process. Such an encryption method is rare in recent findings. Various performance analyses are employed to assess the efficiency and resilience of the algorithm. The large key range enhances the algorithm's security against brute force attacks and the careful adjustment of keys empowers the chaos to create different sequences of pseudo-random numbers, which significantly influences the proposed algorithm. The correlation coefficient is close to zero and NPCR is at least 99.62%, UACI is at least 33.50%. After encryption, the histogram is uniformly distributed, key space is extensive with 10^135, and the three-dimensional intensity plot of the encrypted image also exhibits uniformity. Moreover, the encryption algorithm can overcome several noise attacks such as salt and pepper noise, Gaussian noise additionally provides strong resistance against clipping attacks, underscoring the algorithm's effectiveness and resilience.
Enhanced Readiness Forensic Framework for the Complexity of Internet of Things (IoT) Investigation Based on Artificial Intelligence
Authors: Rizal Randi , Selamat Siti Rahayu , Mas’ud Mohd. Zaki , Widiyasono Nur
Published: August 2024

The growing versatility of Internet of Things devices increases the possibility of multiple attacks occurring and being carried out continuously. The limited processing capabilities and memory capacity of Internet of Things devices pose challenges for security and forensic analysis in collecting and documenting various attacks targeting these devices during the forensic investigation process. Thus, forensic investigative analysis goes beyond expectations, offering a holistic understanding of the complex consequences arising from IoT device attacks that have occurred. These issues and challenges provide important insights into vulnerabilities, potential future threats, and steps to effectively increase the resilience of the IoT ecosystem against the evolving cyber-attack risk landscape. Apart from that, the large amount of IoT attack data generated raises several problems. Such as the difficulty of quickly identifying threats and in-depth forensic analysis of each very diverse attack. The implementation of artificial intelligence is a very useful solution in overcoming the forensic investigation challenges that arise due to IoT attacks with the enormous increase in data volume and complexity. Therefore, this research aims and proposes to improve the IoT forensic readiness framework by collecting and analyzing digital evidence in detecting various attacks from various IoT devices automatically based on an artificial intelligence approach and functioning as an early warning system. Enhanced the proposed IoT forensic readiness framework based on ISO/IEC 27043 serves as a prototype for detecting and collecting various types of attacks as potential digital evidence from various IoT devices, as well as effective forensic investigation of digital evidence with the utilization of smart repository.
Contributing Factors to Key Performance Indicators of Saudi Arabian Construction Project Success
Authors: Hussain Sharafat , Hasmori Muhammad Fikri , Balasbaneh Ali Tighnavard , Khan Muhammad Wajidullah , Sohu Samiullah
Published: August 2024

Practitioners and scholars express concern about construction projects that are unable to achieve the specified goals or objectives. Therefore, this study sought to identify the factors that impact Key Performance Indicators (KPIs), which are crucial to every successful construction project. Construction performance measurement often uses objective KPIs to quantify project success. Project success is presumed if it is completed on schedule, according to budget, and with the specified quality, known as the “iron triangle.” Subsequently, reviewing relevant literature, crucial KPIs for construction projects were selected. Then, a pilot study finalized the empirical survey questionnaire. The survey was administered to 124 practitioners in the KSA Construction industry, and the response rate was 85%. Employing SPSS version 26, the relative importance index (RII) and mean value were calculated to prioritize. The internal consistency and overall value of the coefficient alpha test were 0.717, and the Kaiser-Meyer-Olkin (KMO) statistics were 0.716 > 0.5, confirming sufficient sample size and further study. The survey determined that respondents placed KPIs in construction projects from 3.802 to 4.387 and RII from 0.877 to 0.760. Most respondents rated "time of project" as the first highest ranking on KSA construction projects, with a mean score of 4.387 and RII of 0.877. The second highest was "cost of project," followed by "quality," "safety," and "sustainable construction." The lowest five ranks were "Defects," "Procurement," "Maintenance," "Human Resource Management," and "Business Performance," with mean scores of 3.802 and RII 0.760. This research adds to the corpus of knowledge on the Saudi Arabian key performance indicators for construction projects.
The Accuracy and Error of Ground Penetrating Radar System with Machine Learning Support Vector Regression Technique
Authors: Cheah Chow Wei , A Karim Mohd Nazri , Lee Yeng Seng , Md Ghazal Mimi Diana i
Published: August 2024

