Reviewerly/exHarmony huggingface dataset:
Advantages and Disadvantages of a Virtual Engineering Experience During COVID-19 for Blind and Low-Vision High School Students

Abstract The purpose of this research paper is to describe the advantages and disadvantages of conducting an engineering program experience for blind and low-vision (BLV) high school students in an online, virtual format. This study investigated an online offering of the Engineering Quotient (EQ) program administered by the National Federation of the Blind (NFB). Traditionally, the program is offered in-person at the NFB's headquarters. However, due to the COVID-19 pandemic, the program was conducted fully online for four weeks during the summer of 2021. This program aimed to introduce STEM content and engineering thinking skills, such as spatial ability, to BLV youth. Prior to this study, there has been little research exploring interventions specifically targeted toward BLV populations in order to improve their spatial ability, a construct which has been demonstrated to strongly predict positive outcomes in STEM fields. Interventions such as the EQ program provide opportunities for BLV youth to engage with content that encourages them to use spatial thinking skills and may result in more sophisticated spatial ability skills upon completion. Qualitative analysis of interviews with participants revealed that they had both positive and negative experiences with the online EQ program. For example, participants said that they enjoyed the program being online because it allowed them to have more flexibility in when and how they completed the activities. Participants were able to engage in the EQ program activities while also attending other summer activities, social events, and family obligations. Another advantage of the virtual program was the ability to participate from any physical location. For some students, traveling to a program site in another city or state was a barrier for their participation in engineering programs. In contrast, participants said that the virtual nature of the program made it difficult to follow along and complete some of the activities. They indicated that following verbal origami instructions in a virtual environment was difficult, especially if they missed a step or were confused along the way. Additionally, some students would have benefited from being able to receive hands-on guidance for difficult activities. The inability to receive tactile feedback on a completed origami fold or the selection of a drawing line type contributed to students feeling lost or confused throughout an activity. Results from this study can be used to inform both in-person and virtual program design for BLV students to target their spatial ability and interest in STEM fields. More broadly, by providing BLV students with more opportunities to access STEM content that improves their spatial thinking skills, individuals from this population may be further encouraged to pursue STEM pathways. Keywords: online learning, blind and low-vision engineering, origami activities
Assessing Head- Hand- and Heart-Related Competencies through Augmented-Reality

Abstract This work in progress paper presents an assessment framework for an authentic learning activity in augmented reality (AR). Constant changes in technical and societal needs require educational programs to constantly rethink the status quo and explore ways to align future professionals' formal education with emerging workforce demands. Such is critical for all professions — including those in the architecture, engineering, and construction (AEC) industry. While many may agree on the need to do this, what is less clear is the scholarly approach required for undertaking such an endeavor. Insights from studies associated with the Preparation for the Professions Program led by the Carnegie Foundation for the Advancement of Teaching offer a framework used for exploring professional preparation across professions is commonly referred to as the Three Apprenticeships—namely, Apprenticeships of the Head, the Hand, and the Heart. Within engineering-related fields, academic preparation for the profession primarily focuses on technical knowledge; but there is a need for more holistic, integrated learning experiences that involve different kinds of knowledge (Head), skills (Hand), and professional judgment (Heart). This study leverages the Three Apprenticeship framework to assess an integrated learning AEC experience in augmented reality (AR) by using real-time data collected from participants. Using the context of a children's playground, participants were asked to redesign an existing play structure to better meet the needs of children, parents, and other stakeholders within the community. A five-metric assessment was developed to operationalize the head, hand, and heart constructs in this context and measure participants' ability to think holistically in an authentic learning experience. These five assessment metrics included cost, time, safety, sustainability, and fun. This paper explores the development of this assessment and shares preliminary findings from the study.
Literacy assessment - a case study in diagnosing and building a struggling reader’s profile

Poor language and literacy abilities negatively impact students emotionally, causing low self-esteem, anxiety, and frustration. This affects their attitudes towards learning, reduces motivation, and limits opportunities. Thus, addressing early language and literacy challenges through intervention and accurate assessment is vital for not only positive emotional development but for all round academic growth. In a single-case study, the reading skills of a struggling third grade reader were assessed using tools such as QRI (Qualitative Reading Inventory) and visual-discrimination assessments to create a diagnostic profile. The study aimed to identify the student's reading level, and factors that affect language and literacy abilities. Results showed that the student's instructional reading level was at a low average range for expository texts but at a much higher level (fourth) for narrative texts. Strong word recognition skills were observed, but difficulty in comprehending expository, informational texts was evident. Recommendations include using targeted strategies to improve comprehension skills at all levels (literal, inferential, evaluative) for expository texts, while also addressing the emotional and social development of learners. / Keywords: literacy assessment, struggling reader, language and literacy, case study, elementary education
Analysis of Sinusoid Plus Random Telegraph Noise in Nonlinear Devices: Series Characteristic Function Method

