Reviewerly/exHarmony huggingface dataset:
An extended model for the kinematic identification of a tiltable laser plane in adaptive light-section triangulation

Optical triangulation metrology is an essential part of modern industrial quality assurance. Due to their robustness and cost-effectiveness Laser Light Section Sensors have become a widespread solution for geometry inspections. The configuration of a measurement system involves balancing the size of the measurement volume against the accuracy to be achieved. Therefore, in order to provide accurate measurements on a larger scale, it is required to combine several individual measurements of different configurations. This study thus investigates the identification of parameters of a focus-adjustable triangulation sensor. Adaptability of the working distance is achieved by automatic focusing of the camera and repositionability of the laser with a piezo rotation stage and a mirror. The movement of the projected laser plane has to be identified with regard to the tilting angle. This ensures accurate calibration of the measuring system while the working distance being adjustable. Two general approaches are suitable for solving this task: One is based on a simplified identification of the rotational axis of the tilted laser plane. However, this does not take into account the deviations resulting from the offset of the reflection axis on the mirror surface and the rotational axis. This paper extends conventional models by deriving the position of the projected plane from the complete set of all rigid body transformations with regard to the rotation angles. The position of the laser source, the rotation axis and the mirror surface are described in the camera coordinate system. The validity of the extended model is assessed in comparison with a simplified model. Furthermore, the influence of the focusable camera on the calibration of the laser rotation axis is further investigated.
TEACHING: A Computing Toolkit for Building Efficient Autonomous appliCations Leveraging Humanistic INtelliGence

TEACHING proposes a distributed, trustworthy AI integrating continuous human feedback, supporting CPSoS application design and deployment. TEACHING envisions an intelligent environment, empowering humans through cybernetic assistance. It advances autonomous safety-critical systems, improving safety, reliability and acceptability through human-centred design and formal validation crossing paradigms. TEACHING brings humans and AI together, enabling participatory development, optimisation and oversight.
Development of a full-field polarization interferometer for measurement of wafer surface profile

This research presents a novel polarization interferometer using a polarization camera for accurate and reliable wafer surface profile measurement. The proposed technique employs Fizeau-type polarization interferometry to acquire polarization interference patterns, from which four phase-quadrature interference patterns are obtained. By applying a phase-shifting algorithm, the wafer surface profile can be determined. Experimental testing demonstrates the effectiveness of the proposed system, offering precise and accurate results. Compared to existing techniques, it offers advantages such as high measurement resolution, fast measurement speed, and full-field capability. These features make it a promising solution for improving quality control and manufacturing efficiency in the semiconductor industry, leading to enhanced product performance and increased competitiveness.
Improved 3D form profiler based on extending illumination aperture

We recently demonstrated that the 3D shape of micro-parts can be measured using LED illumination based on contrast evaluation. The technique is based on imaging the object under test using partially coherent illumination. The limited spatial coherence of LED illumination was utilized to discriminate depth. For a fast depth scan without mechanically moving parts, an electrically tunable lens (ETL) in a 4f optical configuration is used. This approach is efficient, takes less than a second to capture all required images, is eye-safe, and offers a depth of focus of a few millimeters. However, the main limitation of the proposed approach arises from the underlying assumption that a small angle of variation of illumination is required. Such a small illumination aperture affects the axial scan resolution that dominates the measurement uncertainty. In the present paper we propose a method to overcome the main limitation of the above-mentioned profiling technique. The approach combines measurements with multiple illumination directions achieved by illuminating the object simultaneously with several independent light sources. In this way, the full-width half maximum of the contrast envelope is reduced. A tilted metallic plate is used for proof of concept.
The Nyquist criterion and its applicability in phase-stepping digital shearography

Phase-stepping shearography is a useful speckle interferometric technique having wide applicability in various fields. Nyquist criterion has long been considered to be the gold standard in signal processing and imaging. This criterion states that the spatial frequency of image sampling should be more than twice the maximum spatial frequency in the image. As applied to speckle imaging in shearography, this implies that, if a two-dimensional charge-coupled device (CCD) is used for imaging, the pixel separation of the CCD device should be half of the minimum feature size in the image, or half of the speckle size. We examined the applicability of the Nyquist criterion in image sampling in phase-stepping shearography. We used a shearographic system employing a 24-megapixel digital still camera and a Michelson interferometer based shearing arrangement. We generated phase maps from a deformed object, which was a center-loaded thin aluminum plate fixed at the periphery. For a given amount of deformation and image shear, detailed phase maps where generated using the 4+4 phase stepping protocol for a different F-numbers, representing different sampling situations, ranging from the sub-Nyquist domain (undersampling) through the Nyquist domain, to the above-Nyquist (oversampling) domain. From the generated phase maps and quantitative measurements, we show that adherence to the Nyquist criterion is not a strict requirement in digital shearography. Operation in the sub-Nyquist domain is acceptable, even desirable, in many cases. Phase maps of good contrast and quality, with or without filtering, can be generated in the sub-Nyquist domain, which can be useful in strain analysis and non-destructive testing applications.
A Comparison of Summarization Methods for Duplicate Software Bug Reports