Ground penetrating radar (GPR) is a non-destructive evaluation technique which involve knowledge of electromagnetic theory. Basically, there are three types of radar systems that are often applied in radar applications such as Monostatic, Bistatic, and Multi-static radar. Besides, in order to detect and locate the underground object, various technique has been implemented to cater issues in GPR such as clutter issues, inaccuracy in detect and locate the target object, signal loss, properties of soil and etc. In this paper, machine learning (ML) with support vector regression (SVR) is applied in GPR system using copper plat as buried object. Evaluation and validation on this method was carried out in term of S-Parameter and operating frequency. The scope of this work focuses on data analysis for the accuracy of object detection, validation graph and the error signal processing of Machine Learning in GPR system. The result of the experiment was shows low error, the validation point fit to hyperplane line (validation graph). Therefore, the output that expected for this research is validate the low false alarm rate of machine learning in GPR system.
Detecting and Classifying Household Insects in Iraq by Using Transfer Learning Models
Authors: Ewaeed Noora Abdallah , Abed Hazim Noman , Abed Sanaa Nagem
Published: August 2024

Household insects are a part of everyday life, yet they may be a menace in some different situations. Developing more efficient detection and classification methods is necessary since the conventional approach may be laborious and error-prone. By harnessing the ability of algorithms to handle enormous volumes of data and extract essential information, machine learning has emerged as a potential method for insect detection and classification. In this study, insect detection and classification were proposed based on machine learning and deep learning techniques. Transfer learning was used for feature extraction, a YOLOv8 for detection, and a support vector machine algorithm for classification. Transferring learning models may significantly boost detection and classification precision when learning about insects. Convolutional neural networks (CNN) are often used as a transfer learning model for image categorization. Insect Recognition Using Deep Transfer Learning Models Would Be Shown The IP102 and Leeds butterfly database, and insect classification were used for this study. In addition, a special database was established in Iraq called the Household Insects Database. Deep learning models Resnet50 and VGG19 were chosen as described in the study. The chosen models' robustness may be shown by performing tests that measure their accuracy and performance measures, including accuracy, recall, and F1 score, and concluding with a comparison of findings to other studies that have utilized the same IP102 dataset. Compared to other works in the field, the submitted work performed very well on every metric tested: precision, recall, and F1 score. The experimental results recommend using the Resnet50 model to detect insects because its accuracy reaches more than 95.11%. At the same time, the results of the vgg19 model came to 93.89%.
Real-Time Multi-Agent Based Flood Forecasting and Warning System Model: A Malaysia Perspectives
Authors: Md Rashid Nor Aimuni , Zainal Abidin Zaheera , Abas Zuraida Abal
Published: August 2024

The development of a precise flood forecasting methodology necessitates the utilization of an automated data collection system for the examination of a comprehensive range of hydrographic catchment parameters that are continuously monitored. Monitoring river basins is a topic of significant strategic importance. In recent years, researchers have introduced several cutting-edge technologies to enhance this process, including the utilization of artificial intelligence (AI). Notably, AI has been applied in various techniques such as knowledge-based systems, agent-based modelling, and neural networks. These AI-based approaches have shown promise in improving the monitoring and management of river basins. The nationwide flood forecasting and warning system, known as 'NaFFWS', has been implemented in Malaysia through the PRAB program. The establishment was created with the purpose of facilitating the advancement of mitigation technologies aimed at minimizing the potential consequences of forthcoming flood events. The current utilization of modelling tools incorporates multiple factors that contribute to uncertainty, which can be attributed to the specific characteristics of the system. This review paper aims to explore the potential capabilities of an integrated multi-agent system specifically designed for the purpose of monitoring flood events. The proposed system is composed of logical agents and utilizes deep reinforcement learning (MADRL) techniques. This approach introduces a conceptual framework wherein a collection of intelligent agents collaborates to accomplish diverse tasks and effectively exchange information, ultimately facilitating the generation of timely alerts in the context of flood crises. The agents in question operate in collaboration with a hybrid approach that combines the DQN and TD3 algorithms. This combination is utilized to mitigate the various challenges arising from uncertainty. The proposed model's contribution is notable in enhancing flood forecasting accuracy amidst diverse sources of uncertainty.
An Enhancement of Multi-Factor Weighted Approach Technique in Prioritizing Test Cases by Comparing Similarity Distance
Authors: Al-Shaibani Alaa Alrhman Mohammed Raweh , Ahmad Johanna , Hassan Rohayanti , Baharom Salmi , Antari Dwinta Suci
Published: August 2024