Random telegraph noise (RTN) is a common phenomenon in semiconductors, and it is often desired to quantify the effect of the observed RTN on circuits. In this paper we show that the series form of the characteristic function method of nonlinear analysis is suitable for modeling and predicting the output correlation and spectrum of a combination of signals and RTN. We derive the general characteristic function for RTN defined by a single transition parameter, and its spectrum identified as Lorentzian (Cauchy), proportional to the reciprocal of the square of frequency. We then show how the output spectrum is a weighted sum of the respective spectra of the input sinusoid and RTN. Using a simple large-signal model of a MOSFET amplifier, we compute the contributions to the output spectrum as SNR and sinusoid amplitude are varied, and present numerical results. The procedure is easily adapted for other signals and nonlinear circuits.
Two Heads Better than One: Dual Degradation Representation for Blind Super-Resolution

Previous methods have demonstrated remarkable performance in single image super-resolution (SISR) tasks with known and fixed degradation (e.g., bicubic downsampling). However, when the actual degradation deviates from these assumptions, these methods may experience significant declines in performance. In this paper, we propose a Dual Branch Degradation Extractor Network to address the blind SR problem. While some BlindSR methods assume noisefree degradation and others do not explicitly consider the presence of noise in the degradation model, our approach predicts two unsupervised degradation embeddings that represent blurry and noisy information, respectively. The SR network can then be adapted to blur embedding and noise embedding in distinct ways. Furthermore, we treat the degradation extractor as a regularizer to capitalize on the differences between SR and HR images. Extensive experiments on several benchmarks demonstrate that our method achieves SOTA performance in the blind SR problem.
Illuminating The Path To Enhanced Resilience Of Machine Learning Models Against The Shadows Of Missing Labels

The sensitivity of state-of-the-art supervised classification models is compromised by contamination-prone biomedical datasets, which are vulnerable to the presence of missing or erroneous labels (i.e., inliers). From codon frequencies, electrocardiogram signals, biomarkers, morphological features, and patient questionnaires, we attempted to cover a wide range of typical biomedical databases exposed to the risk of inlier contamination. In some very niche fields, such as image recognition, missing labels have received a lot of attention, but in Life Sciences, where outliers are almost systematically filtered, inliers have remained orphans. Our study introduced a pragmatic and innovative methodology that consists of upcycling one-class semi-supervised anomaly detection models for filtering potential inliers in training datasets. By validating this methodology and benchmarking five one-class semi-supervised models and two ensemble methods were benchmarked against various traditional classifiers on 6 databases with 10 different contamination levels and 10 random samplings, achieving an average Matthews correlation coefficient of 78±17% in validation, whereas 22 supervised classifiers achieved an average score of 81±9% trained with the complete and uncontaminated trainset. Therefore, by filtering the training set with an isolation forest, the average resilience to inliers of 22 tested Machine Learning models increased from 69±11% to 95±1%, including neural networks and gradient-boosting methods. Taken together, our study showcased the efficacy of our versatile approach in enhancing the resilience of Machine Learnig models and highlighted the importance of accurately addressing the inliers challenge in the domains of Life Sciences.
Body: between sacrum and profanum – a report

Body: between sacrum and profanum is an international conference organized in the Department of Modern Languages and the Department of German Studies at the University of Zielona Góra, Poland on November 28-29, 2023. The conference was organized within the ninth edition of Foreign Languages Days (known in Polish as Dni Języków Obcych - DJO) held annually since 2015 in the Department of Modern Languages and the Department of German Studies at the Faculty of Humanities. The conference had the honorary patronage of the Rector of the University of Zielona Góra, Professor Wojciech Strzyżewski.
Tuning the initial phase to control the final state of a driven qubit

A driven quantum system can experience Landau-Zener-St\"uckelberg-Majorana (LZSM) transitions between its states when the respective energy levels quasicross. If this quasicrossing is traversed repeatedly under periodic driving, the trajectories can interfere either constructively or destructively. In the latter case, known as coherent destruction of tunneling, the transition between the energy states is suppressed. Even for the double-passage case, the accumulated phase difference (also referred to as the St\"uckelberg phase) can lead to destructive interference, resulting in no transition. In this paper, we discuss a similar process for the single-passage dynamics. We study the LZSM single-passage problem starting from a superposition state. The phase difference of this initial state results in interference. When this results in either a zero or a unit transition probability, such a situation can be called single-passage complete localization in a target state. The phase can be chosen so that the occupation probabilities do not change after the transition, which is analogous to the problem of transitionless driving. We demonstrate how varying the system parameters (driving velocity, initial phase, initial detuning) can be used for quantum coherent control.
Automating Grading System for Faculty and Students

