Reviewerly/exHarmony huggingface dataset:
Reflections on English Speaking Anxiety of Engineering Students: Pilot Project

Human beings scream for effective communication skills in this modern age of space technology. The 21st-century demands the engineering universities to address the speaking skill deficiencies of engineering students. This research discovers factors responsible for English speaking anxiety of engineering students. A qualitative research design was implemented and semi-structured interviews were piloted. A purposive sampling approach was employed.Outcomes revealed engineering students faced hesitation, poor confidence, poor mental approach,poor English, unknown fears, poor vocabulary, dearth of speaking opportunities, fear of criticism,nervousness, stress, lack of motivation, poor communication skill, poor language, and low self-esteem as English-speaking anxiety factors of engineering students. Additionally, they used deep breathing, giving space for thinking and code switch in gas strategies to overcome English-speaking anxiety.
Connectives and anaphoric reference patterns to negative quantifiers

Moxey and Sanford (1987, 1993a; Sanford, Moxey & Paterson, 1996) observed that negative or monotone decreasing quantifiers appear to allow a broader range of possibilities for prominal reference than do monotone increasing or nonmonotone quantifiers. In particular, a pattern emerges in which reference to the Complement Set is possible, as shown in (1): Not quite all of the fans went to the game. They watched it on TV instead.
Grading on the Fly

We specify a model for the conceptual interpretation of relative adjectives (like “big”), which covers a crucial aspect of the underlying comprehension process - the comparison to a norm that is associated with a comparison class. Building on an elaborate domain ontology and knowledge about intercorrelations, comparison classes are dynamically created depending on the context in which adjectival utterances occur.
The Role of Reflection in Scientific Exploration

In this paper we explore the idea of reflection in the context of scientific exploration. How does an agent reflect upon its behavior in order to enable productive exploration? We outline an abstract cognitive architecture for combining reflection and exploration. To achieve this we present a language for modeling cognition: the Task-Method-Knowledge (TMK) language. We further present a computational model based on this language, ToRQUE2 (Griffith et al., 1997; Griffith, 1997). ToRQUE2 is a model of exploratory reasoning in the domain of scientific problem solving. We claim that the TMK language supports both reflection and exploration, and enables them to benefit from one another.
Comparison in Context

The features of a concept that come to mind depend on the context in which that concept occurs. Tversky (1977) argued that context affects the outcome of a comparison by changing the salience of particular features in the meanings of all items in the comparison set. We investigate further the dynamics of the interaction between context and comparison. We hypothesized that a context given just before a target concept will have far greater influence on the salience distribution of features of that target, than if the context is given just after the target.
Factors Affecting the Satisfaction of Using Testing and Certification Bodies in the Manufacturing Sector

The industry of testing, inspection and certification has been recognized as an industry with an infrastructure that supports the production, so there is a lack of the academic research on the industry of testing, inspection and certification compared to other industries. This study conducted panel analysis related to domestic specialized testing, inspection and certification institutions, which play a pivotal role in the development of the testing, inspection and certification industry. In order to check the factors affecting the satisfaction of specialized testing, inspection and inspection institutions, this paper considered (1) the frequency of use for specialized testing, inspection and certification institutions, (2) the utilization rate, (3) the status of possession of testing, inspection and certification equipments, and (4) the number of use by other institutions as major explanatory variables. As a result, it was concluded that the fixed effect model was suitable to explain the factors affecting the satisfaction of testing, inspection and certification institutions.
Toward A Fine-Grained Analysis of Distribution Shifts in MSMARCO

Recent IR approaches based on Pretrained Language Models (PLM) have now largely outperformed their predecessors on a variety of IR tasks. However, what happens to learned word representations with distribution shifts remains unclear. Recently, the BEIR benchmark was introduced to assess the performance of neural rankers in zero-shot settings and revealed deficiencies for several models. In complement to BEIR, we propose to control \textit{explicitly} distribution shifts. We selected different query subsets leading to different distribution shifts: short versus long queries, wh-words types of queries and 5 topic-based clusters. Then, we benchmarked state of the art neural rankers such as dense Bi-Encoder, SPLADE and ColBERT under these different training and test conditions. Our study demonstrates that it is possible to design distribution shift experiments within the MSMARCO collection, and that the query subsets we selected constitute an additional benchmark to better study factors of generalization for various models.
Modeling Individual Differences in Learning a Navigation Task

Our goal is to develop a cognitive model of how humans acquire skills on complex, sensorimotor tasks. To achieve this goal, we collected data from subjects learning the NRL Navigation task, then used the data to construct a model that reflects the basic, cognitive elements required to learn and thereby succeed at this task (Gordon & Subramanian, 1997). This paper describes a new experiment with human subjects on the task. Data from this experiment not only confirms the key cognitive element of our model, but also helps us better understand individual differences in learning this task. Four evaluation metrics indicate that we are able to model important trends in the evolution of action choice.
A study on Korean culture education methods utilizing regional cultural characteristics: Focusing on foreign students