Software testing is one of the most critical phases in the software development life cycle model (SDLC), where the quality of a software product is evaluated. Test case prioritization (TCP) is used to prioritize and schedule test case execution to conduct higher-priority test cases to optimize the software testing process. Traditionally, techniques rely on source code or a specification for the tested system. Therefore, numerous factors and techniques have been used to optimize the prioritization process. One of the factors is distance. String Distance aims to find the degree of similarity between the test cases, which helps prioritize the test case according to the dissimilar value. The higher the dissimilarity value, the higher the probability of detecting new faults. Previous research has used Jaccard Distance to measure the distance to prioritize test cases with the same priority value. In the meantime, the Manhattan Distance is used in this research as it provides a better measure of distance. Our aim of this research is to compare and evaluate both Jaccard and Manhattan Distance algorithms in terms of their effectiveness to formulate the enhancement of the previous multi-factor weighted Approach. The research experiment has shown the process of calculating the Distance matrix for the sample Java Programs and subsequent evaluation using the mutation testing approach and APFD calculation. The results of The Average Percentage of Fault Detected (APFD) of the Test case prioritization by the Manhattan Distance matrix have obtained a higher value, validating its hypothesized effectiveness.
Trends Virtual Laboratory for Practical Learning in Vocational Education
Authors: Subekti Sri , Ana Ana , Muktiarni Muktiarni , Ismail Affero , Masek Alias
Published: August 2024

Using virtual laboratories for practical learning in vocational education has significantly increased in recent years. This study aims to analyse virtual laboratory research trends for practical learning in vocational education through bibliometric analysis by taking data from Scopus (intro/issue). The method used in this bibliometric journal article is the bibliometric method. This research step consists of (i) determining search keywords, (ii) collection of publication data, (iii) bibliometric data processing, (iv) bibliometric data mapping, and (v) data analysis. The search keywords used to collect data were "Virtual laboratory," "Vocational," and "Education." There are 31 articles indexed by Scopus from 2002 to 2023. From 2019 to 2023, research on virtual laboratories in vocational education has increased. This is because access to computer technology, the internet, and mobile devices is increasingly widespread, and a surge in technology use occurred during the COVID-19 pandemic. The results of the bibliometric mapping analysis show there are 24 terms grouped into 3 clusters. The terms virtual laboratory and vocational education are related in research. Virtual laboratories help overcome problems in vocational education, especially for productive vocational subjects such as working on dangerous equipment.
Performance Analysis of Strain Sensor Based on Fiber Bragg Grating
Authors: Naim Nani Fadzlina , Kamarozaman Nurul Farhana Husna , Yusof Azita Laily , Ya’acob Norsuzila , Sarnin Suzi Seroja , Ramza Harry
Published: August 2024

This project presents on the analysis of strain sensing performance through software simulation and experimental setup. The bare and FBG strain sensors are tested by applying strain at the grating region of the FBG and the output of the experiment is displayed on the optical spectrum analyzer (OSA) in terms of power (dBm) and wavelength (nm). The performance of the FBGs has been evaluated by comparing the strain sensitivity and wavelength shift obtained. The FBG strain sensor has a strain sensitivity of 38.25 pm/N, which is higher than the bare FBG's strain sensitivity of 12.49 pm/N. The FBG strain sensor's experimental and simulation performance is also investigated. OptiSystem software is used to simulate the strain sensor performance. The overall results indicate the ability of FBG to be utilized as a strain sensor as the Bragg wavelength is shifted by the combination effect of effective refractive index and grating period influenced by the changes of strain
Designing Persuasive Sustainable Waste Management Application for Urban Community in Malaysia: Understanding End-User Perspectives
Authors: Mohd Mohadis Hazwani , Azmin Shompa Zohora
Published: August 2024

Solid waste management in urban areas in Malaysia is a critical issue that requires immediate attention. Waste management in Malaysia will become even more complex and difficult in the future due to the tremendous growth of the economy, urban population, and consumption patterns. The primary issue in this situation is the growing amount of waste production, which is outpacing the growth in disposal capacity. The Malaysian government has introduced the Waste Separation at Source Initiative (SSI), which mandates the Malaysian community to sustainable waste management practices in their daily lives. However, most urban Malaysians are unaware of these environmentally friendly waste management practices, despite the government's numerous attempts. Therefore, how to motivate the Malaysian community to adopt sustainable waste management practices has been of concern.  A variety of persuasive technologies (PT) applications have been developed within sustainable HCI to promote sustainable waste management. However, its effectiveness among the urban community in Malaysia remains unknown.  Accordingly, to develop an effective persuasive application for sustainable waste management, this study attempts to investigate end-user perspectives on effective persuasive design principles based on the Persuasive System Design (PSD) model. In-depth interview sessions were conducted with seven (7) participants, aged 31 to 47 years residing in various regions in Klang Valley. During interview sessions, participants were presented with several user interfaces (UIs) of waste management applications showing how each persuasive design principle had been applied.  Next, we conducted a thematic analysis of positive and negative reviews of end-users to identify effective persuasive design principles to encourage sustainable waste management. Our results uncover 20 positives, 3 negatives, and 5 mixed views (positive and negative) perceptions. The positive perceptions fall under the following categories: reduction, tailoring, personalization, self-monitoring, simulation, praise, rewards, reminders, liking, social role, trustworthiness, expertise, surface credibility, real-world feel, verifiability, social learning, normative influence, and cooperation principles. Some of the negative perceptions include rehearsal, similarity, and recognition principles. Meanwhile, tunneling, suggestion, authority, third-party endorsement, competition, social comparison, and social facilitation principles with mixed views (positive and negative) perceptions.
Optimization of Fused Deposition Modelling Acrylonitrile-co-Butadiene-co-Styrene Parameters using ANOVA and Hybrid GRA–TOPSIS
Authors: Sabry Ibrahim , El-Attar Tarek , Hewidy A.M.
Published: August 2024