Use of some common Microsoft Excel functions, e.g., SUM, AVERAGE, can substantially reduce the drudgery of processing individual student grades to the final form of letter grades.This self developed Excel spreadsheet system may work better than many commercially available grade processing software because of its flexibilities to meet the needs by the department, college, and as well as by any accreditation authority.This spreadsheet system can be modified or updated any time to suit the individual courses and tastes.This paper describes the steps of developing of an Excel grading file assuming some usual weight distribution for a course.It starts with a blank spreadsheet and shows the development of the automatic grading system by using some functions, such as, AVERAGE(), SUM(), COUNTA(), COUNTIF(), LOOKUP(), STDEVA(), MEDIAN(), MODE(), and MIN().Once these functions are in effect, the only job remains for the instructor, is to input the raw numerical scores on homework, project or test into the sheet.With each entry of scores at any time throughout a semester, the sheet shows the current letter grades of students, class statistics as well as graphical displays of various measures of the class.A partially modified electronic file, excluding the student names and any grades, can be distributed to the students at the beginning of a semester.This will make the students aware of their progress status throughout the semester thus guiding them in determining how much extra effort they might need to add in order to obtain a desired letter grade in a course.
The Electronic Boycott of Foreign Products and its Impact on the Purchasing Rate of the Jordanian Consumer for Products from Beirut Lights Company for Hygienic Paper Manufacturing

This study investigated the effect of an electronic boycott of foreign products on the purchasing rate of Jordanian consumers for products from Beirut Lights company for hygienic paper manufacturing. This study collected data from 310 consumers purchasing products from Beirut Lights Company for Hygienic Paper Manufacturing using questionnaires. This study employed the Partial Least Square Structural Equation Modelling (PLS-SEM) approach and analysed the data. The results revealed that electronic boycotts (consumer animosity, consumer ethnocentrism, consumer efficacy, and product judgment) have significant and positive effects on purchasing rates. The results revealed that a 1% increase in Consumer Animosity would lead to an 18.5% increase in Purchasing Rate. Additionally, the results demonstrated that Purchasing Rate would increase by 15.2 percent with a 1% increase in Consumer Efficacy. Also, the results revealed that a 1% increase in Consumer Ethnocentrism would lead to a 23.5% increase in Purchasing Rate. Similarly, the results revealed that a 1% increase in Product Judgement would lead to a 44.1% increase in Purchasing Rate. For Western multinational corporations focused on expanding their foothold in the world's biggest consumer market, this study's conclusions have crucial consequences for decision-makers and management. The suppressed and intense emotion of hostility, which is a remnant of past hostilities, needs much more attention from the Beirut lights firm, which manufactures hygiene paper in Jordan. In other hostile market scenarios, the conclusions of this examination may be applicable to a strategic study of the boycott model.
Digital Systems Teaching and Research (DSTR) Robot: A Flexible Platform for Education and Applied Research

The DSTR (pronounced "Disaster") robot has a strong history of being adaptable to different user's needs, and there are many opportunities ahead that indicate that the sky, quite literally, is not the limit for this robust platform.This paper provides a historical perspective on the development of the DSTR robot as a collaborative design developed by the Mobile Integrated Solutions Laboratory (MISL) at Texas A&M University and ASEP 4X4 Inc.Texas Instruments has been a major partner in the integration of the control electronics, and Texas Space Technology Applications and Research (T STAR) LLC has played a significant role in the propagation of the DSTR robot as an adaptable applied research/education/STEM outreach platform.The paper will present examples of the strong industry-academic relationships that allow the DSTR robot to be utilized in a multitude of experiential learning environments.In addition to a number of STEM outreach activities, the DSTR robots are being used in the Introduction to Engineering course at Blinn College and in the Freshman Engineering curriculum at Texas A&M University.DSTRs have also been selected by NASA scientists as a low-cost lunar sample collector.The paper will also discuss the newly developed DSTR-E (DSTR Engineering) unit which requires students to perform several engineering tasks during the build process.The paper will also include the lessons learned from initial design through its transfer to the private sector for commercialization and future plans.
The Role of Computer Technologies in Music Teacher Training: Implementing the Humane Education Strategy