본 연구는 지역 문화 특성을 활용하여 외국인 유학생을 대상으로 한국어 문화 교육 방안을 제안하는 데에 목적이 있다. 연구결과는 다음과 같다. 첫째, 지역 문화 한국어교육은 구성주의 로 기반하여 개발되어야 한다. 둘째, 부산 지역 문화 특성을 활용한 한국어 문화 교육 내용 구 성의 실제적 자료를 제시하였다. 셋째, 실제적 자료를 활용한 교육방법을 제시하였다. 지역 문 화의 특성을 활용하여 한국어 문화 및 한국어를 가르치는 것은 학습자들의 적극성, 호기심 및 자발성을 높일 수 있으며 자연스러운 의사소통 능력 향상에도 도움이 될 수 있다.The purpose of this study is to propose a plan for Korean culture education for foreign students by utilizing the characteristics of local culture. The research results are as follows. First, local culture Korean education should be developed based on constructivism. Second, practical data on the content composition of Korean culture education using Busan regional cultural characteristics were presented. Third, an educational method using actual data was presented. Teaching Korean culture and Korean language using the characteristics of local culture can increase learners activeness, curiosity, and spontaneity, and can also help improve natural communication skills.
Experiences and Perceptions of Distance Learning among Early Childhood Pre-service Teachers in Korea during the COVID-19 Pandemic

The purpose of this study was to gain an understanding of the experiences and perceptions of distance learning among early childhood pre-service teachers in Korea during the COVID-19 pandemic, which has been spreading worldwide since early 2020. A total of 196 early childhood pre-service teachers with experience in distance learning participated in the survey, and the results of the survey are as follows. While early childhood pre-service teachers perceived a difference between face-to-face (in-person) classes and distance learning, they expressed a high willingness to take part in distance learning in the post-COVID-19 era. Convenience and usefulness were mentioned as key advantages of distance learning, while difficulties in interaction and concentration were emphasised as disadvantages. To improve the quality of distance learning in the future, they suggested that students should increase participation, while instructors should strengthen their distance learning-related capabilities and universities should enhance support through system development. The implications of this study were discussed based on these results.
PROBLEMS OF IMPROVING PROFESSIONAL TRAINING OF FUTURE HISTORY TEACHERS

Views were made on the problems of improving the professional training of future history teachers, as well as the components of their professional skills.
Early Validation of Task Analysis Data: Processes and Representations

Task analysis is a critical first step in understanding a new complex domain. Currently, task analysis is a mostly manual process with weak automation support. This paper introduces the first phase of the SAVVII prototype as a proof-of-concept for early validation of task analysis activities. Early validation is supported by the transference of semantics from data values to data structures. Rough estimations of discrepancies between tasks are used to focus the knowledge elicitor’s attention on questionable areas, thereby reducing much of the tediousness and time-intensive nature of validation. SAVVII was shown to work on the developmental domain of parables. It is currently undergoing experimentation in two real-world knowledge acquisition activities.
Distributed Sorting Architecture on Multiple FPGA

FPGA has demonstrated promising performance in high throughput data sorting. Data compression techniques are adopted to exploit the redundant information between subsequent values in a sorted dataset. However, the standalone FPGA design inhibits the scalability to handle the growing dataset. Moreover, previous data compression techniques in data sorting lack versatility to support various ranges of data. This paper proposes the design of a distributed sorting accelerator on multiple FPGAs and introduce a Configurable Compressed Array to handle the various data widths. The experimental results have shown that the proposed design attains 3.69x enhancement when compared to the previous design.
Solutions to the Catastrophic Forgetting Problem

In this paper we review three kinds of proposed solutions to the catastrophic forgetting problem in neural networks. The solutions are based on reducing hidden unit overlap, rehearsal, and pseudorehearsal mechanisms. We compare the methods and identify some underlying similarities. W e then briefly note some potential im plications of the rehearsal / pseudorehearsal based methods, including their application to sequential learning tasks.
How does economic expansion react to educational expenditure, financial development, and financial integration A nonlinear Granger causality and quantile regression analysis in an Asian perspective