Traditional materials used in mechanical structures should be swapped out for less expensive alternatives that are both strong and simple to produce. ABS+, or poly (acrylonitrile-co-butadiene-co-styrene), is a substitute material used in 3D printing. The quick changes in model size and forms during the prototype stage and the comparably inexpensive cost of new parts are made possible by 3D printing technology. In the market for 3D printers, there are several suppliers of plastic materials. A combined MCDM technique and analysis of variance are used in the current work to assess the FDM process's parameters. During the experiment, three process factors—Layer height, extrusion temperature, and printing speed—are considered, and their associated response parameters, ultimate tensile strength, and surface roughness are established. The multiple-criteria decision-making strategy, which incorporates hybrid GRA-TOPSIS and ANOVA, is employed since there are two responses and two objectives. The ideal parameters determined by these statistical methods were an extrusion temperature of 2600c, layer height of 0.2 mm, and printing speed of 60 mm/s. This study concludes that the optimal parameters for the investigated experimental data are convergent regardless of the two techniques used.
Non-Orthogonal Algorithm with Fourier Transform Symmetry for Performance Enhancement of DCO-OFDM Systems
Authors: S. Elbakry Mohamed , K. Eldyasti Sherif , Ramadan Khaled
Published: August 2024

The direct current (DC) biased optical orthogonal frequency division multiplexing (DCO-OFDM) technique has been widely used in visible light communication (VLC) systems due to its ease of installation. In this study, the Fourier symmetry (FT) scheme is proposed for the DCO-OFDM systems using BPSK modulation scheme. Furthermore, the proposed FT symmetry scheme is used either for increasing the data rate of the system or for enhancement the bit error rate (BER) system performances. In addition, the non-orthogonal algorithm (NOA) combined with the FT symmetry scheme is proposed for improving the DCO-OFDM system using QPSK modulation scheme. In the proposed NOA algorithm, the successive interference cancellation (SIC) is used at receiver to overcome interfering between real and imaginary parts. In the simulation, different transforms such as Fast Fourier transform (FFT), discrete cosine transform (DCT) and discrete Wavelet transform (DWT) are applied in the proposed schemes. Finally, simulation results show that the proposed schemes can significantly increase the overall system performance compared to the conventional scenario via different measure of performance such as BER, power spectral density (PSD) and peak to average power ratio (PAPR).
Comprehensive Review of Different Approaches used by Manufacturing Industries in Handling Capacity Planning under Demand Uncertainties
Authors: Ang Chew Woon , Yahaya Saifudin Hafiz , Salleh Mohd Shukor , Cahyadi Novi
Published: August 2024

In today's dynamic industrial environment, efficient capacity planning is of essential relevance, especially in the face of unpredictable and fluctuating client demands. Failure to address demand uncertainty may lead to undesirable effects, such as overproduction or underproduction. This study carefully analyses variety of capacity planning approaches employed by the industry. Additionally, the research extended to explore several simulation approaches employed as powerful tool in tackling capacity planning issues, delivering adaptable solutions that respond to the particular demands of both major organizations and small to medium-sized firms. This analysis underlines the vital role of simulation in increasing operational performance, optimizing resource allocation, and reacting to changing production needs, eventually leading to greater competitiveness and efficiency within the manufacturing industry.
The Chemical Puzzle of Weak G-Band Stars: A Comprehensive Study of HD 54627, HD 105783, HD 198718, and HD 201557
Authors: Holanda N. , Flaulhabe T. , Quispe-Huaynasi F. , Sonally A. , Pereira C. B.
Published: August 2024