Bug reports vary in length, while some bug reports are lengthy, others are too brief to describe bugs in detail. In such a case, duplicate bug reports can serve as valuable resources for enriching bug descriptions. However, existing bug summarization methods mainly focused on summarizing a single bug report. In this paper, we focus on summarizing duplicate bug reports. By doing so, we aim to obtain an informative summary of bug reports while reducing redundant sentences in the summary. We apply several text summarization methods to duplicate bug reports. We then compare summarization results generated by different summarization methods and identify the most effective method for summarizing duplicate bug reports. Our comparative experiment reveals that the extractive multi-document method based on TF-IDF is the most effective in the summarization. This method successfully captures the relevant information from duplicate bug reports, resulting in comprehensive summaries. These results contribute to the advancement of bug summarization techniques, especially in summarizing duplicate bug reports.
Speaker Recognition Based on the Joint Loss Function

The statistical pyramid dense time-delay neural network (SPD-TDNN) model makes it difficult to deal with the imbalance of training data, poses a high risk of overfitting, and has weak generalization ability. To solve these problems, we propose a method based on the joint loss function and improved statistical pyramid dense time-delay neural network (JLF-ISPD-TDNN), which improves on the SPD-TDNN model and uses the joint loss function method to combine the advantages of the cross-entropy loss function and the comparative learning of the loss function. By minimizing the distance between speech embeddings from the same speaker and maximizing the distance between speech embeddings from different speakers, the model could achieve enhanced generalization performance and more robust speaker feature representation. We evaluated the proposed method’s performance using the evaluation indexes of the equal error rate (EER) and minimum cost function (minDCF). The experimental results show that the EEE and minDCF on the Aishell-1 dataset reached 1.02% and 0.1221%, respectively. Therefore, using the joint loss function in the improved SPD-TDNN model can significantly enhance the model’s speaker recognition performance.
The effect of spatial resolution on deep learning classification of lung cancer histopathology

The microscopic analysis of biopsied lung nodules represents the gold-standard for definitive diagnosis of lung cancer. Deep learning has achieved pathologist-level classification of non-small cell lung cancer histopathology images at high resolutions (0.5-2 µm/px), and recent studies have revealed tomography-histology relationships at lower spatial resolutions. Thus, we tested whether patterns for histological classification of lung cancer could be detected at spatial resolutions such as those offered by ultra-high-resolution CT.We investigated the performance of a deep convolutional neural network (inception-v3) to classify lung histopathology images at lower spatial resolutions than that of typical pathology. Models were trained on 2167 histopathology slides from The Cancer Genome Atlas to differentiate between lung cancer tissues (adenocarcinoma (LUAD) and squamous-cell carcinoma (LUSC)), and normal dense tissue. Slides were accessed at 2.5 × magnification (4 µm/px) and reduced resolutions of 8, 16, 32, 64, and 128 µm/px were simulated by applying digital low-pass filters.The classifier achieved area under the curve ≥0.95 for all classes at spatial resolutions of 4-16 µm/px, and area under the curve ≥0.95 for differentiating normal tissue from the two cancer types at 128 µm/px.Features for tissue classification by deep learning exist at spatial resolutions below what is typically viewed by pathologists.We demonstrated that a deep convolutional network could differentiate normal and cancerous lung tissue at spatial resolutions as low as 128 µm/px and LUAD, LUSC, and normal tissue as low as 16 µm/px. Our data, and results of tomography-histology studies, indicate that these patterns should also be detectable within tomographic data at these resolutions.
Security in defect detection: A new one-pixel attack for fooling DNNs