This empirical analysis aspires to adequately investigate the causal effect of financial integration, educational expenditure and financial development on economic growth, by exerting the nonlinear Granger-causality approach. On another hand, it additionally strives to uncover the heterogeneous effect of financial integration, academic expenditure and financial development on the economic growth of nine pertinent Asian economies by employing quantile regression techniques. The consequence of nonlinear Granger causality analysis demonstrates that the nonlinear causality exists from educational spending towards the economic growth in the countries such as Bangladesh, India, China, and Thailand. While on the other hand, no such causality found in civilised nations like Australia, Japan, Korea, Malaysia, and Singapore. The empirical outcome also manifests that if monetary integration, financial development, and educational expenditure happen simultaneously then it leads to economic growth in Bangladesh, China, India, Japan, Malaysia, and Thailand. Additionally the outcome of quantile regression documents that education sector outlay enhances the economic growth of underdeveloped or developing countries while it does not demonstrate a significant impact on the economic growth of the highly developed nations.
Kemegahan Kuil Hindu Batu Caves Malaysia

Batu Caves is a hill lime , having a series of cave-ridden and the temple of the cave , located in the district of Gombak, Selangor, Malaysia. This place named from the river stone, it runs through a hill. Batu caves is also a nearest the names of villages .This cave is one of Hindu temple outside India most popular, dedicated to the hindu god Murugan. This is the point site focus thaipusam hindu festival in Malaysia.Keywords : Batu Caves; Gombak,Selangor; Malaysia; Hindu temple.
Clustering Algorithms

In this chapter, we will look at clustering algorithms or, as I like to call them, K-algorithms. Specifically, I’m referring to the K-nearest neighbor algorithm and the K-means algorithm. These algorithms are finding extensive use in classification systems and machine learning systems. These algorithms can become complex and mathematical. However, what we will do is look at the principles of these algorithms without the mathematical details of their implementation and simply use the concepts behind the mathematics to explain them.
Eeadoselfcloud: Energy Efficient Adaptive Depth Optimized Self Cloud Mechanism for VM Migration in Data Centers

Cloud computing is a paradigm where all resources like software, hardware and information are accessed over internet by using highly sophisticated virtual data centres. The cloud has a data center with a host of many features. Each machine is shared by many users, and virtual machines are used to use these machines. With a large number of data centers and data centers with a large number of physical hosts. Two important issues in cloud environment are Load balancing and power consumption which solved by virtual machine migration. In earlier learnings, Artificial Bee Colony (ABC)’s policy could lead to a compromise between productivity and energy consumption. There are, however, two ways in the ABC-based Abstract based approach: (1) How to find effective solutions across the globe. (2) how to reduce the time to decide to distribute BM. To overcome this issue, this project develop one novel VM migration scheme called eado Self Cloud. This proposed method introduces Bee Lion Optimization (BLO) for VM allocation. Data Center Utilization, Average Node Utilization, Request Rejection Ration, Number of Hop Count and Power Consumption are employed as parameters for the proposed algorithm analysis. The experimental results indicate that the proposed algorithm does better than the other available methods.
Weighing the Odds: Probability

In this chapter, we introduce the elements of probabilityProbability theory. In the spirit of the book, we confine ourselves to the discrete case, that is, probabilitiesProbability on finite domainsDomain, leaving aside the infinite case. We begin by defining probability functionsProbability function on a finite sample spaceSample space and identifying some of their basic properties. So much is simple mathematics. This is followed by some words on different philosophiesPhilosophy of probabilityProbability, and warnings of traps that arise in applications. Then back to the mathematical work, introducing the concept of conditional probabilityConditional probability, outlining its behaviour, connections with independenceIndependence, and deployment in Bayes’ rule. An interlude reflects on a curious configuration known as Simpson’s paradoxSimpson’s paradox. In the final section we explain the notions of a payoff functionPayoff function and expected valueExpected value.
Distribution Models

This chapter provides guidelines for sharing cine-VR experiences with others. These approaches can work for both individual and multiuser experiences. There are multiple factors to consider when picking a distribution platform, including cost, quality, audio requirements, and accessibility. Cine-VR should ideally be played on VR headsets with headphones. While in a headset, most surrounding distractions are eliminated; little outside the experience can steal our attention, especially if the peoples use quality headphones. In an era of continuous distractions, this sort of isolation creates a more engaging experience. VR headsets and touchscreen devices like smartphones and tablets have similar hardware components. Both have built-in hardware sensors called gyroscopes and accelerometers. All wireless headsets support streaming content directly to headsets while maintaining decent quality. As mentioned previously, streaming is the easiest solution for mass distribution. Headsets, smartphones, tablets, and web browsers all support streaming natively.
String Theory to M-theory

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Measuring Mobility and Room Occupancy in Clinical Settings: System Development and Implementation (Preprint)