Weak G-band stars (WGBs) are a unique class of objects characterized by weak CH molecular lines in the Fraunhofer G band, indicative of a deficiency in 12C. This peculiar spectral feature is often accompanied by significant enrichments in N and, occasionally, Li and Na abundances. Despite their rarity and recent discoveries of new WGB candidates, the underlying formation mechanism of these stars remains unknown. In this study, we present a comprehensive chemical analysis of four neglected WGBs: HD 54627, HD 105783, HD 198718, and HD 201557. These stars, though identified as WGBs, have been poorly studied to date. Our analysis utilizes high-resolution échelle spectra with a power resolution of R ≈ 48,000, complemented by photometric and astrometric data from the literature. Applying the local thermodynamic equilibrium (LTE) approximation we determine the chemical abundance and then we conduct posterior non-LTE (NLTE) corrections for specific chemical abundances, including Li, O, Na, and Mg. Additionally, we provide details on the projected rotational velocities (

v

sin

i

) and conduct a thorough investigation of the kinematics and orbits of our sample, comparing them with other well-studied WGBs reported in the literature. Our findings indicate that these stars originate from the thin disk, as evidenced by the absence of alpha-element enrichment and kinematics. Notably, half of the WGBs in our sample exhibit Li-rich characteristics, and we identify no rapid rotators (

v

sin

i

>

8.0 km s−1) or infrared excess among our studied stars.
Mating behavior and three types of mating songs of the sandy beach-dwelling ground cricket Dianemobius csikii (Grylloidea, Trigonidiidae, Nemobiinae)
Authors: Kuriwada Takashi
Published: August 2024

This study aimed to investigate the mating behavior of the sandy beach-dwelling ground cricket, Dianemobius csikii (Bolívar, 1901) (Orthoptera, Grylloidea, Trigonidiidae, Nemobiinae). The calling songs of males were recorded, and the temporal structures of the songs were analyzed. Subsequently, the courtship song and mating behavior of cricket pairs were observed. The calling song consisted only of monotonous chirps, while the courtship song consisted of similar chirps and ticks consisting of a single pulse. Dianemobius csikii exhibited a relatively longer courtship duration than other cricket species. The female stayed with the male for approximately 25 min while the male emitted the courtship song. The male then changed to the trill song, which is a continuous song, just before copulation. Copulation occurred within 10–40 s of the male emitting the trill song. The courtship behavior differs from that of other well-studied cricket species, such as Gryllinae. The findings of this study provide insight into the mating behaviors of crickets.
Taxonomic review of Amemboa Esaki, 1925 from China, with description of a new species (Hemiptera, Heteroptera, Gerridae)
Authors: Leng Zhaoqi , Zhang Beichen , Jin Zezhong , Ye Zhen
Published: August 2024

The species of Amemboa Esaki, 1925 from China are reviewed. Amemboa hainanicasp. nov., is described from Hainan Island, and Amemboa burmensis J. Polhemus & Andersen, 1984 is newly recorded from China. Additionally, diagnoses and new distribution records are provided for six species previously reported from China: A. brevifasciata Miyamoto, 1967, A. cristata J. Polhemus & Andersen, 1984, A. esakii J. Polhemus & Andersen, 1984, A. fumi Esaki, 1925, A. riparia J. Polhemus & Andersen, 1984, and A. speciosa J. Polhemus & Andersen, 1984. Photographs and line drawings of the habitus, the diagnostic characteristics of males, in-situ habitus, and their habitats are presented. A key and a distribution map are also provided for species of Amemboa occurring in China.
Decision Aid–Led Tapering of Biologic and Targeted Synthetic Disease-Modifying Antirheumatic Drugs in Rheumatoid Arthritis: A Qualitative Study
Authors: Lee Jungyeon , Barber Claire E.H. , Jung Michelle , Kaminska Elzbieta , Bansback Nick , Richards Dawn , Proulx Laurie , Rebutoc Ann , Hazlewood Glen S.
Published: August 2024

Objective

To explore the experiences and perspectives of patients and rheumatologists on decision aid (DA)-led tapering of advanced therapy in rheumatoid arthritis (RA).

Methods

Semistructured interviews were completed with patients and rheumatologists, embedded within a pilot study of DA-led tapering (ie, dose reduction) of biologic disease-modifying antirheumatic drugs (bDMARDs) and targeted synthetic DMARDs (tsDMARDs) in RA. All patients were in sustained (≥ 6 mos) remission and had chosen to reduce their therapy after a DA-led shared decision with their rheumatologist. The rheumatologists included those participating in the pilot (n = 4), and those who were not (n = 8). Reflexive thematic analysis of audiotaped and transcribed interviews identified themes in the group experiences.

Results

Patients (n = 10, 6 female) unanimously found the DA easy to understand and felt confident in shared decision making about treatment tapering and managing flares. Rheumatologists’ (n = 12, 5 female) perspectives on tapering bDMARDs and tsDMARDs varied widely, from very supportive to completely opposed, and influenced their views on the DA. Rheumatologists expressed concerns about patient comprehension, destabilizing a stable situation, risks of flare, and extending appointment times. Despite their initial reservations about sending the DA to all eligible patients ahead of appointments, 3 of 4 participating rheumatologists adopted this approach during the pilot, which had the benefit of facilitating patient-led conversations.