The Industrial 5.0 Model integrates enabling technologies such as deep learning, digital twins, and the meta-universe with new development concepts. However, model and data security may pose challenges for developing zero-defect production and other industrial manufacturing industries. To address this issue, we generate adversarial examples using a one-pixel attack in adversarial machine learning, which can fool the defect detection classification model. The traditional one-pixel attack based on the Differential Evolution (DE) algorithm has limited global search ability. Therefore, we use a novel algorithm called Teaching and Learning-based Moth-Flame Optimization (TLMFO), which enhances the global search performance and improves the attack effectiveness. We evaluate TLMFO on benchmark functions and attacks on Cifar10 and ImageNet datasets, and compare it with MFO and DE. The results show that TLMFO outperforms both MFO and DE in terms of accuracy and speed of convergence. Moreover, TLMFO achieves notably better attack effectiveness than DE under targeted and untargeted attacks on the Cifar10 dataset and under-targeted attacks on the ImageNet dataset. Our research confirms that safety prevention is a link worth considering in developing Industry 5.0.
Cybersecurity Considerations in the Development of Enterprise Information Systems

Amidst an era characterized by dependence on digital systems, this study delves into the crucial interplay of integrating cybersecurity into contemporary enterprise information system development. Drawing insights from a diverse array of 60 participants, including cybersecurity specialists, information system developers, and decision-makers within organizations, the research reveals unanimous consensus (85%) on the "extremely high importance" attributed to cybersecurity integration. This collective acknowledgement underscores a heightened recognition of the evolving landscape of cyber threats. The identified challenges, encompassing the delicate balance between security and usability, along with the scarcity of proficient experts, mirror the intricate dynamics faced by organizations. The advocated strategies, aligned with established practices, underscore the prominence of risk-based methodologies and adaptive security measures. The influence of regulatory adherence and human factors brings to light nuanced aspects of the subject. Ultimately, the study underscores the compelling need to embed cybersecurity seamlessly into information system development, culminating in resilient, secure, and forward-oriented systems within an interconnected digital milieu
DevOps Practices and their Role in Streamlining Information System Development

This study delves into the realm of modern software development by investigating the role of DevOps practices in streamlining information system development. Employing a qualitative research approach, a blend of in-depth interviews and comprehensive surveys were conducted to capture insights from professionals in software development and operations roles. The findings reveal a prevalent adoption of DevOps practices, with 70% of interviewees and 65% of survey respondents indicating integration. Notably, Continuous Integration (CI) emerged as a cornerstone practice, fostering rapid code integration, while Automated Testing fortified software quality. Enhanced collaboration and reduced lead times signify the potency of DevOps's impact on development cycles. However, challenges in cultural transformation and effective automated testing suites underscore the journey's complexities. Ultimately, the study illuminates DevOps as a catalyst for collaborative agility and a transformative force shaping the software engineering landscape.
Blockchain Technology and its Implications for Information System Development

The potential transformation brought by blockchain technology in information system development is gaining momentum. This research explores the intricate consequences of integrating blockchain into information system development, drawing insights from a group of 30 professionals representing various sectors. Utilizing a mixed-methods approach that combines qualitative interviews and quantitative surveys, the study investigates participants' viewpoints on the advantages, challenges, and recommendations for adopting blockchain. The outcomes reveal substantial recognition (83.3%) of heightened data security and data integrity (76.7%) as primary benefits. Concerns revolve around scalability (70%) and the complexities of system integration (60%). Remarkably, participants envision enhanced operational efficiency (73.3%) and amplified transparency (63.3%) as potential outcomes. Regulatory considerations elicit diverse responses (50%), highlighting the dynamic nature of legal frameworks. Recommendations (80%) include implementing comprehensive training programs and initiating pilot projects (63.3%) to facilitate effective integration. The results enhance the understanding of blockchain's role in information system development, offering guidance to practitioners and organizations for well-informed decision-making amidst a constantly evolving technological landscape.
Breve revisión de los modelos clásicos de Estimación de Esfuerzo para proyectos de desarrollo de Software

A critical synthesis on the most representative models for software development project effort estimation is provided. This work is a basis for a discussion about the methodological and practical challenges which entail the effort estimation field, specially in the mathematical/statistical modelling fundamentals, and its empirical verification in the software industry.
Rendition of Noncanonical Opposition: A Case Study of Qur’anic Composition in Bilingual Transposition

Grammar and meaning, form and function, are two linguistic levels intrinsic and indispensable to reading and rendering the Qur’an, the Divine Word of Islamic Scripture, in a foreign tongue. Nida and de Waard’s (1986) ‘functional equivalence’, an amalgamation of formal equivalence and dynamic equivalence, posits that emphasis in translation activity and practice must also be laid on SL form which must be retained and maintained in TL where possible as long as it performs discourse functions and conciliates SL fidelity and TL legibility. The present study argues that the syntactic frames that host noncanonical oppositions in the Qur’an trigger distinct discourse functions that must be transposed as lexicosyntactic and lexicosemantic translation units into Qur’an translation. Building on a typological analysis of a representative dataset retrieved from Qur’anic Arabic Corpus (QAC), the study reveals remarkable variations among the translators in their renditions of noncanonical opposition frames and functions owing to explicitation and domestication. This study recommends revival and reuse of the grammar-translation method in Qur’an translation when SL meaning and function are based on SL grammar and form.
The Psychological, Social and Economic Effect of The Purchase of The Fake Brand in Ready-To-Wear Sector in The Saudi Arabia: Case Study Done on Saudi Women