The ever-evolving nature of society dictates educational policies, which is mirrored in the challenges of training music teachers in higher education. Pedagogical universities are constantly investigating ways to revolutionize education and introduce new pedagogical tools. This article analyzes the experiences, difficulties and directions of music teacher training in the scope of the humane education strategy. Surveying the condition of music education, its current status and potential for progress has demonstrated that the career of a musician-educator is and will remain in high demand as long as it is augmented with new professional content. This can be used to broaden the role of a music teacher in both regular and extra schooling, such as designing and implementing numerous musical and creative progression programmes. Importantly, the article delves into the issue of developing a model for teaching information technologies to future music teachers, which follows an interdisciplinary and context-oriented content selection principle. It advocates for a comprehensive approach to shaping a continuous sequence of educational subjects throughout the entire period of university education. It also highlights the integration of music and computer technologies as a means of teaching information technology and as a subject for study. Finally, the article highlights the significance of computer technologies in training future music teachers as there is a growing demand for music education specialists who are proficient in the technological processes associated with music software and can effectively employ computer technologies in their professional duties.
When University Met Industry

Abstract When University Met Industry Abstract With rapidly evolving technologies, the academia – industry collaboration on education and research has never been more important. Traditionally, academic institutions educate industry professionals before they enter the workforce, and the industry provides funding for universities on research projects. However, the current one-way flow of education and research can be enhanced by creating a more diverse and interactive dynamic to comprehensively address the ongoing challenges faced by both parties. This paper discusses the importance and challenges of industry and academic collaborations as well as strategies for successful academia – industry partnerships based on the newly established power engineering program at George Mason University.
Development of a Joint Cybersecurity Graduate Program at Mercer University

Abstract This paper discusses the development of a new MS in Cybersecurity program at Mercer University. This is a joint program between the School of Engineering, the Computer Science program (in the College of Liberal Arts and Sciences), and the School of Business. This program requires 30 credit hours, and it has three different tracks. The program also includes 12 credit hours of common core. This paper discusses how the program will be assessed, and how the program aligns with the NICE framework.
Classification of Java Cities/Regencies Based on Human Development Index Using Discriminant Analysis and Naïve Bayes Classifier

Aims: This research aims at grouping of cities/regencies on the island of Java, where the central government as well as the most densely populated island in Indonesia, using linear discriminant analysis (LDA) and Naïve Bayes Classifier (NBC).&#x0D; Study Design: Quantitative design.&#x0D; Place and Duration of Study: Sample: The data used in this study is secondary data from the Indonesian Central Statistics Agency (Badan Pusat Statistik, BPS) regarding the 2022 Human Development Index (HDI) from 119 cities/regencies on the island of Java. The data used are four HDI indicators as independent variables (long and healthy living, knowledge, and the dimensions of decent living standards) and the HDI value as the dependent variable.&#x0D; Methodology: The grouping was carried out using LDA and NBC. LDA is a type of multivariate analysis used in the dependency method where the relationship between variables can be distinguished between the independent variable and the dependent variable. It aims at obtaining discriminant function equations to group cases into certain groups and to determine differences between groups based on independent variables. Meanwhile, the NBC method is a simple probability-based prediction technique based on the application of Bayes' theorem (Bayes' rule) with a strong assumption of independence.&#x0D; Results: Both LDA and NBC can be used for prediction and classification. Based on the results of the discriminant analysis, three discriminant functions were formed to group cities/regencies on the island of Java into three HDI groups. In the NBC analysis, the prior probability value for the very high category HDI group was 0.211, the high category HDI group was 0.606, and the medium category HDI group was 0.183. The research results show that LDA is better than the NBC for grouping cities/regencies based on the 2022 HDI indicators with an accuracy rate of 72.92%. Meanwhile, the NBC analysis only provides an accuracy of 64.58%. Three discriminant functions have been obtained to group cities/regencies on the island of Java based on the largest discriminant score where life expectancy makes the largest contribution in distinguishing each group.&#x0D; Conclusion: As a result, in this case LDA is a better classification method than the NBC. It is also of important to note medium class regions for further actions from stakeholders.
APPLICATION OF UTAUT IN ASSESSING VIRTUAL KITCHEN ADOPTION AMONG LICENSED RESTAURANTS IN KENYA

The growing demand for dine-out consumption in Kenya, fueled by the influx of online food delivery (OFD) platforms, necessitates the adoption of a new restaurant business model known as virtual kitchens (VKs). As an emerging phenomenon in Kenya, this study used the UTAUT theory to evaluate the determinants of VK adoption among licensed restaurants in Kenya by surveying 149 restaurant managers/owners. The regression analysis results show that performance expectancy, effort expectancy, facilitating conditions, and price value all have a significant effect on the intention to use VKs (F [4, 144] = 20.662, p &lt; .01, R2 =.365). The study not only adds to the existing body of knowledge debate on VK adoption by providing informative insights on VK adoption in Kenya, but it also contributes to industry practice.