Conclusion

A DA-led strategy for tapering advanced therapy in RA was acceptable to patients and feasible in practice. Sending patients a DA ahead of their appointment facilitated patient-led conversations about tapering.
Vanishing Abdominal Aorta
Authors: Yamada Kenji , Hazue Ryo , Rokutanda Ryo
Published: August 2024

Fewer than 1% of Takayasu arteritis (TA) cases are diagnosed in individuals over 60 years old.1Early-stage TA generally presents with nonspecific systemic inflammatory symptoms, which can progress to the chronic, fibrotic occlusive phase,2although there is significant heterogeneity in disease activity.3
Functions of bounded $ {\bf (2, k)} $-variation in 2-normed spaces
Authors: Arenas Jaffeth Cure , Sotelo Kandy Ferrer , Villar Osmin Ferrer
Published: August 2024

In this work, the notion of function of bounded variation in 2-normed spaces was established (Definition 4.2), the set of functions of bounded $ (2, k) $-variation was endowed with a norm (Theorem 4.5), and it was proved that such a set is a Banach space (Theorem 4.6). In addition, the fundamental properties of the functions of bounded $ (2, k) $-variation in the formalism of 2-Hilbert and 2-normed spaces were studied (see Theorems 4.1, 4.3, 4.4). Also, it was shown how to endow a 2-normed space with a function of bounded $ (2, k) $-variation from a classical Hilbert space (Proposition 4.1). A series of examples and counterexamples are presented that enrich the results obtained in this work (4.1 and 4.2).
Equitable Digital Practices for Multilingual Learners
Authors: Mendoza Laura E.
Published: August 2024

Leveraging today's use of technology is a responsibility that educators, administrators, and policymakers should be sharing. Unfortunately, this task has been confluently left to educators, who, in addition to having to face many other challenges in their classrooms, have to plan accordingly how technology can represent a benefit and not a struggle for their students. In the multilingual classroom, where educators and students concurrently are facing a variety of types of marginalization, finding the balance between including differentiated instruction through technology and empowering students through various digital literacy practices might be even harder. The present chapter aims to contribute to the growing knowledge of the intersectionality that equity and digital literacy practices represent in the multilingual classroom. This chapter also aims to continue the conversation of the cultural competence educators and multilingual learners must navigate to be successful at school and outside of it.
The Deployment of Blended Learning for English Vocabulary Enhancement
Authors: Tran Thao Quoc , Nguyen Thao Phuong
Published: August 2024

Blending learning (BL) has emerged as one of the effective teaching and learning approaches in education, and research on the deployment of BL has been extensively conducted. This book chapter sets to present a mixed-methods study exploring Vietnamese L2 students' perceptions of the effects of BL on their English vocabulary enhancement. A cohort of 300 L2 students studying general English (GE) at a Ho Chi Minh City-based university in Vietnam took part in answering a questionnaire, and 15 of them participated in semi-structured interviews. Statistical analysis and content analysis were employed for quantitative and qualitative data analysis, respectively, and the sociolinguistic perspective was adopted for interpreting the results. The findings unraveled that Vietnamese L2 students perceived the effects of the deployment of BL in GE courses on their vocabulary enhancement as they could remember a wide range of vocabulary, recognize vocabulary meaning in context, and apply vocabulary in writing and speaking effectively.
Using Digital Tools to Innovate in Higher Education
Authors: Delplancq Véronique , Costa Ana Maria , Pereira José , Gillain Romain , Fidalgo Susana
Published: August 2024

This chapter explores the evolving role of pedagogical innovation in foreign language (FL) classes for media studies undergraduates at the School of Education (ESEV) of the Polytechnic Institute of Viseu (Portugal). It highlights the transformation of digital tools, initially seen as “icebreakers,” into powerful aids for active methodologies, fostering both hard and soft skills essential for contemporary society and the job market. Teachers commonly integrate online applications, online platforms, and social networks to enhance FL learning. The narrative delves into challenges faced by teachers and students amid constant societal changes. The text emphasizes skills development, improvements over traditional methods, encountered difficulties, and the dynamics within the teaching-learning process. One relies upon gamification as a tool in FL classes, so as to look into its potential to contribute to the systematic exploration of successful educational innovations supported by digital tools in higher education, providing a foundation for future research.
Authentic Presentation Experiences as a Tool to Develop Transferable Skills
Authors: Schneider Jennifer
Published: August 2024