<sec> <title>BACKGROUND</title> The use of location-based data in clinical settings is often limited to real-time monitoring. In this study, we aim to develop a proximity-based localization system and show how its longitudinal deployment can provide operational insights related to staff and patients' mobility and room occupancy in clinical settings. Such a streamlined data-driven approach can help in increasing the uptime of operating rooms and more broadly provide an improved understanding of facility utilization. </sec> <sec> <title>OBJECTIVE</title> The aim of this study is to measure the accuracy of the system and algorithmically calculate measures of mobility and occupancy. </sec> <sec> <title>METHODS</title> We developed a Bluetooth low energy, proximity-based localization system and deployed it in a hospital for 30 days. The system recorded the position of 75 people (17 patients and 55 staff) during this period. In addition, we collected ground-truth data and used them to validate system performance and accuracy. A number of analyses were conducted to estimate how people move in the hospital and where they spend their time. </sec> <sec> <title>RESULTS</title> Using ground-truth data, we estimated the accuracy of our system to be 96%. Using mobility trace analysis, we generated occupancy rates for different rooms in the hospital occupied by both staff and patients. We were also able to measure how much time, on average, patients spend in different rooms of the hospital. Finally, using unsupervised hierarchical clustering, we showed that the system could differentiate between staff and patients without training. </sec> <sec> <title>CONCLUSIONS</title> Analysis of longitudinal, location-based data can offer rich operational insights into hospital efficiency. In particular, they allow quick and consistent assessment of new strategies and protocols and provide a quantitative way to measure their effectiveness. </sec>
Parsing INI Files Using Regexes and Grammars

You’ve probably seen .ini files before; they are quite common as configuration files on the Microsoft Windows platform but are also found in many other places such as ODBC configuration files, Ansible’s inventory files, and so on.
Analysing Sentiment Analysis Twitter Data on Diabetes Cases By Using Bayes Classification

With the rise of social networking approach, there has been a surge ofusers generated content all over the world and with that in an erawhere technology advancement are up to the level where it could putus in a step ahead of pathogens and germination of diseases, wecouldn’t help but to take advantage of that advancement and providean early precaution measures to overcome it. Twitter on the other handare one of the social media platform that provides access towards ahuge data availability. To manipulate those data and transform it intoan important information that could be used in many different scopethat could help improve people’s life for the better. In this paper, wegather a total of six algorithm from Bayes Classifier to comparebetween them on which algorithm suited the most with the diabetesdataset. This research are using WEKA as the data mining tool fordata analyzation
Comparison of the Least-Squares Regression Line and a Truncated Discrete Fourier Transform when describing Linearly Correlated data

For long, the least squares regression line has been a primary tool for analyzing linear data. In this paper, the author suggests a method involving a truncated fourier transform that would achieve everything the least squares method achieves and more, including details about the magnitude of deviation.
Software Engineering Mathematics

Chapter 19 discusses software engineering and the mathematics to support software engineering. We discuss traditional software engineering including the activities in the waterfall lifecycle model. We discuss early mathematical work in software engineering including Floyd’s work on assertions which influenced C. A. R. Hoare.
Analisis Kesalahan Berbahasa Bidang Ejaan pada Essay Festifal of Agri-Science and Technology (FAST) 2015

ABSTRACTIndonesia is rich in culture and traditional languages, however, the main language remains Indonesian. Talking about Indonesian as the main language to Indonesian as a unifying nation, in its use has increasingly led to the study of the problem of language phenomena for Indonesian language management, ranging from students, students, lecturers, to administrators of the central language. All have a role to make the study of linguistic phenomena so that their use is more appropriate. Therefore, researchers want to take part in contributing studies to improve language by conducting research related to one of the language phenomena. The study was conducted to find out and explain linguistic phenomena, especially in the spelling level of Essay FAST 2015. This research is descriptive qualitative. Data collection using techniques (1) data collection (2) identification of language errors in accordance with the level of language (3) ranking errors (4) correcting errors. The results of this study indicate an error in writing capital letters, punctuation, and italics. Based on these findings, the results of the analysis can be a reference material for researchers, educators, and students so that the work created is better.
Feature Engineering Techniques to improve Identification Accuracy for Offline Signature Case-Bases

Handwritten signatures have been widely acclaimed for personal identification viability in educated human society. But, the astronomical growth of population in recent years warrant developing mechanized systems to remove the tedium and bias associated with manual checking. Here the proposed system, performing identification with Nearest Neighbor matching between offline signature images collected temporally. The raw images and their extracted features are preserved using Case Based Reasoning and Feature Engineering principles. Image patterns are captured through standard global and local features, along with some profitable indigenously developed features. Outlier feature values, on detection, are automatically replaced by their nearest statistically determined limit values. Search space reduction possibilities within the case base are probed on a few selected key features, applying Hierarchical clustering and Dendogram representation. Signature identification accuracy is found promising when compared with other machine learning techniques and a few existing well known approaches.