The American Marketing Association (2010) defines a brand name as “a name, term, design, symbol, or any other characteristic intended to identify the good or service of a seller and to differentiate it from those of other sellers”. customers interact with several brands and products over the course of their lives and build an attachment to a well-defined brand category (Schouten; MC Alexander 1985), which differs from one consumer to another, which is not always the same and it’s not stable. One of the most important factors interfering here, in this relationship: the values. Those values perceived by this individual justify his consumption of such a product to the detriment of the other. In addition, the existence of a variety or patchwork of brands of “like” products from the same industry puts the consumer in a confusion.
The Effect of Integrating Mobile Application in Workplace English Vocabulary Acquisition

The English language is widely taught in Taiwan, with many students starting their learning at an early age. Despite this, college students at universities of technology are not performing as well as expected in English proficiency. To enhance their employability skills, universities of technology have shifted their focus from everyday English to workplace English, even though the vocabulary size and topics are unfamiliar to students. To improve vocabulary acquisition, this study investigated the effectiveness of mobile applications in comparison to traditional vocabulary learning methods. The study examined how different vocabulary learning tasks and word length can impact short-term and long-term retention among college EFL learners. The results indicated that vocabulary learning tasks can improve short-term memory, with mobile learning being more effective than gap-filling tasks. However, no significant difference was observed in long-term memory retention between the two tasks. Additionally, learners were found to remember longer words better than shorter ones. These findings have practical implications for EFL language pedagogy, as word-focused tasks can aid learners in retaining and acquiring new vocabulary, and offer insights into vocabulary task design. Further research is needed to support these findings.
The Implementation of Mobile Apps in Developing English Speaking Skills among Students at a Vocational School

This study aimed at investigating the perceptions of both teachers and students towards the employment of two educational apps named ELSA Speak and Duolingo in assisting the teaching and learning English speaking skills. To answer the two research questions regarding the perceptions of both stakeholder towards the apps, both quantitative and qualitative methods were used. 295 students who have completed their English course with the integration of ELSA Speak and Duolingo were involved in the process of data collection from a questionnaire followed by an optional open-ended question. Regarding the qualitative data from teachers, 9 English teachers were invited to answer the interview questions. The results revealed that both of these stakeholders have positive feedback on the apps, but several issues were recorded.
Experience in using BYOD approaches in teacher education

A study is described that reveals the advantages and disadvantages of BYOD when conducting exams. The analysis of publications on the topic of the study, confirming the relevance and significance of the study, was carried out. An assessment was made of students' readiness for the implementation of BYOD. Results of the study: the majority of students of KazNPU named after Abai are ready to use their own devices when conducting exams, along with the positive aspects of BYOD technology, security problems and risks are analyzed.
Video Quality Indicators for Video-Based Learning System in Higher Education

Higher education worldwide has adopted Video-Based Learning (VBL) over the past decade. They have tried to build a VBL system to improve services to students. However, the researcher's topic was not fully explored, especially in making the video itself. What features are mandatory and must be considered in making a video lecture to increase student engagement. A systematic review of the literature (SLR) is a way to identify these features. This study provides a critical analysis of the current research in VBL over the last five years (2017 – 2021). It presents a general trend examining 1336 journals and many literary works related to VBL design in Higher Education, selected through a stepwise process based on PRISMA Framework guidelines, using pre-defined selection criteria. We carefully selected 32 journals and found 22 features referring to the Lecture Video Design succession.
Second Language Learning, Literacy and Mobile Learning:

This case study sought to evaluate the effectiveness of a mobile learning software, Duolingo, a data-driven online language learning software with over 35 languages, to enhance students' knowledge acquisition in theory and practical communication. The research was conducted in Sri Lanka for one month with the participation of twenty university undergraduates whom neither have previous knowledge of using the Chinese Language as a Second Foreign Language nor experience using "Duolingo" as a Mobile learning app. Studies revealed that new Chinese language learners who used the Mobile App could enhance their language skills, whilst literacy skills led to successful Mobile learners. The implications of this study revealed that further research at the macro level to compare and contrast the App's effectiveness in the online classroom environment is needed.