Despite the widely recognized and acknowledged importance of communication, written, and presentation skills, students often struggle in this area, especially in connection with digital literacy. A noted disconnect between current skill sets, including digital literacy, and workplace needs supports an inquiry into how best to address this challenge in equitable and inclusive ways so as to strengthen both student awareness of the importance of transferable skills and the associated development of digital literacy and soft skills across disciplines. This chapter describes a course-long project that is grounded in principles of feminist digital pedagogy digital literacy, inclusive instruction, and equity and designed to support the development and transfer of written, presentation, and soft skills in a legal technology course developed at a two-year community college located in a large urban area and with a student population comprised primarily of minority and first-generation students. The project emphasizes equitable and inclusive reliance upon technology in all steps and components.
Understanding Shadow Education
Authors: Kumaravel Sathish Kumar , Murugesan Regan , Nagaram Nagadevi Bala , Mohan Kala Raja , Rasappan Suresh
Published: August 2024

Shadow education, also known as private tutoring or supplementary education, has global implications for educational systems. This abstract explores its origins, prevalence, impact, and contributing factors. It shapes academic trajectories, influences student outcomes, and addresses educational equity. Cultural norms, perceived educational system shortcomings, and historical trends contribute to its growth. The abstract delves into its integration into educational systems, effectiveness in enhancing academic performance, and potential consequences. Factors like socioeconomic disparities, high-stakes exams, and cultural pressures drive its demand. Policymakers face challenges reconciling its benefits with drawbacks and implications for equity and social mobility. The abstract provides insights into regulatory measures and policy responses, offering a resource for navigating the coexistence of formal and shadow education.
Does Tutoring Participation Affect Relationship Patterns and Mental Well-Being?
Authors: Alam Md. Bayezid , Zhu Zhiyong
Published: August 2024

While many studies have explored the impact of private tutoring on academic performance, this chapter aims to investigate the effects of students' tutoring participation on their relationship patterns and mental well-being. The semi-structured interviews with six Bangladeshi higher secondary (Grades 11–12) students provided the qualitative data. A pre-determined thematic analysis procedure was employed to analyze the data. The findings illustrated that private tutoring adversely affected students' relationship patterns with their teachers, peers, families, relatives, and communities. It overburdens students' lives, reduces the scope for recreation, and exhausts them mentally. The study may contribute to the evolving empirical literature on shadow schooling in Bangladesh. Policymakers may find the data useful in reducing students' workloads and guarantee their holistic growth.
The Subterranean English Training Market
Authors: Hu Hengzhi , Zhou Qing
Published: August 2024

This chapter explores the perceptions of parents and students toward China's double-reduction policies and examines the factors that drive resistance to these policies through shadow English training (SET). While the double-reduction policies are designed to alleviate students' academic burden and promote a balanced educational approach, this qualitative investigation reveals a complex interplay between policy objectives and grassroots resistance. The study identifies key concerns among parents and students, including the perceived dilution of education quality at school, limited SET opportunities for academic development, and exacerbated educational inequity. Despite recognising the disadvantages of SET, such as increased financial burden and social isolation, stakeholders highlight its irreplaceable role in providing targeted after-class instruction and enhancing academic performance in China's competitive educational system.
Unraveling the Shadow
Authors: Sharma Gaurab Kumar
Published: August 2024

Shadow education, private tutoring outside mainstream schooling, has expanded exponentially in India since the 1990s. This tutoring aims to give students an edge in competitive exams for limited university seats. Though historically present, its scale has fueled equity concerns. This chapter analyzes the forces driving growth and their implications on finances, disparities, learning, student welfare, and public schooling. Quantitative evidence shows the stunning rise in prevalence and spending, from cities to rural India. Competitive exams, mobility aspirations, and dissatisfaction with public education propel demand. The chapter highlights financial burdens, including families incurring debt, and access inequalities across socioeconomic, geographic, gender and caste lines. Learning outcomes remain contested, with risks of teaching to the test. Tutoring's relationship with student stress and public school quality is complex. While bans face hurdles, regulatory options have tradeoffs. Further research on long-term impacts is imperative.
Blockchain Technology and Islamic Finance
Authors: Kismawadi Early Ridho
Published: August 2024

This research aims to explore the potential applications of advanced blockchain technology such as DeFi (decentralized finance) and NFTs (non-fungible tokens) in supporting halal micro, small, and medium enterprises (MSMEs). Through theoretical analysis and case studies, the research identifies how these technologies can be integrated within the framework of Islamic finance, while highlighting the emerging ethical and operational implications. The methodology of this research involves extensive literature review and content analysis of existing blockchain projects. The results show that DeFi and NFTs offer significant opportunities for halal MSMEs in gaining easier access to financing, reducing transaction costs, and increasing the speed and transparency of financial operations.
Digital Innovation in Indonesian Sharia Banks
Authors: Said Muhammad , Muhammadun Muzdalifah
Published: August 2024

This study examines the implementation of digital innovation in the practices of Sharia banks in Indonesia and its impact on increasing operational efficiency and the variety of financial services offered to micro, small, and medium enterprises (MSMEs). Using a qualitative approach, this research identifies the strategies and approaches used by Sharia banks in digitizing their products and services to support MSME expansion into international markets. The results show that the adoption of digital technologies such as AI and blockchain by Sharia banks can enhance operational efficiency, expand financial services, and improve the global competitiveness of MSME products. However, MSMEs still face significant challenges, including a lack of financial literacy and access to digital technology. Policy recommendations include improving digital literacy, collaborating with fintech, developing technology-based financing models, and evaluating government policies. This study aims to provide guidance for Sharia banks and the government in formulating effective strategies to advance the Islamic economy and MSMEs in Indonesia through the adoption of digital technology.
Innovative Product Management Strategies for Sustainable SMEs
Authors: Chandratreya Abhijit
Published: August 2024

This chapter explores the dynamic landscape of product management within small and medium-sized enterprises (SMEs), focusing on sustainable practices and innovation. It delves into the challenges faced by SMEs in integrating sustainability into their product management strategies while remaining competitive in the market. Through case studies and theoretical frameworks, it examines innovative approaches that SMEs can adopt to align their product management with sustainability goals. Key themes include agile development, circular economy principles, stakeholder engagement, co-creation, green supply chain management, and market responsiveness. By leveraging these strategies, SMEs can not only enhance their environmental and social impact but also foster long-term business success and resilience in a rapidly evolving marketplace.
The Applicability of Collaborative Writing in the Post-Graduate Context
Authors: Kırmızı Özkan
Published: August 2024

The present study aims to explore post-graduate EFL learners' perceptions, emotions, emotion regulation, and agentic engagement during an argumentative CW task. The procedure lasted around six weeks during which the post-graduate learners completed one argumentative task collaboratively. Data was collected through session evaluation forms, overall evaluation forms, critical incident analysis, as well as follow-up semi-structured interviews. For critical incident analysis, the learners were asked to identify the critical incidents they have experienced during the CW task and draw a plot of them. This enabled the leaners to see the process retrospectively. The session and overall evaluation forms provided substantial data regarding how the participants viewed CW process and what emotions they went through. Semi-structured interviews were conducted based on the critical incidents. Based on the findings, the study makes an overall evaluation of the applicability of CW at post-graduate level and proposes the flexible collaborative writing model based on the findings.
Community-Based Service-Learning Projects for Linguistically Responsive Teachers
Authors: Atlamaz Tuba Arabacı
Published: August 2024

As the student body becomes more diverse around the world, teachers may not be ready to teach in these diverse classrooms. Community-based service-learning (CBSL) projects in teacher education seems an effective solution to prepare pre-service teachers (PSTs) for these diverse populations, which is examined in this chapter. The CBSL project was part of a semester-long course, examined also in a larger study. This chapter analyzes three PSTs' stories using the framework by Lucas and Villegas, emphasizing knowledge, skills, and dispositions for linguistically responsive teachers (LRT). The findings showed that close interaction with the community members have benefits for PSTs. They recognized and enhanced their knowledge and dispositions towards ELLs. Moreover, they gained specific strategies to be used in the future. This chapter aims to add to the literature on teacher education by promoting more thorough planning for CBSL projects to prepare mainstream/content area teachers for culturally and linguistically diverse communities.
Pre-Service English Language Teachers Preparedness to Teach English
Authors: Kaya İbrahim , Subaşı Gonca
Published: August 2024

Pre-service English language teacher preparedness has historically been debated primarily over a range of issues. Research on preservice teacher preparedness has gained increasing attention and a great body of research on the topic has been conducted. In this chapter, the authors provided ample insight into pre-service English language teacher education, and conceptualized preparedness to teach in English language teaching. Additionally, they examined the concept of preparedness to teach under six major categories: (a) Preparedness to teach English, (b) preparedness to teach English in varying settings, (c) preparedness to teach English to young learners, (d) preparedness to teach English about practicum, (e) preparedness to teach English about efficacy, and (f) preparedness to teach English and technology use. The authors summarized the relevant research under each major category. To conclude, despite the range of categorization driven, there is still a need for research on the topic for researchers and recommendations teacher educators stated at the end of the chapter.
Unraveling the Inner Workings of Massive Language Models
Authors: Babu C. V. Suresh , Anniyappa C. S. Akkash , Sastha B. Dharma
Published: August 2024

This study explores the evolution of language models, emphasizing the shift from traditional statistical methods to advanced neural networks, particularly the transformer architecture. It aims to understand the impact of these advancements on natural language processing (NLP). The study examines the core concepts of language models, including neural networks, attention, and self-attention mechanisms, and evaluates their performance on various NLP tasks. The findings demonstrate significant improvements in language modeling, especially in dialogue generation and translation. Despite these advancements, the study highlights the need to address ethical issues such as bias, fairness, privacy, and security for responsible AI deployment.